Publications by authors named "Ho Sung Kim"

170 Publications

Neuroimaging Findings in Patients with COVID-19: A Systematic Review and Meta-Analysis.

Korean J Radiol 2021 Jul 1. Epub 2021 Jul 1.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.

Objective: Central nervous system involvement in coronavirus disease 2019 (COVID-19) has been increasingly reported. We performed a systematic review and meta-analysis to evaluate the incidence of radiologically demonstrated neurologic complications and detailed neuroimaging findings associated with COVID-19.

Materials And Methods: A systematic literature search of MEDLINE/PubMed and EMBASE databases was performed up to September 17, 2020, and studies evaluating neuroimaging findings of COVID-19 using brain CT or MRI were included. Several cohort-based outcomes, including the proportion of patients with abnormal neuroimaging findings related to COVID-19 were evaluated. The proportion of patients showing specific neuroimaging findings was also assessed. Subgroup analyses were also conducted focusing on critically ill COVID-19 patients and results from studies that used MRI as the only imaging modality.

Results: A total of 1394 COVID-19 patients who underwent neuroimaging from 17 studies were included; among them, 3.4% of the patients demonstrated COVID-19-related neuroimaging findings. Olfactory bulb abnormalities were the most commonly observed (23.1%). The predominant cerebral neuroimaging finding was white matter abnormality (17.6%), followed by acute/subacute ischemic infarction (16.0%), and encephalopathy (13.0%). Significantly more critically ill patients had COVID-19-related neuroimaging findings than other patients (9.1% vs. 1.6%; = 0.029). The type of imaging modality used did not significantly affect the proportion of COVID-19-related neuroimaging findings.

Conclusion: Abnormal neuroimaging findings were occasionally observed in COVID-19 patients. Olfactory bulb abnormalities were the most commonly observed finding. Critically ill patients showed abnormal neuroimaging findings more frequently than the other patient groups. White matter abnormalities, ischemic infarctions, and encephalopathies were the common cerebral neuroimaging findings.
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http://dx.doi.org/10.3348/kjr.2021.0127DOI Listing
July 2021

Reconstruction of a small defect of the lower vermilion adjacent to white roll using a modified O-Z flap.

Arch Craniofac Surg 2021 Jun 25;22(3):164-167. Epub 2021 Jun 25.

Department of Plastic and Reconstructive Surgery, Kosin University Gospel Hospital, Busan, Korea.

Reconstruction of lip defects is important because the lips play an important role in maintaining aesthetic facial balance, facial expressions, and speech. There are various methods of lip reconstruction such as primary repair, skin grafting, and utilization of local and free flaps. It is important to select a proper reconstruction method according to the size and location of lip defect. Failure to select an appropriate method may result in distortion, color mismatch, sensory loss, and aesthetic imbalance. Herein we present a case of successful aesthetic reconstruction of the lower vermilion. We removed a venous malformation, which was limited to the lower vermilion and adjacent to the white roll, and repaired the defect using the modified O-Z flap.
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http://dx.doi.org/10.7181/acfs.2021.00150DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8257448PMC
June 2021

Refinement of response assessment in neuro-oncology (RANO) using non-enhancing lesion type and contrast enhancement evolution pattern in IDH wild-type glioblastomas.

BMC Cancer 2021 Jun 1;21(1):654. Epub 2021 Jun 1.

Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 05505, Republic of Korea.

Background: Updated response assessment in neuro-oncology (RANO) does not consider peritumoral non-enhancing lesion (NEL) and baseline (residual) contrast enhancement (CE) volume. The objective of this study is to explore helpful imaging characteristics to refine RANO for assessing early treatment response (pseudoprogression and time-to-progression [TTP]) in patients with IDH wild-type glioblastoma.

Methods: This retrospective study enrolled 86 patients with IDH wild-type glioblastoma who underwent consecutive MRI examinations before and after concurrent chemoradiotherapy (CCRT). NEL was classified as edema- or tumor-dominant type on pre-CCRT MRI. CE evolution was categorized into 4 patterns based on post-operative residual CE (measurable vs. non-measurable) and CE volume change (same criteria with RANO) during CCRT. Multivariable logistic regression, including clinical parameters, NEL type, and CE evolution pattern, was used to analyze pseudoprogression rate. TTP and OS according to NEL type and CE evolution pattern was analyzed by the Kaplan-Meier method.

Results: Pseudoprogression rate was significantly lower (chi-square test, P = .047) and TTP was significantly shorter (hazard ratio [HR] = 2.03, P = .005) for tumor-dominant type than edema-dominant type of NEL. NEL type was the only predictive marker of pseudoprogression on multivariate analysis (odds ratio = 0.26, P = .046). Among CE evolution patterns, TTP and OS was shortest in patients with residual CE compared with those exhibiting new CE (HR = 4.33, P < 0.001 and HR = 3.71, P = .009, respectively). In edema-dominant NEL type, both TTP and OS was stratified by CE evolution pattern (log-rank, P = .001), whereas it was not in tumor-dominant NEL.

Conclusions: NEL type improves prediction of pseudoprogression and, together with CE evolution pattern, further stratifies TTP and OS in patients with IDH wild-type glioblastoma and may become a helpful biomarker for refining RANO.
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http://dx.doi.org/10.1186/s12885-021-08414-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170938PMC
June 2021

Development of Brain Metastases in Patients With Non-Small Cell Lung Cancer and No Brain Metastases at Initial Staging Evaluation: Cumulative Incidence and Risk Factor Analysis.

AJR Am J Roentgenol 2021 May 26. Epub 2021 May 26.

Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

While established guidelines give indications for performing staging brain MRI at initial non-small cell lung cancer (NSCLC) diagnosis, guidelines are lacking for performing surveillance brain MRI in patients without brain metastases at presentation. To estimate the cumulative incidence of, and risk factors associated with, brain metastasis development in patients with NSCLC without brain metastases at initial presentation. This retrospective study included 1495 patients with NSCLC (mean age 65±10 years; 920 men, 575 women) without brain metastases at initial evaluation that included brain MRI. Follow-up brain MRI was ordered at referrer physicians' discretion. MRI examinations were reviewed in combination with clinical records for brain metastasis development; patients not undergoing MRI were deemed to have not developed metastases through last clinical follow-up. Cumulative incidence of brain metastases was determined with death as a competing risk and stratified by clinical stage group, cell type, and epidermal growth factor receptor (EGFR) status. Univariable and multivariable Cox proportional hazards regression analyses were performed. A total of 258/1495 (17.3%) patients underwent follow-up brain MRI, and 72/1495 (4.8%) developed brain metastases at a median of 12.3 months after initial NSCLC diagnosis. Among the 72 patients developing metastases, 44% had no neurologic symptoms, and 58% had stable primary thoracic disease. Cumulative incidence of brain metastases at 6, 12, 18, and 24 months was 0.6%, 2.1%, 4.2% and 6.8%, respectively. Cumulative incidence was higher (P<.001) in clinical stage III-IV (1.3%, 3.9%, 7.7%, and 10.9%) than I-II (0.0%, 0.8%, 1.2%, and 2.6%) disease, and higher (P<.001) in EGFR positive (0.7%, 2.5%, 6.3%, and 12.3%) than EGFR negative (0.4%, 1.8%, 2.9%, and 4.4%) adenocarcinoma. Among 1109 patients with adenocarcinoma, independent risk factors for brain metastasis development were clinical stage III-IV (hazard ratio [HR]=9.39; P<.001) and EGFR positivity (HR=1.78; P=.04). Brain metastasis incidence over the study interval was 8.7% in clinical stage III-IV disease and 8.6% in EGFR positive adenocarcinoma. Clinical stage III-IV and EGFR positive adenocarcinoma are independent risk factors for brain metastasis development. Surveillance brain MRI may be warranted 12 months after initial evaluation in clinical stage III-IV disease or EGFR-positive adenocarcinoma.
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http://dx.doi.org/10.2214/AJR.21.25787DOI Listing
May 2021

Generative adversarial network for glioblastoma ensures morphologic variations and improves diagnostic model for isocitrate dehydrogenase mutant type.

Sci Rep 2021 May 10;11(1):9912. Epub 2021 May 10.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea.

Generative adversarial network (GAN) creates synthetic images to increase data quantity, but whether GAN ensures meaningful morphologic variations is still unknown. We investigated whether GAN-based synthetic images provide sufficient morphologic variations to improve molecular-based prediction, as a rare disease of isocitrate dehydrogenase (IDH)-mutant glioblastomas. GAN was initially trained on 500 normal brains and 110 IDH-mutant high-grade astocytomas, and paired contrast-enhanced T1-weighted and FLAIR MRI data were generated. Diagnostic models were developed from real IDH-wild type (n = 80) with real IDH-mutant glioblastomas (n = 38), or with synthetic IDH-mutant glioblastomas, or augmented by adding both real and synthetic IDH-mutant glioblastomas. Turing tests showed synthetic data showed reality (classification rate of 55%). Both the real and synthetic data showed that a more frontal or insular location (odds ratio [OR] 1.34 vs. 1.52; P = 0.04) and distinct non-enhancing tumor margins (OR 2.68 vs. 3.88; P < 0.001), which become significant predictors of IDH-mutation. In an independent validation set, diagnostic accuracy was higher for the augmented model (90.9% [40/44] and 93.2% [41/44] for each reader, respectively) than for the real model (84.1% [37/44] and 86.4% [38/44] for each reader, respectively). The GAN-based synthetic images yield morphologically variable, realistic-seeming IDH-mutant glioblastomas. GAN will be useful to create a realistic training set in terms of morphologic variations and quality, thereby improving diagnostic performance in a clinical model.
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http://dx.doi.org/10.1038/s41598-021-89477-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110557PMC
May 2021

The Incidence of Epstein-Barr Virus-Positive Diffuse Large B-Cell Lymphoma: A Systematic Review and Meta-Analysis.

Cancers (Basel) 2021 Apr 8;13(8). Epub 2021 Apr 8.

Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA.

The worldwide prevalence of Epstein-Barr virus-positive (EBV+) diffuse large B-cell lymphoma (DLBCL) is undetermined. There is no clearly defined cut-off for EBV-encoded RNA (EBER) positivity in tumor cells by in-situ hybridization. The purpose of this study was to establish the proportions of EBV+ DLBCL patients and influence of the different cut-offs for EBER positivity, geographical location, and age on the prevalence of EBV+ DLBCL. PubMed and EMBASE were searched for studies published up to May 28, 2020 that reported proportions of EBER positivity in immunocompetent and de novo DLBCL patients. The pooled proportions were computed by an inverse variance method for calculating the weights and the DerSimonian-Laird method. Multiple subgroup analyses were conducted to explore any heterogeneity. Thirty-one studies (8249 patients) were included. The pooled proportion of EBV+ DLBCL was 7.9% (95% CI, 6.2-10.0%) with significant heterogeneity among studies ( < 0.001). The prevalence of EBV+ DLBCL was significantly higher in Asia and South America compared with Western countries ( < 0.01). The cut-offs for EBER positivity (10%, 20%, 50%) and patients' age (≥50 years vs. <50 years) did not significantly affect the prevalence ( ≥ 0.10). EBV+ DLBCL is rare with a pooled proportion of 7.9% in patients with DLBCL and the geographic heterogeneity was confirmed.
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http://dx.doi.org/10.3390/cancers13081785DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068359PMC
April 2021

Magnetic Resonance Imaging Parameters for Noninvasive Prediction of Epidermal Growth Factor Receptor Amplification in Isocitrate Dehydrogenase-Wild-Type Lower-Grade Gliomas: A Multicenter Study.

Neurosurgery 2021 Jul;89(2):257-265

Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.

Background: The epidermal growth factor receptor (EGFR) amplification status of isocitrate dehydrogenase-wild-type (IDHwt) lower-grade gliomas (LGGs; grade II/III) is one of the key markers for diagnosing molecular glioblastoma. However, the association between EGFR status and imaging parameters is unclear.

Objective: To identify noninvasive imaging parameters from diffusion-weighted and dynamic susceptibility contrast imaging for predicting the EGFR amplification status of IDHwt LGGs.

Methods: A total of 86 IDHwt LGG patients with known EGFR amplification status (62 nonamplified and 24 amplified) from 3 tertiary institutions were included. Qualitative and quantitative imaging features, including histogram parameters from apparent diffusion coefficient (ADC), normalized cerebral blood volume (nCBV), and normalized cerebral blood flow (nCBF), were assessed. Univariable and multivariable logistic regression models were constructed.

Results: On multivariable analysis, multifocal/multicentric distribution (odds ratio [OR] = 11.77, P = .006), mean ADC (OR = 0.01, P = .044), 5th percentile of ADC (OR = 0.01, P = .046), and 95th percentile of nCBF (OR = 1.24, P = .031) were independent predictors of EGFR amplification. The diagnostic performance of the model with qualitative imaging parameters increased significantly when quantitative imaging parameters were added, with areas under the curves of 0.81 and 0.93, respectively (P = .004).

Conclusion: The presence of multifocal/multicentric distribution patterns, lower mean ADC, lower 5th percentile of ADC, and higher 95th percentile of nCBF may be useful imaging biomarkers for EGFR amplification in IDHwt LGGs. Moreover, quantitative imaging biomarkers may add value to qualitative imaging parameters.
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http://dx.doi.org/10.1093/neuros/nyab136DOI Listing
July 2021

The Korean Society for Neuro-Oncology (KSNO) Guideline for Antiepileptic Drug Usage of Brain Tumor: Version 2021.1.

Brain Tumor Res Treat 2021 Apr;9(1):9-15

Department of Cancer Control, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea.

Background: To date, there has been no practical guidelines for the prescription of antiepileptic drugs (AEDs) in brain tumor patients in Korea. Thus, the Korean Society for Neuro-Oncology (KSNO), a multidisciplinary academic society, had begun preparing guidelines for AED usage in brain tumors since 2019.

Methods: The Working Group was composed of 27 multidisciplinary medical experts in Korea. References were identified through searches of PubMed, MEDLINE, EMBASE, and Cochrane CENTRAL using specific and sensitive keywords as well as combinations of the keywords.

Results: The core contents are as follows. Prophylactic AED administration is not recommended in newly diagnosed brain tumor patients without previous seizure history. When AEDs are administered during peri/postoperative period, it may be tapered off according to the following recommendations. In seizure-naïve patients with no postoperative seizure, it is recommended to stop or reduce AED 1 week after surgery. In seizure-naïve patients with one early postoperative seizure (<1 week after surgery), it is advisable to maintain AED for at least 3 months before tapering. In seizure-naïve patients with ≥2 postoperative seizures or in patients with preoperative seizure history, it is recommended to maintain AEDs for more than 1 year. The possibility of drug interactions should be considered when selecting AEDs in brain tumor patients. Driving can be allowed in brain tumor patients when proven to be seizure-free for more than 1 year.

Conclusion: The KSNO suggests prescribing AEDs in patients with brain tumor based on the current guideline. This guideline will contribute to spreading evidence-based prescription of AEDs in brain tumor patients in Korea.
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http://dx.doi.org/10.14791/btrt.2021.9.e7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082286PMC
April 2021

The Korean Society for Neuro-Oncology (KSNO) Guideline for Adult Diffuse Midline Glioma: Version 2021.1.

Brain Tumor Res Treat 2021 Apr;9(1):1-8

Department of Cancer Control, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea.

Background: There have been no guidelines for the management of adult patients with diffuse midline glioma (DMG), H3K27M-mutant in Korea since the 2016 revised WHO classification newly defined this disease entity. Thus, the Korean Society for Neuro-Oncology (KSNO), a multidisciplinary academic society, had begun preparing guidelines for DMG since 2019.

Methods: The Working Group was composed of 27 multidisciplinary medical experts in Korea. References were identified through searches of PubMed, MEDLINE, EMBASE, and Cochrane CENTRAL using specific and sensitive keywords as well as combinations of keywords. As 'diffuse midline glioma' was recently defined, and there was no international guideline, trials and guidelines of 'diffuse intrinsic pontine glioma' or 'brain stem glioma' were thoroughly reviewed first.

Results: The core contents are as follows. The DMG can be diagnosed when all of the following three criteria are satisfied: the presence of the H3K27M mutation, midline location, and infiltrating feature. Without identification of H3K27M mutation by diagnostic biopsy, DMG cannot be diagnosed. For the primary treatment, maximal safe resection should be considered for tumors when feasible. Radiotherapy is the primary option for tumors in case the total resection is not possible. A total dose of 54 Gy to 60 Gy with conventional fractionation prescribed at 1-2 cm plus gross tumor volume is recommended. Although no chemotherapy has proven to be effective in DMG, concurrent chemoradiotherapy (± maintenance chemotherapy) with temozolomide following WHO grade IV glioblastoma's protocol is recommended.

Conclusion: The detection of H3K27M mutation is the most important diagnostic criteria for DMG. Combination of surgery (if amenable to surgery), radiotherapy, and chemotherapy based on comprehensive multidisciplinary discussion can be considered as the treatment options for DMG.
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http://dx.doi.org/10.14791/btrt.2021.9.e8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082289PMC
April 2021

Low conductivity on electrical properties tomography demonstrates unique tumor habitats indicating progression in glioblastoma.

Eur Radiol 2021 Apr 20. Epub 2021 Apr 20.

Department of Tomographic Imaging, Philips Research Laboratories, Hamburg, Germany.

Objectives: Tissue conductivity measurements made with electrical properties tomography (EPT) can be used to define temporal changes in tissue habitats on longitudinal multiparametric MRI. We aimed to demonstrate the added insights for identifying tumor habitats obtained by including EPT with diffusion- and perfusion-weighted MRI, and to evaluate the use of these tumor habitats for determining tumor treatment response in post-treatment glioblastoma.

Methods: Tumor habitats were developed from EPT, diffusion-weighted, and perfusion-weighted MRI in 60 patients with glioblastoma who underwent concurrent chemoradiotherapy. Voxels from EPT, apparent diffusion coefficient (ADC), and cerebral blood volume (CBV) maps were clustered into habitats, and each habitat was serially examined to assess its temporal change. The usefulness of temporal changes in tumor habitats for diagnosing tumor progression and treatment-related change was investigated using logistic regression. The performance of significant predictors was measured using the area under the curve (AUC) from receiver-operating-characteristics analysis with 1000-fold bootstrapping.

Results: Five tumor habitats were identified, and of these, the hypervascular cellular habitat (odds ratio [OR] 5.45; 95% CI, 1.75-31.42; p = .02), hypovascular low conductivity habitat (OR 2.00; 95% CI, 1.45-3.05; p < .001), and hypovascular intermediate habitat (OR 1.57; 95% CI, 1.18-2.30; p = .006) were predictive of tumor progression. Low EPT and low CBV reflected a unique hypovascular low conductivity habitat that showed the highest diagnostic performance (AUC 0.86; 95% CI, 0.76-0.96). The combined habitats showed high performance (AUC 0.90; 95% CI, 0.82-0.98) in the differentiation of tumor progression from treatment-related change.

Conclusion: EPT reveals low conductivity habitats that can improve the diagnosis of tumor progression in post-treatment glioblastoma.

Key Points: • Electrical properties tomography (EPT) demonstrated lower conductivity in tumor progression than in treatment-related change. • EPT allowed identification of a unique hypovascular low conductivity habitat when combined with cerebral blood volume mapping. • Tumor habitats with a hypovascular low conductivity habitat, hypervascular cellular habitat, and hypovascular intermediate habitat yielded high diagnostic performance for diagnosing tumor progression.
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http://dx.doi.org/10.1007/s00330-021-07976-wDOI Listing
April 2021

Comparative Value of 2-Hydroxyglutarate-to-Lipid and Lactate Ratio versus 2-Hydroxyglutarate Concentration on MR Spectroscopic Images for Predicting Isocitrate Dehydrogenase Mutation Status in Gliomas.

Radiol Imaging Cancer 2020 07 31;2(4):e190083. Epub 2020 Jul 31.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 33, Seoul 05505, Republic of Korea (C.H.S., H.S.K., J.E.P., S.C.J., C.G.C., H.B.L., S.J.K.), and Bioimaging Center, Biomedical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea (D.C.W.).

Purpose: To compare the ability of 2-hydroxyglutarate (2HG)-to-lipid and lactate (2HG/[lipid + lactate]) ratio with the ability of 2HG concentration alone to predict the isocitrate dehydrogenase mutation status in patients with glioma.

Materials And Methods: In this retrospective study, consecutive patients with histopathologically proven glioma were enrolled between July 2016 and February 2019. A total of 79 patients were enrolled (mean age, 44 years; 49 men). The 2HG concentration and other MR spectroscopic parameters were measured by single-voxel point-resolved spectroscopy before surgery. The diagnostic performance of the 2HG concentration and 2HG/(lipid + lactate) ratio were calculated. Internal validation was assessed by the bootstrap approach with 1000 bootstrap resamples. Differences in the predictive accuracy of 2HG/(lipid + lactate) ratio and 2HG concentration were determined by calculating the integrated discrimination improvement. The diagnostic accuracy (sensitivity, specificity, and area under the receiver operating characteristic curve [AUC]) of these measures was also compared separately in patients with glioblastomas and patients with lower-grade gliomas.

Results: Of the 79 enrolled patients, 28 had mutations and 51 had wild-type . The sensitivity, specificity, and AUC of 2HG concentration for predicting -mutant gliomas were 89% (25 of 28), 67% (34 of 51), and 0.80 (95% confidence interval [CI]: 0.70, 0.88; C statistic, 0.80), respectively. The sensitivity, specificity, and AUC of the 2HG/(lipid + lactate) ratio for predicting -mutant gliomas were 79% (22 of 28), 92% (47 of 51), and 0.90 (95% CI: 0.81, 0.96; C statistics, 0.90), respectively. The optimal cutoff value for the 2HG/(lipid + lactate) ratio was 0.63. The 2HG/(lipid + lactate) ratio was significantly better for predicting mutation status than the 2HG concentration alone ( < .01). In glioblastoma, the 2HG/(lipid + lactate) ratio was also better for predicting mutations than the 2HG concentration alone, with borderline significance ( = .052). In lower-grade glioma, the 2HG/(lipid + lactate) ratio and the 2HG concentration showed comparable diagnostic performance ( = .72).

Conclusion: The 2HG/(lipid + lactate) ratio is more accurate for predicting mutation status in patients with glioma than the 2HG concentration alone. Brain/Brain Stem, CNS, MR-Imaging, MR-Spectroscopy, Neoplasms-Primary, Neuro-Oncology© RSNA, 2020.
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http://dx.doi.org/10.1148/rycan.2020190083DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7983780PMC
July 2020

Accelerated multicontrast reconstruction for synthetic MRI using joint parallel imaging and variable splitting networks.

Med Phys 2021 Jun 12;48(6):2939-2950. Epub 2021 Apr 12.

Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.

Purpose: Synthetic magnetic resonance imaging (MRI) requires the acquisition of multicontrast images to estimate quantitative parameter maps, such as T , T , and proton density (PD). The study aims to develop a multicontrast reconstruction method based on joint parallel imaging (JPI) and joint deep learning (JDL) to enable further acceleration of synthetic MRI.

Methods: The JPI and JDL methods are extended and combined to improve reconstruction for better-quality, synthesized images. JPI is performed as a first step to estimate the missing k-space lines, and JDL is then performed to correct and refine the previous estimate with a trained neural network. For the JDL architecture, the original variable splitting network (VS-Net) is modified and extended to form a joint variable splitting network (JVS-Net) to apply to multicontrast reconstructions. The proposed method is designed and tested for multidynamic multiecho (MDME) images with Cartesian uniform under-sampling using acceleration factors between 4 and 8.

Results: It is demonstrated that the normalized root-mean-square error (nRMSE) is lower and the structural similarity index measure (SSIM) values are higher with the proposed method compared to both the JPI and JDL methods individually. The method also demonstrates the potential to produce a set of synthesized contrast-weighted images that closely resemble those from the fully sampled acquisition without erroneous artifacts.

Conclusion: Combining JPI and JDL enables the reconstruction of highly accelerated synthetic MRIs.
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http://dx.doi.org/10.1002/mp.14848DOI Listing
June 2021

Spatiotemporal habitats from multiparametric physiologic MRI distinguish tumor progression from treatment-related change in post-treatment glioblastoma.

Eur Radiol 2021 Aug 10;31(8):6374-6383. Epub 2021 Feb 10.

Department of Neurosurgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.

Objectives: We aimed to develop multiparametric physiologic MRI-based spatial habitats and to evaluate whether temporal changes in these habitats help to distinguish tumor progression from treatment-related change in post-treatment glioblastoma.

Methods: This retrospective, single-institution study included patients with glioblastoma treated by concurrent chemoradiotherapy who had newly developed or enlarging, measurable contrast-enhancing mass. Contrast-enhancing mass was divided into three spatial habitats by K-means clustering of voxel-wise ADC and CBV values. Temporal changes of these habitats between two consecutive examinations prior to the diagnosis of tumor progression or treatment-related change were assessed. Predictors were selected using logistic regression and the performance was measured with an area under the receiver operating characteristics curve (AUC). Spatiotemporal habitats were further analyzed for correlation with the site of tumor progression.

Results: There were 75 patients (mean, 58 years; range, 26-81 years; 43 men) with 48 cases of tumor progression and 39 cases of treatment-related change including 12 patient overlaps at different time points. Three spatial habitats of hypervascular cellular, hypovascular cellular, and nonviable tissue were identified. Increase in the hypervascular cellular (OR 4.55, p = .002) and hypovascular cellular habitat (OR 1.22, p < .001) was predictive of tumor progression. Combination of spatiotemporal habitats yielded a high diagnostic performance with an AUC of 0.89 (95% CI, 0.87-0.92). An increase in hypovascular cellular habitat predicted the site of tumor progression in 84% [21/25] of cases with tumor progression.

Conclusions: Temporal changes in spatial habitats derived from multiparametric physiologic MRI provided diagnostic value in distinguishing tumor progression from treatment-related change and predicted site of tumor progression in post-treatment glioblastoma.

Key Points: • In post-treatment glioblastoma, three spatial habitats of hypervascular cellular, hypovascular cellular, and nonviable tissue were identified, and an increase in the hypervascular cellular (OR 4.55, p = .002) and hypovascular cellular habitat (OR 1.22, p < .001) was predictive of tumor progression. • Combination of spatiotemporal habitats yielded a high diagnostic performance with an AUC of 0.89 (95% CI, 0.87-0.92). • An increase in hypovascular cellular habitat predicted the site of tumor progression in 84% (21/25) of cases with tumor progression.
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http://dx.doi.org/10.1007/s00330-021-07718-yDOI Listing
August 2021

Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation.

Sci Rep 2021 Feb 3;11(1):2913. Epub 2021 Feb 3.

Department of Radiology and Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, South Korea.

The purpose of this study was to establish a high-performing radiomics strategy with machine learning from conventional and diffusion MRI to differentiate recurrent glioblastoma (GBM) from radiation necrosis (RN) after concurrent chemoradiotherapy (CCRT) or radiotherapy. Eighty-six patients with GBM were enrolled in the training set after they underwent CCRT or radiotherapy and presented with new or enlarging contrast enhancement within the radiation field on follow-up MRI. A diagnosis was established either pathologically or clinicoradiologically (63 recurrent GBM and 23 RN). Another 41 patients (23 recurrent GBM and 18 RN) from a different institution were enrolled in the test set. Conventional MRI sequences (T2-weighted and postcontrast T1-weighted images) and ADC were analyzed to extract 263 radiomic features. After feature selection, various machine learning models with oversampling methods were trained with combinations of MRI sequences and subsequently validated in the test set. In the independent test set, the model using ADC sequence showed the best diagnostic performance, with an AUC, accuracy, sensitivity, specificity of 0.80, 78%, 66.7%, and 87%, respectively. In conclusion, the radiomics models models using other MRI sequences showed AUCs ranging from 0.65 to 0.66 in the test set. The diffusion radiomics may be helpful in differentiating recurrent GBM from RN..
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http://dx.doi.org/10.1038/s41598-021-82467-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7858615PMC
February 2021

The T2-FLAIR mismatch sign as a predictor of IDH-mutant, 1p/19q-noncodeleted lower-grade gliomas: a systematic review and diagnostic meta-analysis.

Eur Radiol 2021 Jul 6;31(7):5289-5299. Epub 2021 Jan 6.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 33, Seoul, 05505, Republic of Korea.

Objectives: To evaluate the diagnostic performance of the T2-FLAIR mismatch sign for prediction of isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted lower-grade gliomas (LGGs) and review studies with false positive results.

Methods: The MEDLINE and EMBASE databases were searched up to March 13, 2020, to identify articles reporting the diagnostic performance of the T2-FLAIR mismatch sign for prediction of IDH-mutant, 1p/19q-noncodeleted LGGs (IDHmut-Noncodel) using the search terms (T2 FLAIR mismatch). Pooled sensitivity, specificity, and correlation coefficient for interobserver agreement were calculated.

Results: Twelve studies including a total of 1053 patients were included. The median age was 43 (median; range, 14-56). The pooled sensitivity and specificity were 42% (95% CI, 28-58%) and 100% (95% CI, 88-100%), respectively. According to the HSROC curve, the area under the curve was 0.77 (95% CI, 0.73-0.80). Considerable heterogeneity was possible among the studies in terms of both sensitivity and specificity. A threshold effect was suggested and was considered to explain most of the heterogeneity. Four studies reported false positive results for the T2-FLAIR mismatch sign, including dysembryoplastic neuroepithelial tumor, pediatric-type gliomas, and non-neoplastic lesions. The 2 original articles with false positive results showed the highest sensitivities among the 10 studies included in the quantitative analysis, supporting the probability of the threshold effect. The pooled correlation coefficient was 0.87 (95% CI, 0.73-0.94).

Conclusions: The T2-FLAIR mismatch sign had a high specificity and interobserver agreement for the prediction of IDHmut-Noncodel. However, the sign demonstrated low sensitivity, and a few studies with false positive cases were also reported.

Key Points: • The pooled sensitivity and specificity of the T2-FLAIR mismatch sign for prediction of IDH-mutant, 1p/19q-noncodeleted lower-grade gliomas were 42% and 100%, respectively. • Four studies reported false positive results. • The pooled correlation coefficient was 0.87, suggesting almost perfect interobserver agreement.
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http://dx.doi.org/10.1007/s00330-020-07467-4DOI Listing
July 2021

Immune Checkpoint Inhibitors with or without Radiotherapy in Non-Small Cell Lung Cancer Patients with Brain Metastases: A Systematic Review and Meta-Analysis.

Diagnostics (Basel) 2020 Dec 16;10(12). Epub 2020 Dec 16.

Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea.

This study aimed to evaluate the radiologic response and adverse event rates of immune checkpoint inhibitor (ICI) therapy with or without radiotherapy for the treatment of non-small cell lung cancer (NSCLC) brain metastases. A systematic literature search was performed up to January 3, 2020. Studies evaluating the intracranial objective response rates (ORR) and/or disease control rates (DCR) of ICI with or without radiotherapy for treating NSCLC brain metastases were included. Consequently, twelve studies satisfied inclusion criteria. ICI combined with radiotherapy (pooled ORR, 95%; DCR, 97%) showed better local efficacy compared to ICI monotherapy (pooled ORR, 24%; DCR, 44%; < 0.01 for both ORR and DCR). Grade 3 or 4 central nervous system (CNS)-related adverse event rates were not different (5% vs. 4%; = 0.93). In conclusion, ICI combined with radiotherapy showed better intracranial efficacy than ICI monotherapy for treating NSCLC brain metastases. CNS-related grade 3 or 4 adverse event rate was not statistically different between the two groups. Several prospective trials are needed to compare the efficacy of ICI combined with radiotherapy and ICI monotherapy.
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http://dx.doi.org/10.3390/diagnostics10121098DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7767255PMC
December 2020

Pretreatment brain volumes can affect the effectiveness of deep brain stimulation in Parkinson's disease patients.

Sci Rep 2020 12 16;10(1):22065. Epub 2020 Dec 16.

Clinical Research Team, DEEPNOID Inc., Seoul, Republic of Korea.

We aimed to assess whether brain volumes may affect the results of deep brain stimulation (DBS) in patients with Parkinson's disease (PD). Eighty-one consecutive patients with PD (male:female 40:41), treated with DBS between June 2012 and December 2017, were enrolled. Total and regional brain volumes were measured using automated brain volumetry (NeuroQuant). The Unified Parkinson Disease Rating Scale motor score quotient was used to assess changes in clinical outcome and compare the preoperative regional brain volume in patients categorized into the higher motor improvement and lower motor improvement groups based on changes in the postoperative scores. The study groups showed significant volume differences in multiple brain areas. In the higher motor improvement group, the anterior cingulate and right thalamus showed high volumes after false discovery rate (FDR) correction. In the lower motor improvement group, the left caudate, paracentral, right primary sensory and left primary motor cortex showed high volume, but no area showed high volumes after FDR correction. Our data suggest that the effectiveness of DBS in patients with PD may be affected by decreased brain volume in different areas, including the cingulate gyrus and thalamus. Preoperative volumetry could help predict outcomes in patients with PD undergoing DBS.
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http://dx.doi.org/10.1038/s41598-020-79138-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744532PMC
December 2020

Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation.

Sci Rep 2020 12 8;10(1):21485. Epub 2020 Dec 8.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea.

Current image processing methods for dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) do not capture complex dynamic information of time-signal intensity curves. We investigated whether an autoencoder-based pattern analysis of DSC MRI captured representative temporal features that improves tissue characterization and tumor diagnosis in a multicenter setting. The autoencoder was applied to the time-signal intensity curves to obtain representative temporal patterns, which were subsequently learned by a convolutional neural network. This network was trained with 216 preoperative DSC MRI acquisitions and validated using external data (n = 43) collected with different DSC acquisition protocols. The autoencoder applied to time-signal intensity curves and clustering obtained nine representative clusters of temporal patterns, which accurately identified tumor and non-tumoral tissues. The dominant clusters of temporal patterns distinguished primary central nervous system lymphoma (PCNSL) from glioblastoma (AUC 0.89) and metastasis from glioblastoma (AUC 0.95). The autoencoder captured DSC time-signal intensity patterns that improved identification of tumoral tissues and differentiation of tumor type and was generalizable across centers.
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http://dx.doi.org/10.1038/s41598-020-78485-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7723041PMC
December 2020

Immune Checkpoint Inhibitor with or without Radiotherapy in Melanoma Patients with Brain Metastases: A Systematic Review and Meta-Analysis.

Korean J Radiol 2021 04 26;22(4):584-595. Epub 2020 Nov 26.

Department of Radiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.

Objective: Immune checkpoint inhibitor (ICI) therapy has shown activity against melanoma brain metastases. Recently, promising results have also been reported for ICI combination therapy and ICI combined with radiotherapy. We aimed to evaluate radiologic response and adverse event rates of these therapeutic options by a systematic review and meta-analysis.

Materials And Methods: A systematic literature search of Ovid-MEDLINE and EMBASE was performed up to October 12, 2019 and included studies evaluating the intracranial objective response rates (ORRs) and/or disease control rates (DCRs) of ICI with or without radiotherapy for treating melanoma brain metastases. We also evaluated safety-associated outcomes.

Results: Eleven studies with 14 cohorts (3 with ICI combination therapy; 5 with ICI combined with radiotherapy; 6 with ICI monotherapy) were included. ICI combination therapy {pooled ORR, 53% (95% confidence interval [CI], 44-61%); DCR, 57% (95% CI, 49-66%)} and ICI combined with radiotherapy (pooled ORR, 42% [95% CI, 31-54%]; DCR, 85% [95% CI, 63-95%]) showed higher local efficacy compared to ICI monotherapy (pooled ORR, 15% [95% CI, 11-20%]; DCR, 26% [95% CI, 21-32%]). The grade 3 or 4 adverse event rate was significantly higher with ICI combination therapy (60%; 95% CI, 52-67%) compared to ICI monotherapy (11%; 95% CI, 8-17%) and ICI combined with radiotherapy (4%; 95% CI, 1-19%). Grade 3 or 4 central nervous system (CNS)-related adverse event rates were not different (9% in ICI combination therapy; 8% in ICI combined with radiotherapy; 5% in ICI monotherapy).

Conclusion: ICI combination therapy or ICI combined with radiotherapy showed better local efficacy than ICI monotherapy for treating melanoma brain metastasis. The grade 3 or 4 adverse event rate was highest with ICI combination therapy, and the CNS-related grade 3 or 4 event rate was similar. Prospective trials will be necessary to compare the efficacy of ICI combination therapy and ICI combined with radiotherapy.
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http://dx.doi.org/10.3348/kjr.2020.0728DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005357PMC
April 2021

Immune checkpoint inhibitor therapy may increase the incidence of treatment-related necrosis after stereotactic radiosurgery for brain metastases: a systematic review and meta-analysis.

Eur Radiol 2021 Jun 25;31(6):4114-4129. Epub 2020 Nov 25.

Division of Neuroradiology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA.

Objectives: To compare the incidence of treatment-related necrosis between combination SRS+ICI therapy and SRS therapy alone in patients with brain metastases from melanoma and non-small cell lung cancer (NSCLC).

Methods: A systematic literature search of Ovid-MEDLINE and EMBASE was performed up to August 10, 2020. The difference in the pooled incidence of treatment-related necrosis after SRS+ICI or SRS alone was evaluated. The cumulative incidence of treatment-related necrosis at the specific time point after the treatment was calculated and plotted. Subgroup and meta-regression analyses were additionally performed.

Results: Sixteen studies (14 on melanoma, 2 on NSCLC) were included. In NSCLC brain metastasis, the reported incidences of treatment-related necrosis in SRS+ICI and SRS alone ranged 2.9-3.4% and 0-2.9%, respectively. Meta-analysis was conducted including 14 studies on melanoma brain metastasis. The incidence of treatment-related necrosis was higher in SRS+ICI than SRS alone (16.0% vs. 6.5%; p = 0.065; OR, 2.35). The incidence showed rapid increase until 12 months after the SRS when combined with ICI therapy (14%; 95% CI, 8-22%) and its pace of increase slowed thereafter. Histopathologic diagnosis as the reference standard for treatment-related necrosis and inclusion of only symptomatic cases were the source of heterogeneity in SRS+ICI.

Conclusions: Treatment-related necrosis tended to occur 2.4 times more frequently in the setting of combination SRS+ICI therapy compared with SRS alone in melanoma brain metastasis showing high cumulative incidence within the first year. Treatment-related necrosis should be considered when SRS+ICI combination therapy is used for melanoma brain metastasis, especially in the first year.

Key Points: • Treatment-related necrosis occurred 2.4 times more frequently in the setting of combination SRS+ICI therapy compared with SRS alone in melanoma brain metastasis. • Treatment-related necrosis more frequently occurred in brain metastases from melanoma than NSCLC. • Reference standard for treatment-related necrosis and inclusion of only symptomatic treatment-related necrosis were a significant source of heterogeneity, indicating varying definitions of treatment-related necrosis in the literature need to be unified.
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http://dx.doi.org/10.1007/s00330-020-07514-0DOI Listing
June 2021

Retrospective review of 108 breast reconstructions using the round block technique after breast-conserving surgery: Indications, complications, and outcomes.

Arch Plast Surg 2020 Nov 15;47(6):574-582. Epub 2020 Nov 15.

Department of Plastic and Reconstructive Surgery, Kosin University Gospel Hospital, Busan, Korea.

Background: Several oncoplastic approaches have been implemented in recent years to enhance cosmetic results and to reduce complications. The round block technique is a volume displacement technique for breast reconstruction after breast-conserving surgery (BCS). However, its indications are currently limited according to tumor location, and its cosmetic results and complications have not been clearly established. We hypothesized that the round block technique could produce favorable cosmetic results without major complications regardless of tumor location or nipple-tumor distance, below a certain resected tumor volume and tumor-breast volume ratio.

Methods: All breast reconstructions using the round block technique after BCS were included in this analysis. Patients' data were reviewed retrospectively to investigate complications during follow-up, and clinical photos were used to evaluate cosmetic results. The relationships of tumor location, nipple-tumor distance, tumor volume, and the tumor-breast volume ratio with cosmetic results were investigated.

Results: In total, 108 breasts were reconstructed. The mean resected tumor volume was 30.2±15.0 mL. The cosmetic score was 4.5±0.6 out of 5. Tumor location, nipple-tumor distance, tumor volume, tumor-breast volume ratio, radiotherapy, and chemotherapy had no significant effects on cosmetic results or complications. There were no major complications requiring reoperation.

Conclusions: Breast reconstruction using the round block technique after BCS can lead to good cosmetic results without major complications regardless of the tumor location, nipple-tumor distance, radiotherapy, or chemotherapy. Below the maximum tumor volume (79.2 mL) and the maximum tumor-breast volume ratio (14%), favorable results were consistently obtained.
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http://dx.doi.org/10.5999/aps.2020.00325DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7700858PMC
November 2020

Survival outcome and prognostic factors in anaplastic oligodendroglioma: a single-institution study of 95 cases.

Sci Rep 2020 11 19;10(1):20162. Epub 2020 Nov 19.

Department of Neurological Surgery, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea.

The aim of this study was to evaluate prognostic factors including surgical, radiographic, and histopathologic analyses in anaplastic oligodendroglioma (AO) patients. We reviewed the electronic records of 95 patients who underwent surgery and were diagnosed with AO for 20 years. The primary endpoints were progression-free survival (PFS) and overall survival (OS). Univariate and multivariable analyses included clinical, histopathological, and radiographic prognostic factors. Subgroup analysis was performed in isocitrate dehydrogenase (IDH1/2)-mutant and 1p/19q-codeleted patients. The median PFS and OS were 24.7 months and 50.8 months, respectively. The 1-, 3-, 5-, and 10-year PFS were 75.8%, 42.9%, 32.4%, and 16.4%, respectively. Furthermore, the 1-, 3-, 5-, and 10-year OS were 98.9%, 76.9%, 42.9%, and 29.7%, respectively. The median PFS and OS of the IDH1/2-mutant and 1p/19q-codeleted patients were 54.2 and 57.8 months, respectively. In univariate analyses, young age, frontal lobe, weak enhancement, gross total resection (GTR), low Ki-67 index, 1p/19q codeletion, and IDH1/2 mutations were associated with a favorable outcome. In multivariable analyses, IDH1/2 mutation was related to better PFS and OS. In subgroup analysis, GTR was associated with favorable outcomes.
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http://dx.doi.org/10.1038/s41598-020-77228-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677372PMC
November 2020

Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting.

Radiology 2021 01 3;298(1):114-122. Epub 2020 Nov 3.

From the Department of Radiology and Research Institute of Radiology (M.K., H.S.K., H.J.K., J.E.P., S.J.K.), Department of Clinical Epidemiology and Biostatistics (S.Y.P.), and Department of Neurosurgery (Y.H.K.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-Gu, Seoul 05505, South Korea; GE Healthcare Korea, Seoul, Korea (J.L.); GE Healthcare Canada, Calgary, Canada (M.R.L.); and Department of Radiology, University of Calgary, Calgary, Canada (M.R.L.).

Background Achieving high-spatial-resolution pituitary MRI is challenging because of the trade-off between image noise and spatial resolution. Deep learning-based MRI reconstruction enables image denoising with sharp edges and reduced artifacts, which improves the image quality of thin-slice MRI. Purpose To assess the diagnostic performance of 1-mm slice thickness MRI with deep learning-based reconstruction (DLR) (hereafter, 1-mm MRI+DLR) compared with 3-mm slice thickness MRI (hereafter, 3-mm MRI) for identifying residual tumor and cavernous sinus invasion in the evaluation of postoperative pituitary adenoma. Materials and Methods This single-institution retrospective study included 65 patients (mean age ± standard deviation, 54 years ± 10; 26 women) who underwent a combined imaging protocol including 3-mm MRI and 1-mm MRI+DLR for postoperative evaluation of pituitary adenoma between August and October 2019. Reference standards for correct diagnosis were established by using all available imaging resources, clinical histories, laboratory findings, surgical records, and pathology reports. The diagnostic performances of 3-mm MRI, 1-mm slice thickness MRI without DLR (hereafter, 1-mm MRI), and 1-mm MRI+DLR for identifying residual tumor and cavernous sinus invasion were evaluated by two readers and compared between the protocols. Results The performance of 1-mm MRI+DLR in the identification of residual tumor was comparable to that of 3-mm MRI (area under the receiver operating characteristic curve [AUC], 0.89-0.92 vs 0.85-0.89, respectively; ≥ .09). In the identification of cavernous sinus invasion, the diagnostic performance of 1-mm MRI+DLR was higher than that of 3-mm MRI (AUC, 0.95-0.98 vs 0.83-0.87, respectively; ≤ .02). Conventional 1-mm MRI (AUC, 0.82-0.83) showed comparable diagnostic performance to 3-mm MRI (AUC, 0.83-0.87) ( ≥ .38). With 1-mm MRI+DLR, residual tumor was diagnosed in 20 patients and cavernous sinus invasion was diagnosed in 14 patients, in whom these diagnoses were not made with 3-mm MRI. Conclusion In the postoperative evaluation of pituitary adenoma, 1-mm slice thickness MRI with deep learning-based reconstruction showed higher diagnostic performance than 3-mm slice thickness MRI in the identification of cavernous sinus invasion and comparable diagnostic performance to 3-mm slice thickness MRI in the identification of residual tumor. © RSNA, 2020
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http://dx.doi.org/10.1148/radiol.2020200723DOI Listing
January 2021

Diffusion and perfusion MRI radiomics obtained from deep learning segmentation provides reproducible and comparable diagnostic model to human in post-treatment glioblastoma.

Eur Radiol 2021 May 31;31(5):3127-3137. Epub 2020 Oct 31.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, South Korea.

Objectives: Deep learning-based automatic segmentation (DLAS) helps the reproducibility of radiomics features, but its effect on radiomics modeling is unknown. We therefore evaluated whether DLAS can robustly extract anatomical and physiological MRI features, thereby assisting in the accurate assessment of treatment response in glioblastoma patients.

Methods: A DLAS model was trained on 238 glioblastomas and validated on an independent set of 98 pre- and 86 post-treatment glioblastomas from two tertiary hospitals. A total of 1618 radiomics features from contrast-enhanced T1-weighted images (CE-T1w) and histogram features from apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) mapping were extracted. The diagnostic performance of radiomics features and ADC and CBV parameters for identifying treatment response was tested using area under the curve (AUC) from receiver operating characteristics analysis. Feature reproducibility was tested using a 0.80 cutoff for concordance correlation coefficients.

Results: Reproducibility was excellent for ADC and CBV features (ICC, 0.82-0.99) and first-order features (pre- and post-treatment, 100% and 94.1% remained), but lower for texture (79.0% and 69.1% remained) and wavelet-transformed (81.8% and 74.9% remained) features of CE-T1w. DLAS-based radiomics showed similar performance to human-performed segmentations in internal validation (AUC, 0.81 [95% CI, 0.64-0.99] vs. AUC, 0.81 [0.60-1.00], p = 0.80), but slightly lower performance in external validation (AUC, 0.78 [0.61-0.95] vs. AUC, 0.65 [0.46-0.84], p = 0.23).

Conclusion: DLAS-based feature extraction showed high reproducibility for first-order features from anatomical and physiological MRI, and comparable diagnostic performance to human manual segmentations in the identification of pseudoprogression, supporting the utility of DLAS in quantitative MRI analysis.

Key Points: • Deep learning-based automatic segmentation (DLAS) enables fast and robust feature extraction from diffusion- and perfusion-weighted MRI. • DLAS showed high reproducibility in first-order feature extraction from anatomical, diffusion, and perfusion MRI across two centers. • DLAS-based radiomics features showed comparable diagnostic accuracy to manual segmentations in post-treatment glioblastoma.
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http://dx.doi.org/10.1007/s00330-020-07414-3DOI Listing
May 2021

Spatiotemporal Heterogeneity in Multiparametric Physiologic MRI Is Associated with Patient Outcomes in IDH-Wildtype Glioblastoma.

Clin Cancer Res 2021 Jan 7;27(1):237-245. Epub 2020 Oct 7.

Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.

Purpose: Heterogeneity in glioblastomas is associated with poorer outcomes, and physiologic heterogeneity can be quantified with noninvasive imaging. We developed spatial habitats based on multiparametric physiologic MRI and evaluated associations between temporal changes in these habitats and progression-free survival (PFS) after concurrent chemoradiotherapy (CCRT) in patients with glioblastoma.

Experimental Design: Ninety-seven patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma were enrolled and two serial MRI examinations after CCRT were analyzed. Cerebral blood volumes and apparent diffusion coefficients were grouped using k-means clustering into three spatial habitats. Associations between temporal changes in spatial habitats and PFS were investigated using Cox proportional hazard modeling. The performance of significant predictors for PFS and overall survival (OS) was measured using a discrete increase of habitat (habitat risk score) in a temporal validation set from a prospective registry ( = 53, ClinicalTrials.gov NCT02619890). The site of progression was matched with the spatiotemporal habitats.

Results: Three spatial habitats of hypervascular cellular, hypovascular cellular, and nonviable tissue were identified. A short-term increase in the hypervascular cellular habitat (HR, 40.0; = 0.001) and hypovascular cellular habitat was significantly associated with shorter PFS (HR, 3.78; < 0.001) after CCRT. Combined with clinical predictors, the habitat risk score showed a C-index of 0.79 for PFS and 0.74 for OS and stratified patients with short, intermediate, and long PFS ( = 0.016). An increase in the hypovascular cellular habitat predicted tumor progression sites.

Conclusions: Hypovascular cellular habitats derived from multiparametric physiologic MRIs may be useful predictors of clinical outcomes in patients with posttreatment glioblastoma.
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http://dx.doi.org/10.1158/1078-0432.CCR-20-2156DOI Listing
January 2021

Diagnostic Yield of Staging Brain MRI in Patients with Newly Diagnosed Non-Small Cell Lung Cancer.

Radiology 2020 11 25;297(2):419-427. Epub 2020 Aug 25.

From the Department of Radiology and Research Institute of Radiology (M.K., C.H.S., S.M.L., H.S.K.) and Department of Pulmonology and Critical Care Medicine (H.C.K.), Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro, Seoul 05505, Republic of Korea; Department of Radiation Oncology (A.A.A.) and Division of Neuroradiology (J.P.G., R.Y.H.), Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Mass; Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC (T.K.Y.); and Department of Diagnostic Imaging, Rhode Island Hospital and Warren Alpert Medical School of Brown University, Providence, RI (H.X.B.).

Background Existing guidelines are inconsistent regarding the indications for staging brain MRI in patients with newly diagnosed, early-stage non-small cell lung cancer (NSCLC). Purpose To evaluate the diagnostic yield of staging brain MRI in the initial evaluation of lung cancer. Materials and Methods This retrospective, observational, single-institution study included patients with newly diagnosed NSCLC who underwent staging chest CT and staging brain MRI from November 2017 to October 2018. Diagnostic yield was defined as the proportion of patients with brain metastases among all patients. Yield was stratified into clinical stage groups per the eighth edition of the American Joint Committee on Cancer staging guidelines, based on staging chest CT and in adenocarcinoma with epidermal growth factor receptor gene mutation and anaplastic lymphoma kinase gene rearrangement. Subgroup analyses were performed on the basis of cell types and molecular markers. The χ test was performed to compare the diagnostic yields, and Bonferroni correction was used to account for multiple testing between stage groups. Results A total of 1712 patients (mean age, 64 years ± 10 [standard deviation]; 1035 men) were included. The diagnostic yield of staging brain MRI in newly diagnosed NSCLC was 11.9% (203 of 1712; 95% confidence interval [CI]: 10.4%, 13.5%). In clinical stage IA, IB, and II disease, the diagnostic yields were 0.3% (two of 615; 95% CI: 0.0%, 1.2%), 3.8% (seven of 186; 95% CI: 1.5%, 7.6%), and 4.7% (eight of 171; 95% CI: 2.0%, 9.0%), respectively. The diagnostic yield was higher in patients with adenocarcinoma (13.6%; 176 of 1297; 95% CI: 11.8%, 15.6%) than squamous cell carcinoma (5.9%; 21 of 354; 95% CI: 3.7%, 8.9%) and in patients with mutation-positive adenocarcinoma (17.5%; 85 of 487; 95% CI: 14.2%, 21.1%) than with mutation-negative adenocarcinoma (10.6%; 68 of 639; 95% CI: 8.4%, 13.3%) ( < .001 for both). Conclusion The diagnostic yield of staging brain MRI in clinical stage IA non-small cell lung cancer was low, but staging brain MRI had a higher diagnostic yield in clinical stage IB and epidermal growth factor receptor mutation-positive adenocarcinoma. © RSNA, 2020
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http://dx.doi.org/10.1148/radiol.2020201194DOI Listing
November 2020

Diagnostic Yield of Body CT and Whole-Body FDG PET/CT for Initial Systemic Staging in Patients With Suspected Primary CNS Lymphoma: A Systematic Review and Meta-Analysis.

AJR Am J Roentgenol 2021 05 19;216(5):1172-1182. Epub 2020 Aug 19.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 33, Seoul 05505, Republic of Korea.

Several guidelines recommend body imaging for the initial work-up of patients with suspected primary CNS lymphoma, to exclude subclinical systemic involvement. However, to our knowledge, the diagnostic yield of body CT (contrast-enhanced CT of the chest, abdomen, and pelvis) and whole-body FDG PET/CT for the evaluation of subclinical systemic lymphoma has not yet been systematically evaluated. The purpose of this study was to investigate and compare the diagnostic yield of body CT and whole-body FDG PET/CT in detecting subclinical systemic lymphoma in patients with suspected primary CNS lymphoma. A systematic search of the MEDLINE and EMBASE databases through July 5, 2020, was conducted to identify studies evaluating the diagnostic yield of body CT or whole-body FDG PET/CT in detecting subclinical systemic lymphoma in patients with suspected primary CNS lymphoma. Pooled estimates of the diagnostic yield of both imaging modalities were calculated using the DerSimonian and Laird random-effects model. The false referral rate and the rate of incidental secondary malignancy were also pooled. Nine original articles on studies evaluating a total of 1040 patients were included. In detecting subclinical systemic lymphoma, the pooled diagnostic yields of body CT and whole-body FDG PET/CT were 2.5% (95% CI, 1.5-3.9%) and 4.9% (95% CI, 2.8-8.5%), respectively. In the subgroup analysis, the diagnostic yield of whole-body FDG PET/CT was significantly higher than that of body CT ( = .03). Four studies reported changes in the management plan: the R-CHOP (rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine, and prednisone) regimen with or without radiation therapy was added if extracranial lymphoma involvement was detected by body CT or whole-body FDG PET/CT. The pooled false referral rate of whole-body FDG PET/CT was 5.3% (95% CI, 2.2-12.0%). The pooled rate of incidental secondary malignancy detected on whole-body FDG PET/CT was 3.1% (95% CI, 1.7-5.6%). Body imaging should be used in the initial workup of patients with suspected primary CNS lymphoma, to exclude systemic involvement. Whole-body FDG PET/CT may be a better alternative to body CT. Our results support current National Comprehensive Cancer Network guidelines for the use of body imaging to exclude subclinical systemic involvement in patients with suspected primary CNS lymphoma.
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http://dx.doi.org/10.2214/AJR.20.24036DOI Listing
May 2021

Extensive peritumoral edema and brain-to-tumor interface MRI features enable prediction of brain invasion in meningioma: development and validation.

Neuro Oncol 2021 02;23(2):324-333

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.

Background: Brain invasion by meningioma is a stand-alone criterion for tumor atypia in the 2016 World Health Organization classification, but no imaging parameter has yet been shown to be sufficient for predicting it. The aim of this study was to develop and validate an MRI-based radiomics model from the brain-to-tumor interface to predict brain invasion by meningioma.

Methods: Preoperative T2-weighted and contrast-enhanced T1-weighted imaging data were obtained from 454 patients (88 patients with brain invasion) between 2012 and 2017. Feature selection was performed from 3222 radiomics features obtained in the 1 cm thickness tumor-to-brain interface region using least absolute shrinkage and selection operator. Peritumoral edema volume, age, sex, and selected radiomics features were used to construct a random forest classifier-based diagnostic model. The performance was evaluated using the areas under the curves (AUCs) of the receiver operating characteristic in an independent cohort of 150 patients (29 patients with brain invasion) between 2018 and 2019.

Results: Volume of peritumoral edema was an independent predictor of brain invasion (P < 0.001). The top 6 interface radiomics features plus the volume of peritumoral edema were selected for model construction. The combined model showed the highest performance for prediction of brain invasion in the training (AUC 0.97; 95% CI: 0.95-0.98) and validation sets (AUC 0.91; 95% CI: 0.84-0.98), and improved diagnostic performance over volume of peritumoral edema only (AUC 0.76; 95% CI: 0.66-0.86).

Conclusion: An imaging-based model combining interface radiomics and peritumoral edema can help to predict brain invasion by meningioma and improve the diagnostic performance of known clinical and imaging parameters.
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http://dx.doi.org/10.1093/neuonc/noaa190DOI Listing
February 2021

Cerebellar Hemangioblastoma: Diagnostic Yield of Contrast-Enhanced Abdominal CT and Whole-Spine MRI as Initial Screening Imaging.

AJR Am J Roentgenol 2020 09 22;215(3):706-712. Epub 2020 Jul 22.

Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Olympic-ro 33, Seoul, 05505, Republic of Korea.

The existing literature lacks research into the benefits of initial screening imaging for patients with cerebellar hemangioblastoma. We aimed to evaluate the diagnostic yield of initial screening imaging using abdominal CT and whole-spine MRI in patients with cerebellar hemangioblastoma. This retrospective study included 117 consecutive patients with histopathologically confirmed, newly diagnosed cerebellar hemangioblastomas at a single tertiary hospital between January 2006 and October 2018. Patients underwent contrast-enhanced abdominal CT, whole-spine MRI, or both to detect abdominal and spinal lesions of von Hippel-Lindau disease. Diagnostic yields and false referral rates for initial screening imaging were determined. After exclusion of six patients who forewent any initial imaging, 111 patients were included (53 men [mean age ± SD, 51 ± 13 years] and 58 women [mean age, 43 ± 16 years]). The diagnostic yield of abdominal CT was 3.8% (4 of 105; 95% CI, 1.1-9.3%), whereas the false referral rate was 1.0% (1 of 105; 95% CI, 0.0-5.2%). For whole-spine MRI, the corresponding values were 5.6% (4 of 71; 95% CI, 1.6-13.8%) and 2.8% (2 of 71; 95% CI, 0.3-9.8%), respectively. The respective diagnostic yields in patients with a single cerebellar hemangioblastoma were both 0% (0 of 98 and 66, respectively). For patients with a single cerebellar hemangioblastoma, screening examinations with abdominal CT and whole-spine MRI are unnecessary before the results of genetic testing are available.
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http://dx.doi.org/10.2214/AJR.19.22447DOI Listing
September 2020
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