Publications by authors named "Lale Umutlu"

212 Publications

Artificial intelligence guided enhancement of digital PET: scans as fast as CT?

Eur J Nucl Med Mol Imaging 2022 Jul 29. Epub 2022 Jul 29.

Department of Nuclear Medicine and German Cancer Consortium (DKTK), University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147, Essen, Germany.

Purpose: Both digital positron emission tomography (PET) detector technologies and artificial intelligence based image post-reconstruction methods allow to reduce the PET acquisition time while maintaining diagnostic quality. The aim of this study was to acquire ultra-low-count fluorodeoxyglucose (FDG) ExtremePET images on a digital PET/computed tomography (CT) scanner at an acquisition time comparable to a CT scan and to generate synthetic full-dose PET images using an artificial neural network.

Methods: This is a prospective, single-arm, single-center phase I/II imaging study. A total of 587 patients were included. For each patient, a standard and an ultra-low-count FDG PET/CT scan (whole-body acquisition time about 30 s) were acquired. A modified pix2pixHD deep-learning network was trained employing 387 data sets as training and 200 as test cohort. Three models (PET-only and PET/CT with or without group convolution) were compared. Detectability and quantification were evaluated.

Results: The PET/CT input model with group convolution performed best regarding lesion signal recovery and was selected for detailed evaluation. Synthetic PET images were of high visual image quality; mean absolute lesion SUV (maximum standardized uptake value) difference was 1.5. Patient-based sensitivity and specificity for lesion detection were 79% and 100%, respectively. Not-detected lesions were of lower tracer uptake and lesion volume. In a matched-pair comparison, patient-based (lesion-based) detection rate was 89% (78%) for PERCIST (PET response criteria in solid tumors)-measurable and 36% (22%) for non PERCIST-measurable lesions.

Conclusion: Lesion detectability and lesion quantification were promising in the context of extremely fast acquisition times. Possible application scenarios might include re-staging of late-stage cancer patients, in whom assessment of total tumor burden can be of higher relevance than detailed evaluation of small and low-uptake lesions.
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http://dx.doi.org/10.1007/s00259-022-05901-xDOI Listing
July 2022

Lung Nodules Missed in Initial Staging of Breast Cancer Patients in PET/MRI-Clinically Relevant?

Cancers (Basel) 2022 Jul 15;14(14). Epub 2022 Jul 15.

Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, 40225 Dusseldorf, Germany.

Purpose: The evaluation of the clinical relevance of missed lung nodules at initial staging of breast cancer patients in [F]FDG-PET/MRI compared with CT.

Methods: A total of 152 patients underwent an initial whole-body [F]FDG-PET/MRI and a thoracoabdominal CT for staging. Presence, size, shape and location for each lung nodule in [F]FDG-PET/MRI was noted. The reference standard was established by taking initial CT and follow-up imaging into account (a two-step approach) to identify clinically-relevant lung nodules. Patient-based and lesion-based data analysis was performed.

Results: No patient with clinically-relevant lung nodules was missed on a patient-based analysis with MRI VIBE, while 1/84 females was missed with MRI HASTE (1%). Lesion-based analysis revealed 4/96 (4%, VIBE) and 8/138 (6%, HASTE) missed clinically-relevant lung nodules. The average size of missed lung nodules was 3.2 mm ± 1.2 mm (VIBE) and 3.6 mm ± 1.4 mm (HASTE) and the predominant location was in the left lower quadrant and close to the hilum.

Conclusion: All patients with newly-diagnosed breast cancer and clinically-relevant lung nodules were detected at initial [F]FDG-PET/MRI staging. However, due to the lower sensitivity in detecting lung nodules, a small proportion of clinically-relevant lung nodules were missed. Thus, supplemental low-dose chest CT after neoadjuvant therapy should be considered for backup.
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http://dx.doi.org/10.3390/cancers14143454DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321171PMC
July 2022

Optimized whole-body positron emission tomography magnetic resonance imaging sequence workflow in pediatric Hodgkin lymphoma patients.

J Nucl Med 2022 Jul 14. Epub 2022 Jul 14.

Department of Nuclear Medicine, University of Leipzig, Germany.

Fluorodeoxyglucose positron emission tomography (PET)/ magnetic resonance imaging (MRI) might be the diagnostic method of choice for Hodgkin lymphoma patients, as it combines significant metabolic information provided by PET with excellent soft tissue contrast in MRI and avoids radiation exposure from computed tomography (CT). However, a major issue are longer examination times compared to PET/CT, especially for younger children needing anesthesia. Thus, a targeted selection of suitable whole-body MRI sequences is important to optimize the PET/MRI workflow. Initial PET/MRI scans of 84 EuroNet-PHL-C2 study patients from 13 international PET centers were evaluated. In each available MRI sequence, a total of five PET-positive lymph nodes were assessed. If extranodal involvement occurred, two splenic lesions, two skeletal lesions and two lung lesions were also assessed. A detection rate was calculated dividing the number of visible, anatomically assignable and measurable lesions in the respective MRI sequence by the number of all lesions. Transverse relaxation time-weighted (T2w) transverse sequences with fat saturation (fs) yielded the best result with detection rates of 95% for nodal lesions, 62% for splenic lesions, 94% for skeletal lesions and 83% for lung lesions, followed by T2w transverse sequences without fs (86%, 49%, 16% and 59%, respectively) and longitudinal relaxation time-weighted (T1w) contrast-enhanced transverse sequences with fs (74%, 35%, 57% and 55%, respectively). T2w transverse sequences with fs yielded the highest detection rates and are well-suited for accurate whole-body PET/MRI in lymphoma patients. There is no evidence to recommend the use of contrast agents.
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http://dx.doi.org/10.2967/jnumed.122.264112DOI Listing
July 2022

Safety and efficacy of 90Y-FAPI-46 radioligand therapy in patients with advanced sarcoma and other cancer entities.

Clin Cancer Res 2022 Jul 14. Epub 2022 Jul 14.

University Hospital Essen, West German Cancer Cen, Essen, Germany.

Purpose: We report efficacy and safety of 90Y-FAPI-46-RLT in patients with advanced sarcoma, pancreatic cancer (PDAC) and other cancer entities.

Experimental Design: Up to four cycles of RLT were offered to patients with (a) progressive metastatic malignancy, (b) exhaustion of approved therapies, and (c) high fibroblast activation protein (FAP) expression, defined as SUVmax≥10 in more than 50% of tumor. Primary endpoint was RECIST response after RLT. Secondary endpoints included PET response (PERCIST), overall survival, dosimetry and safety of FAP-RLT.

Results: Among n=119 screened patients, n=21 (18%) were found eligible (n=16/3/1/1 sarcoma/PDAC/prostate/gastric cancer; 38% ECOG≥2) and received n=47 90Y-FAPI-46-RLT cycles; n=16/21 (76%) patients underwent repeat RLT. By RECIST disease control was confirmed in n=8/21 patients (38%; 8/16 [50%] of evaluable patients). There were 1 partial response and 7 stable diseases after RLT. Disease control was associated with prolonged overall survival (p=0.013). PERCIST response was noted in n=8/21 patients (38%; 8/15 [53%] of evaluable patients). Dosimetry was acquired in n=19 (90%) patients. Mean absorbed dose was 0.53Gy/GBq in kidney, 0.04Gy/GBq in bone marrow and <0.14Gy/GBq in liver and lung. Treatment-related grade 3 or 4 adverse events were observed in n=8 (38%) patients with thrombocytopenia (n=6) and anemia (n=6) being most prevalent.

Conclusion: 90Y-FAPI-46-RLT was safe and led to RECIST partial response in one case as well as stable disease in about one third of patients with initially progressive sarcomas, PDAC and other cancers. Discontinuation after the first cycle and a low rate of partial response require for future improvement of FAP-RLT.
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http://dx.doi.org/10.1158/1078-0432.CCR-22-1432DOI Listing
July 2022

Intra-Individual Comparison of I-PET/CT and I-PET/MR Hybrid Imaging of Patients with Resected Differentiated Thyroid Carcinoma: Aspects of Attenuation Correction.

Cancers (Basel) 2022 Jun 21;14(13). Epub 2022 Jun 21.

High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, 45147 Essen, Germany.

Background: This study evaluates the quantitative differences between 124-iodine (I) positron emission tomography/computed tomography (PET/CT) and PET/magnetic resonance imaging (PET/MR) in patients with resected differentiated thyroid carcinoma (DTC).

Methods: = 43 I PET/CT and PET/MR exams were included. CT-based attenuation correction (AC) in PET/CT and MR-based AC in PET/MR with bone atlas were compared concerning bone AC in the head-neck region. AC-map artifacts (e.g., dentures) were noted. Standardized uptake values (SUV) were measured in lesions in each PET data reconstruction. Relative differences in SUV were calculated between PET/CT and PET/MR with bone atlas.

Results: Overall, = 111 I-avid lesions were detected in all PET/CT, while = 132 lesions were detected in PET/MR. The median in SUV for = 98 congruent lesions measured in PET/CT was 12.3. In PET/MR, the median in SUV was 16.6 with bone in MR-based AC.

Conclusions: I-PET/CT and I-PET/MR hybrid imaging of patients with DTC after thyroidectomy provides overall comparable quantitative results in a clinical setting despite different patient positioning and AC methods. The overall number of detected I-avid lesions was higher for PET/MR compared to PET/CT. The measured average SUV values for congruent lesions were higher for PET/MR.
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http://dx.doi.org/10.3390/cancers14133040DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9264885PMC
June 2022

Deep Learning-driven classification of external DICOM studies for PACS archiving.

Eur Radiol 2022 Jul 5. Epub 2022 Jul 5.

Institute of AI in Medicine (IKIM), University Hospital Essen, Girardetstraße 2, 45131, Essen, Germany.

Objectives: Over the course of their treatment, patients often switch hospitals, requiring staff at the new hospital to import external imaging studies to their local database. In this study, the authors present MOdality Mapping and Orchestration (MOMO), a Deep Learning-based approach to automate this mapping process by combining metadata analysis and a neural network ensemble.

Methods: A set of 11,934 imaging series with existing anatomical labels was retrieved from the PACS database of the local hospital to train an ensemble of neural networks (DenseNet-161 and ResNet-152), which process radiological images and predict the type of study they belong to. We developed an algorithm that automatically extracts relevant metadata from imaging studies, regardless of their structure, and combines it with the neural network ensemble, forming a powerful classifier. A set of 843 anonymized external studies from 321 hospitals was hand-labeled to assess performance. We tested several variations of this algorithm.

Results: MOMO achieves 92.71% accuracy and 2.63% minor errors (at 99.29% predictive power) on the external study classification task, outperforming both a commercial product (82.86% accuracy, 1.36% minor errors, 96.20% predictive power) and a pure neural network ensemble (72.69% accuracy, 10.3% minor errors, 99.05% predictive power) performing the same task. We find that the highest performance is achieved by an algorithm that combines all information into one vote-based classifier.

Conclusion: Deep Learning combined with metadata matching is a promising and flexible approach for the automated classification of external DICOM studies for PACS archiving.

Key Points: • The algorithm can successfully identify 76 medical study types across seven modalities (CT, X-ray angiography, radiographs, MRI, PET (+CT/MRI), ultrasound, and mammograms). • The algorithm outperforms a commercial product performing the same task by a significant margin (> 9% accuracy gain). • The performance of the algorithm increases through the application of Deep Learning techniques.
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http://dx.doi.org/10.1007/s00330-022-08926-wDOI Listing
July 2022

Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis.

Lancet Digit Health 2022 07;4(7):e507-e519

Department of Diagnostic and Interventional Radiology and Neuroradiology, University-Hospital Essen, Essen, Germany.

Background: We propose a decision-referral approach for integrating artificial intelligence (AI) into the breast-cancer screening pathway, whereby the algorithm makes predictions on the basis of its quantification of uncertainty. Algorithmic assessments with high certainty are done automatically, whereas assessments with lower certainty are referred to the radiologist. This two-part AI system can triage normal mammography exams and provide post-hoc cancer detection to maintain a high degree of sensitivity. This study aimed to evaluate the performance of this AI system on sensitivity and specificity when used either as a standalone system or within a decision-referral approach, compared with the original radiologist decision.

Methods: We used a retrospective dataset consisting of 1 193 197 full-field, digital mammography studies carried out between Jan 1, 2007, and Dec 31, 2020, from eight screening sites participating in the German national breast-cancer screening programme. We derived an internal-test dataset from six screening sites (1670 screen-detected cancers and 19 997 normal mammography exams), and an external-test dataset of breast cancer screening exams (2793 screen-detected cancers and 80 058 normal exams) from two additional screening sites to evaluate the performance of an AI algorithm on sensitivity and specificity when used either as a standalone system or within a decision-referral approach, compared with the original individual radiologist decision at the point-of-screen reading ahead of the consensus conference. Different configurations of the AI algorithm were evaluated. To account for the enrichment of the datasets caused by oversampling cancer cases, weights were applied to reflect the actual distribution of study types in the screening programme. Triaging performance was evaluated as the rate of exams correctly identified as normal. Sensitivity across clinically relevant subgroups, screening sites, and device manufacturers was compared between standalone AI, the radiologist, and decision referral. We present receiver operating characteristic (ROC) curves and area under the ROC (AUROC) to evaluate AI-system performance over its entire operating range. Comparison with radiologists and subgroup analysis was based on sensitivity and specificity at clinically relevant configurations.

Findings: The exemplary configuration of the AI system in standalone mode achieved a sensitivity of 84·2% (95% CI 82·4-85·8) and a specificity of 89·5% (89·0-89·9) on internal-test data, and a sensitivity of 84·6% (83·3-85·9) and a specificity of 91·3% (91·1-91·5) on external-test data, but was less accurate than the average unaided radiologist. By contrast, the simulated decision-referral approach significantly improved upon radiologist sensitivity by 2·6 percentage points and specificity by 1·0 percentage points, corresponding to a triaging performance at 63·0% on the external dataset; the AUROC was 0·982 (95% CI 0·978-0·986) on the subset of studies assessed by AI, surpassing radiologist performance. The decision-referral approach also yielded significant increases in sensitivity for a number of clinically relevant subgroups, including subgroups of small lesion sizes and invasive carcinomas. Sensitivity of the decision-referral approach was consistent across the eight included screening sites and three device manufacturers.

Interpretation: The decision-referral approach leverages the strengths of both the radiologist and AI, demonstrating improvements in sensitivity and specificity surpassing that of the individual radiologist and of the standalone AI system. This approach has the potential to improve the screening accuracy of radiologists, is adaptive to the requirements of screening, and could allow for the reduction of workload ahead of the consensus conference, without discarding the generalised knowledge of radiologists.

Funding: Vara.
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http://dx.doi.org/10.1016/S2589-7500(22)00070-XDOI Listing
July 2022

Streamlining Patient Management of Suspected COVID-19 Patients in the Emergency Department: Incorporation of Pulmonary CT Angiography into the Triaging Algorithm.

Diagnostics (Basel) 2022 May 9;12(5). Epub 2022 May 9.

Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147 Essen, Germany.

Purpose: To evaluate the use of pulmonary computed tomography (CT) angiography during initial admission at an emergency department (ED), to identify COVID-19 patients with accompanying pulmonary embolism (PE) and its impact on clinical management.

Methods: We performed a retrospective analysis of COVID-19 patients that underwent pulmonary CT angiography at the ED. CT scans were evaluated for the presence and extent of PE and for imaging changes suspicious of COVID-19. Patients were subdivided into two groups: (1) Group A consisted of patients with proven COVID-19 based on real-time polymerase chain reaction (RT-PCR), and (2) Group B of patients suspected for COVID-19, comprising patients positive on RT-PCR and/or COVID-19-suspicious CT findings. To assess the differences between patients with and without pulmonary embolism, Fisher's exact test was used.

Results: A total of 308 patients were admitted to the ED for diagnostic work-up of dyspnea and suspected COVID-19, and 95 patients underwent pulmonary CT angiography. PE was detected in 13.6% (3/22) of patients in Group A and 20.7% (6/29) in Group B. No significant differences were observed between patients with and without PE concerning hospitalization (Group B: 100% (6/6) vs. 91.3% (21/23)), the necessity of oxygen therapy (Group B: 66% (4/6) vs. 43.5% (10/23)), and death (Group B: 33% (2/6) vs. 4.3% (1/23) > 0.05, respectively).

Conclusions: In 20.7% of COVID-19 patients, PE was detected upon admission to the ED. Although the incorporation of early pulmonary CT angiography in patients suspicious of COVID-19 may be beneficial to identify concomitant PE, further studies are necessary to corroborate these findings.
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http://dx.doi.org/10.3390/diagnostics12051183DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140044PMC
May 2022

Effects of Anti-Tumor Necrosis Factor Therapy on Osteoblastic Activity at Sites of Inflammatory and Structural Lesions in Radiographic Axial Spondyloarthritis: A Prospective Proof-of-Concept Study Using Positron Emission Tomography/Magnetic Resonance Imaging of the Sacroiliac Joints and Spine.

Arthritis Rheumatol 2022 Apr 27. Epub 2022 Apr 27.

Rheumazentrum Ruhrgebiet, Herne, and Ruhr-University Bochum, Bochum, Germany.

Objective: Proof-of-concept trial to determine the effects of tumor necrosis factor inhibitor (TNFi) therapy on osteoblastic activity at sites of inflammatory and structural lesions in patients with radiographic axial spondyloarthritis (SpA), using fluorine 18-labeled NaF ( F-NaF) positron emission tomography/magnetic resonance imaging (PET/MRI).

Methods: Sixteen patients with clinically active radiographic axial SpA were prospectively enrolled to receive TNFi treatment and undergo F-NaF PET/MRI of the sacroiliac (SI) joints and spine at baseline and at a follow-up visit 3-6 months after treatment initiation. Three readers (1 for PET/MRI and 2 for conventional MRI) evaluated all images, blinded to time point. Bone marrow edema, structural lesions (i.e., fat lesions, sclerosis, erosions, and ankylosis), and F-NaF uptake at SI joint quadrants and vertebral corners (VCs) were recorded.

Results: Overall, 11 male and 5 female patients (mean age ± SD 38.6 ± 12.0 years) were followed up for a mean duration of 4.6 months (range 3-6). F-NaF PET/MRI was conducted on SI joints for 16 patients and the spine for 10; 128 SI joint quadrants and 920 VCs were analyzed at each time point. At baseline, F-NaF uptake was demonstrated in 96.0% of SI joint quadrants with bone marrow edema, 94.2% with sclerosis, and 88.3% with fat lesions. At follow-up, 65.3% of SI joint quadrants with bone marrow edema (P < 0.001), 33.8% with sclerosis (P = 0.23), and 24.5% with fat lesions (P = 0.01) had less F-NaF uptake, compared with baseline. For VCs, F-NaF uptake at baseline was found in 81.5% of edges with sclerosis, 41.9% with fat lesions, and 33.7% with bone marrow edema. At follow-up, 73.5% of VCs with bone marrow edema (P = 0.01), 53.3% with fat lesions (P = 0.03), and 55.6% with sclerosis (P = 0.16) showed less F-NaF uptake, compared with baseline.

Conclusion: Anti-TNF antibody treatment led to a significant decrease in osteoblastic activity within 3-6 months, especially, but not solely, at sites of inflammation. Larger data sets are needed for confirmation of the antiosteoblastic effects of TNFi for the prevention of radiographic progression in axial SpA.
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http://dx.doi.org/10.1002/art.42149DOI Listing
April 2022

First experiences with dynamic renal [Ga]Ga-DOTA PET/CT: a comparison to renal scintigraphy and compartmental modelling to non-invasively estimate the glomerular filtration rate.

Eur J Nucl Med Mol Imaging 2022 Aug 12;49(10):3373-3386. Epub 2022 Apr 12.

Department of Nuclear Medicine, University Hospital Essen, West German Cancer Center (WTZ), University of Duisburg-Essen, Hufelandstrasse 55, 45147, Essen, Germany.

Purpose: The determination of the glomerular filtration rate (GFR) is decisive for a variety of clinical issues, for example, to monitor the renal function in radionuclide therapy patients. Renal scintigraphy using glomerularly filtered tracers allows combined acquisition of renograms and GFR estimation but requires repeated blood sampling for several hours. In contrast, dynamic PET imaging using the glomerularly filtered tracer [Ga]Ga-DOTA bears the potential to non-invasively estimate the GFR by compartmental kinetic modelling. Here, we report the, to our knowledge, first comparison of human renal dynamic [Ga]Ga-DOTA PET imaging in comparison to renal scintigraphy and compare PET-derived to serum creatinine-derived GFR measurements.

Methods: Dynamic [Ga]Ga-DOTA PET data were acquired for 30 min immediately after tracer injection in 12 patients. PET and renal scintigraphy images were visually interpreted in a consensus read by three nuclear medicine physicians. The functional renal cortex was segmented to obtain time-activity curves. The arterial input function was estimated from the PET signal in the abdominal aorta. Single-compartmental tracer kinetic modelling was performed to calculate the GFR using complete 30-min (GFR) and reduced 15-min PET data sets (GFR) to evaluate whether a shorter acquisition time is sufficient for an accurate GFR estimation. A modified approach excluding minutes 2 to 10 was applied to reduce urinary spill-over effects. Serum creatinine-derived GFR (CKD-EPI-formula) was used as reference standard.

Results: PET image interpretation revealed the same findings as conventional scintigraphy (2/12 patients with both- and 1/12 patients with right-sided urinary obstruction). Model fit functions were substantially improved for the modified approach to exclude spill-over. Depending on the modelling approach, GFR and both GFR and GFR were well correlated with interclass correlation coefficients (ICCs) from 0.74 to 0.80 and Pearson's correlation coefficients (PCCs) from 0.74 to 0.81. For a subgroup of patients with undisturbed urinary efflux (n = 9), correlations were good to excellent (ICCs from 0.82 to 0.95 and PCCs from 0.83 to 0.95). Overall, GFR and GFR were excellently correlated (ICCs from 0.96 to 0.99 and PCCs from 0.96 to 0.99).

Conclusion: Renal [Ga]Ga-DOTA PET can be a suitable alternative to conventional scintigraphy. Visual assessment of PET images and conventional renograms revealed comparable results. GFR values derived by non-invasive single-compartmental-modelling of PET data show a good correlation to serum creatinine-derived GFR values. In patients with undisturbed urinary efflux, the correlation was excellent. Dynamic PET data acquisition for 15 min is sufficient for visual evaluation and GFR derivation.
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http://dx.doi.org/10.1007/s00259-022-05781-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002049PMC
August 2022

Multiparametric F-FDG PET/MRI-Based Radiomics for Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

Cancers (Basel) 2022 Mar 29;14(7). Epub 2022 Mar 29.

Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.

Background: The aim of this study was to assess whether multiparametric F-FDG PET/MRI-based radiomics analysis is able to predict pathological complete response in breast cancer patients and hence potentially enhance pretherapeutic patient stratification.

Methods: A total of 73 female patients (mean age 49 years; range 27-77 years) with newly diagnosed, therapy-naive breast cancer underwent simultaneous F-FDG PET/MRI and were included in this retrospective study. All PET/MRI datasets were imported to dedicated software (ITK-SNAP v. 3.6.0) for lesion annotation using a semi-automated method. Pretreatment biopsy specimens were used to determine tumor histology, tumor and nuclear grades, and immunohistochemical status. Histopathological results from surgical tumor specimens were used as the reference standard to distinguish between complete pathological response (pCR) and noncomplete pathological response. An elastic net was employed to select the most important radiomic features prior to model development. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for each model.

Results: The best results in terms of AUCs and NPV for predicting complete pathological response in the entire cohort were obtained by the combination of all MR sequences and PET (0.8 and 79.5%, respectively), and no significant differences from the other models were observed. In further subgroup analyses, combining all MR and PET data, the best AUC (0.94) for predicting complete pathologic response was obtained in the HR+/HER2- group. No difference between results with/without the inclusion of PET characteristics was observed in the TN/HER2+ group, each leading to an AUC of 0.92 for all MR and all MR + PET datasets.

Conclusion: F-FDG PET/MRI enables comprehensive high-quality radiomics analysis for the prediction of pCR in breast cancer patients, especially in those with HR+/HER2- receptor status.
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http://dx.doi.org/10.3390/cancers14071727DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8996836PMC
March 2022

A Role of PET/MR in Breast Cancer?

Semin Nucl Med 2022 Sep 5;52(5):611-618. Epub 2022 Mar 5.

Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, Dusseldorf, Germany. Electronic address:

PET/MRI has been available since 2010, representing the newest of the hybrid imaging modalities. It combines functional as well as morphologic high-resolution MRI data with metabolic information from PET, providing image data sets with complementary information. Especially in the field of oncology, PET/MRI is a promising imaging modality with diverse applications. Since its introduction there has already been a large quantity of studies indicating a high diagnostic value of PET/MRI for whole-body cancer staging. The simultaneous acquisition of metabolic PET and MRI data is expected to have a major impact in the assessment of breast cancer due to the superior resolution of MRI in breast tissue compared to CT. While there is an ongoing debate if the added value of breast F-FDG PET/MRI in the primary diagnosis of breast cancer has clinical impact compared to breast MRI, a large number of studies have proven that F-FDG PET/MRI is extremely valuable for whole-body breast cancer staging and especially for treatment monitoring. Besides molecular markers, distant metastases and axillary lymph node involvement are the most important predictors for overall survival and recurrence in breast cancer patients. Due to the high soft tissue contrast, functional imaging from MRI and metabolic information from PET, distant metastases in organs and in particular in the bones are detected better compared to the conventional staging algorithm with CT and bone scan and can significantly influence the therapy regime. Instead of mastectomy and extensive axillary dissection being performed in many patients, the improved imaging and diagnostic confidence also has helped that local therapy control can be achieved with reduced invasiveness. A future role of F-FDG PET/MRI could therefore become treatment response evaluation under neoadjuvant treatment before or instead of operative therapy. In addition to reduced radiation exposure compared to conventional staging examinations, hybrid F-FDG PET/MRI might serve as a comprehensive "all-in-one" breast cancer staging tool, providing precise local and whole-body staging including MRI of the head in one procedure, which save patients a diagnostic marathon.
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http://dx.doi.org/10.1053/j.semnuclmed.2022.01.003DOI Listing
September 2022

Determining the anatomical site in knee radiographs using deep learning.

Sci Rep 2022 03 7;12(1):3995. Epub 2022 Mar 7.

Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Hufelandstr. 55, 45147, Essen, Germany.

An important quality criterion for radiographs is the correct anatomical side marking. A deep neural network is evaluated to predict the correct anatomical side in radiographs of the knee acquired in anterior-posterior direction. In this retrospective study, a ResNet-34 network was trained on 2892 radiographs from 2540 patients to predict the anatomical side of knees in radiographs. The network was evaluated in an internal validation cohort of 932 radiographs of 816 patients and in an external validation cohort of 490 radiographs from 462 patients. The network showed an accuracy of 99.8% and 99.9% on the internal and external validation cohort, respectively, which is comparable to the accuracy of radiographers. Anatomical side in radiographs of the knee in anterior-posterior direction can be deduced from radiographs with high accuracy using deep learning.
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http://dx.doi.org/10.1038/s41598-022-08020-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8900105PMC
March 2022

Pediatric age estimation from radiographs of the knee using deep learning.

Eur Radiol 2022 Jul 1;32(7):4813-4822. Epub 2022 Mar 1.

Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, D-45147, Essen, Germany.

Objectives: Age estimation, especially in pediatric patients, is regularly used in different contexts ranging from forensic over medicolegal to clinical applications. A deep neural network has been developed to automatically estimate chronological age from knee radiographs in pediatric patients.

Methods: In this retrospective study, 3816 radiographs of the knee from pediatric patients from a German population (acquired between January 2008 and December 2018) were collected to train a neural network. The network was trained to predict chronological age from the knee radiographs and was evaluated on an independent validation cohort of 423 radiographs (acquired between January 2019 and December 2020) and on an external validation cohort of 197 radiographs.

Results: The model showed a mean absolute error of 0.86 ± 0.72 years and 0.9 ± 0.71 years on the internal and external validation cohorts, respectively. Separating age classes (< 14 years from ≥ 14 years and < 18 years from ≥ 18 years) showed AUCs between 0.94 and 0.98.

Conclusions: The chronological age of pediatric patients can be estimated with good accuracy from radiographs of the knee using a deep neural network.

Key Points: • Radiographs of the knee can be used for age estimations in pediatric patients using a standard deep neural network. • The network showed a mean absolute error of 0.86 ± 0.72 years in an internal validation cohort and of 0.9 ± 0.71 years in an external validation cohort. • The network can be used to separate the age classes < 14 years from ≥ 14 years with an AUC of 0.97 and < 18 years from ≥ 18 years with an AUC of 0.94.
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http://dx.doi.org/10.1007/s00330-022-08582-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213267PMC
July 2022

Evaluation of improved CT-based hardware attenuation correction in PET/MRI: Application to a 16-channel RF breast coil.

Med Phys 2022 Apr 21;49(4):2279-2294. Epub 2022 Feb 21.

High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, Essen, Germany.

Purpose: The aim of this study was to compare and evaluate three different bilinear conversion curves for attenuation correction (AC) of a 16-channel radiofrequency (RF) coil in positron emission tomography/magnetic resonance (PET/MR) breast cancer imaging.

Methods: The quantitative impact of three different bilinear conversions of computed tomography (CT) data for the AC of a 16-channel RF breast coil was systematically evaluated in phantom measurements and on n = 20 PET/MR patients with breast cancer. PET data were reconstructed four times: (1) no coil AC (C-NAC) serving as a reference, (2) established bilinear conversion by Carney et al., (3) bilinear conversion by Paulus et al., and (4) bilinear conversion by Oehmigen et al. Relative differences in PET data were calculated.

Results: Independent of the choice of bilinear conversion, significant gains in PET signal, compared to C-NAC, were measurable in all phantom and patient measurements. Mean relative differences of ca. 10% in SUVmean (i.e., standardized uptake value; maximal relative differences up to 30%) due to the integration of the coil AC were calculated, compared to C-NAC in phantom and patient measurements. Relative difference images depict that the quantitative impact of coil AC is highest in regions close to the RF coil when compared to no AC data. Bilinear conversion by Carney et al. shows a slightly overcorrection (2.9%), whereas the conversion by Paulus et al. provides a slight undercorrection of the PET images (-1.6%) in comparison to the no-coil measurement. The bilinear conversion proposed by Oehmigen et al. provides the most appropriate AC for the breast coil in this phantom experiment (-0.2%). A total of 23 congruent lesions could be detected in all patients. All lesions could be detected in all reconstructions.

Conclusions: For the best possible PET image quality and accurate PET quantification in breast PET/MRI, the AC of MR hardware components is important. The bilinear conversion proposed by Oehmigen et al. provides the most appropriate AC for the breast coil in this study.
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http://dx.doi.org/10.1002/mp.15535DOI Listing
April 2022

Free-breathing 3D Stack of Stars GRE (StarVIBE) sequence for detecting pulmonary nodules in F-FDG PET/MRI.

EJNMMI Phys 2022 Feb 7;9(1):11. Epub 2022 Feb 7.

Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, Moorenstrasse 5, 40225, Düsseldorf, Germany.

Background: The free-breathing T1-weighted 3D Stack of Stars GRE (StarVIBE) MR sequence potentially reduces artifacts in chest MRI. The purpose of this study was to evaluate StarVIBE for the detection of pulmonary nodules in F-FDG PET/MRI.

Material And Methods: In this retrospective analysis, conducted on a prospective clinical trial cohort, 88 consecutive women with newly diagnosed breast cancer underwent both contrast-enhanced whole-body F-FDG PET/MRI and computed tomography (CT). Patients' chests were examined on CT as well as on StarVIBE and conventional T1-weighted VIBE and T2-weighted HASTE MR sequences, with CT serving as the reference standard. Presence, size, and location of all detectable lung nodules were assessed. Wilcoxon test was applied to compare nodule features and Pearson's, and Spearman's correlation coefficients were calculated.

Results: Out of 65 lung nodules detected in 36 patients with CT (3.7 ± 1.4 mm), StarVIBE was able to detect 31 (47.7%), VIBE 26 (40%) and HASTE 11 (16.8%), respectively. Overall, CT showed a significantly higher detectability than all MRI sequences combined (65 vs. 36, difference 44.6%, p < 0.001). The VIBE showed a significantly better detection rate than the HASTE (23.1%, p = 0.001). Detection rates between StarVIBE and VIBE did not significantly differ (7.7%, p = 0.27), but the StarVIBE showed a significant advantage detecting centrally located pulmonary nodules (66.7% vs. 16.7%, p = 0.031). There was a strong correlation in nodule size between CT and MRI sequences (HASTE: ρ = 0.80, p = 0.003; VIBE: ρ = 0.77, p < 0.001; StarVIBE: ρ = 0.78, p < 0.001). Mean image quality was rated as good to excellent for CT and MRI sequences.

Conclusion: The overall lung nodule detection rate of StarVIBE was slightly, but not significantly, higher than conventional T1w VIBE and significantly higher than T2w HASTE. Detectability of centrally located nodules is better with StarVIBE than with VIBE. Nevertheless, all MRI analyses demonstrated considerably lower detection rates for small lung nodules, when compared to CT.
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http://dx.doi.org/10.1186/s40658-022-00439-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8821742PMC
February 2022

Metabolic imaging with FDG-PET and time to progression in patients discontinuing immune-checkpoint inhibition for metastatic melanoma.

Cancer Imaging 2022 Feb 5;22(1):11. Epub 2022 Feb 5.

Department of Dermatology, University of Duisburg-Essen and German Cancer Consortium (DKTK), University Hospital Essen, Hufelandstr, 55, 45147, Essen, Germany.

Background: The optimal duration of immune checkpoint blockade (ICB) therapy is not well established. Active residual disease is considered prohibitive for treatment discontinuation and its detection by diagnostic CT imaging is limited. Here, we set out to determine the potential added value of 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) to identify patients at higher risk of relapse following discontinuation of ICB in advanced melanoma.

Methods: Metastatic melanoma patients who discontinued ICB were identified retrospectively. Eligible patients received FDG-PET and diagnostic CT within four months of ICB discontinuation. We defined morphologic response using RECIST v1.1. Complete metabolic response (CMR) was defined as uptake in tumor lesions below background, whereas any site of residual, FDG-avid disease was rated as non-CMR. The primary endpoint was time to progression (TTP) after therapy discontinuation stratified by morphologic and metabolic imaging response using Kaplan-Meier estimates and log-rank test.

Results: Thiry-eight patients were eligible for this analysis. Median follow-up was 37.3 months since ICB discontinuation. Median TTP in the overall cohort was not reached. A greater proportion of patients were rated as CMR in PET (n = 34, 89.5%) as compared to complete response (CR) in CT (n = 13, 34.2%). Median TTP was reached in patients with non-CMR (12.7 months, 95%CI 4.4-not reached) but not for patients with CMR (log-rank: p < 0.001). All patients with complete response by CT had CMR by PET. In a subset of patients excluding those with complete response by CT, TTP remained significantly different between CMR and non-CMR (log-rank: p < 0.001).

Conclusion: Additional FDG-PET at time of discontinuation of ICB therapy helps identify melanoma patients with a low risk of recurrence and favourable prognosis compared to CT imaging alone. Results may have clinical relevance especially for patients with residual tumor burden.
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http://dx.doi.org/10.1186/s40644-022-00449-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8817553PMC
February 2022

An uncertainty-aware, shareable, and transparent neural network architecture for brain-age modeling.

Sci Adv 2022 Jan 5;8(1):eabg9471. Epub 2022 Jan 5.

Department of Psychiatry and Psychotherapy, and Department of Neurology, Jena University Hospital, Jena, Germany.

The deviation between chronological age and age predicted from neuroimaging data has been identified as a sensitive risk marker of cross-disorder brain changes, growing into a cornerstone of biological age research. However, machine learning models underlying the field do not consider uncertainty, thereby confounding results with training data density and variability. Also, existing models are commonly based on homogeneous training sets, often not independently validated, and cannot be shared because of data protection issues. Here, we introduce an uncertainty-aware, shareable, and transparent Monte Carlo dropout composite quantile regression (MCCQR) Neural Network trained on = 10,691 datasets from the German National Cohort. The MCCQR model provides robust, distribution-free uncertainty quantification in high-dimensional neuroimaging data, achieving lower error rates compared with existing models. In two examples, we demonstrate that it prevents spurious associations and increases power to detect deviant brain aging. We make the pretrained model and code publicly available.
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http://dx.doi.org/10.1126/sciadv.abg9471DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8730629PMC
January 2022

Clinical Use of PET/MR in Oncology: An Update.

Semin Nucl Med 2022 05 31;52(3):356-364. Epub 2021 Dec 31.

Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.

The combination of PET and MRI is one of the recent advances of hybrid imaging. Yet to date, the adoption rate of PET/MRI systems has been rather slow. This seems to be partially caused by the high costs of PET/MRI systems and the need to verify an incremental benefit over PET/CT or sequential PET/CT and MRI. In analogy to PET/CT, the MRI part of PET/MRI was primarily used for anatomical imaging. Though this can be advantageous, for example in diseases where the superior soft tissue contrast of MRI is highly appreciated, the sole use of MRI for anatomical orientation lessens the potential of PET/MRI. Consequently, more recent studies focused on its multiparametric potential and employed diffusion weighted sequences and other functional imaging sequences in PET/MRI. This integration puts the focus on a more wholesome approach to PET/MR imaging, in terms of releasing its full potential for local primary staging based on multiparametric imaging and an included one-stop shop approach for whole-body staging. This approach as well as the implementation of computational analysis, in terms of radiomics analysis, has been shown valuable in several oncological diseases, as will be discussed in this review article.
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http://dx.doi.org/10.1053/j.semnuclmed.2021.11.012DOI Listing
May 2022

ULTRA-LOW-DOSE COMPUTED TOMOGRAPHY IN UROLITHIASIS-EFFECT OF AN ADDITIONAL TIN FILTER ON IMAGE QUALITY AND RADIATION DOSE.

Radiat Prot Dosimetry 2021 Dec;197(3-4):146-153

To compare radiation dose and image quality of three CT-scanners using optimal dose protocols in patients with suspected urolithiasis regarding additional hardware (tin filter) and software (iterative reconstruction). Examinations from a single-source CT-scanner (A2) and a dual-source CT-scanner (DSCT) (A1) were compared to a tin filter DSCT (B) regarding dose-length product (DLP) and volume-weighted CT dose-index (CTDIvol). DLP of B was 51 and 53% lower in comparison to A1 and A2 (78.62, 159.20 and 165.80 mGy·cm, respectively; P < 0.0001). CTDIvol of B was 53% and 56% significantly lower compared to A1 and A2, respectively (1.52 vs. 3.22 vs. 3.46 mGy; P < 0.0001). Image quality in B proved to be similar to A1 and A2 (3.57, 3.51 and 3.60, respectively; P > 0.05). Inter-rater agreement regarding image quality was good for all CT-scanners (κ = 0.62). Modern CTs with a built-in tin filter allow a significant reduction of radiation exposure in patients with suspected urolithiasis by optimizing the X-ray spectrum.
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http://dx.doi.org/10.1093/rpd/ncab180DOI Listing
December 2021

Fully Automated MR Based Virtual Biopsy of Cerebral Gliomas.

Cancers (Basel) 2021 Dec 8;13(24). Epub 2021 Dec 8.

Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Hufelandstr. 55, D-45147 Essen, Germany.

Objective: The aim of this study was to investigate the diagnostic accuracy of a radiomics analysis based on a fully automated segmentation and a simplified and robust MR imaging protocol to provide a comprehensive analysis of the genetic profile and grading of cerebral gliomas for everyday clinical use.

Methods: MRI examinations of 217 therapy-naïve patients with cerebral gliomas, each comprising a non-contrast T1-weighted, FLAIR and contrast-enhanced T1-weighted sequence, were included in the study. In addition, clinical and laboratory parameters were incorporated into the analysis. The BraTS 2019 pretrained DeepMedic network was used for automated segmentation. The segmentations generated by DeepMedic were evaluated with 200 manual segmentations with a DICE score of 0.8082 ± 0.1321. Subsequently, the radiomics signatures were utilized to predict the genetic profile of ATRX, IDH1/2, MGMT and 1p19q co-deletion, as well as differentiating low-grade glioma from high-grade glioma.

Results: The network provided an AUC (validation/test) for the differentiation between low-grade gliomas vs. high-grade gliomas of 0.981 ± 0.015/0.885 ± 0.02. The best results were achieved for the prediction of the ATRX expression loss with AUCs of 0.979 ± 0.028/0.923 ± 0.045, followed by 0.929 ± 0.042/0.861 ± 0.023 for the prediction of IDH1/2. The prediction of 1p19q and MGMT achieved moderate results, with AUCs of 0.999 ± 0.005/0.711 ± 0.128 for 1p19q and 0.854 ± 0.046/0.742 ± 0.050 for MGMT.

Conclusion: This fully automated approach utilizing simplified MR protocols to predict the genetic profile and grading of cerebral gliomas provides an easy and efficient method for non-invasive tumor decoding.
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http://dx.doi.org/10.3390/cancers13246186DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8699054PMC
December 2021

Atypical bilateral ventilation/perfusion mismatches in an asymptomatic patient suffering from metastatic thyroid cancer.

Eur J Hybrid Imaging 2021 Dec 20;5(1):25. Epub 2021 Dec 20.

Department of Nuclear Medicine, University Hospital Essen, West German Cancer Center (WTZ), University of Duisburg-Essen, Hufelandstrasse 55, 45147, Essen, Germany.

Background: Pulmonary embolism is indicated by ventilation/perfusion (V/P) mismatches in ventilation/perfusion scintigraphy. However, other pathologies may also evoke segmental or lobar mismatches. Thus, diagnosis can be difficult in asymptomatic patients with equivocal clinical presentation.

Case Presentation: We present a case of multiple bilateral pulmonary ventilation/perfusion mismatches in a poorly differentiated thyroid cancer patient. Exact diagnosis was difficult, as the patient was asymptomatic and pulmonary embolism is commonly unilateral in tumour patients and not typical for thyroid cancer. External pulmonary artery compression by aortic aneurysm, multiple metastases or additional bronchopulmonary malignancies were considered as differential diagnosis. After unilateral pulmonary and hilar metastasectomy, perfusion normalised on the operated side. Pulmonary perfusion defects due to pulmonary artery compression by hilar metastases were finally diagnosed. Pulmonary embolism was deemed unlikely due to the left-sided post-operative normalisation, persistence of right-sided V/P mismatches, and the lack of clinical symptoms.

Conclusion: Pulmonary artery compression may mimic pulmonary artery embolism in lung perfusion scintigraphy and should be considered in bronchopulmonary tumour patients with hilar metastases and unilateral ventilation/perfusion mismatches affecting a complete lobe or even lung. Following the presented case, also bilateral segmental and subsegmental mismatches in patients with hilar metastases from non-bronchopulmonary cancer entities should be carefully evaluated.
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http://dx.doi.org/10.1186/s41824-021-00120-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8685190PMC
December 2021

Imaging the Inflammatory Response in Checkpoint Inhibition Myocarditis.

J Nucl Med 2022 01 2;63(1):14-16. Epub 2021 Dec 2.

Department of Cardiology and Vascular Medicine, West German Heart and Vascular Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany; and.

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http://dx.doi.org/10.2967/jnumed.121.262301DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8717203PMC
January 2022

Prospective comparison of CT and 18F-FDG PET/MRI in N and M staging of primary breast cancer patients: Initial results.

PLoS One 2021 2;16(12):e0260804. Epub 2021 Dec 2.

Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, Dusseldorf, Germany.

Objectives: To compare the diagnostic accuracy of contrast-enhanced thoraco-abdominal computed tomography and whole-body 18F-FDG PET/MRI in N and M staging in newly diagnosed, histopathological proven breast cancer.

Material And Methods: A total of 80 consecutive women with newly diagnosed and histopathologically confirmed breast cancer were enrolled in this prospective study. Following inclusion criteria had to be fulfilled: (1) newly diagnosed, treatment-naive T2-tumor or higher T-stage or (2) newly diagnosed, treatment-naive triple-negative tumor of every size or (3) newly diagnosed, treatment-naive tumor with molecular high risk (T1c, Ki67 >14%, HER2neu over-expression, G3). All patients underwent a thoraco-abdominal ceCT and a whole-body 18F-FDG PET/MRI. All datasets were evaluated by two experienced radiologists in hybrid imaging regarding suspect lesion count, localization, categorization and diagnostic confidence. Images were interpreted in random order with a reading gap of at least 4 weeks to avoid recognition bias. Histopathological results as well as follow-up imaging served as reference standard. Differences in staging accuracy were assessed using Mc Nemars chi2 test.

Results: CT rated the N stage correctly in 64 of 80 (80%, 95% CI:70.0-87.3) patients with a sensitivity of 61.5% (CI:45.9-75.1), a specificity of 97.6% (CI:87.4-99.6), a PPV of 96% (CI:80.5-99.3), and a NPV of 72.7% (CI:59.8-82.7). Compared to this, 18F-FDG PET/MRI determined the N stage correctly in 71 of 80 (88.75%, CI:80.0-94.0) patients with a sensitivity of 82.1% (CI:67.3-91.0), a specificity of 95.1% (CI:83.9-98.7), a PPV of 94.1% (CI:80.9-98.4) and a NPV of 84.8% (CI:71.8-92.4). Differences in sensitivities were statistically significant (difference 20.6%, CI:-0.02-40.9; p = 0.008). Distant metastases were present in 7/80 patients (8.75%). 18 F-FDG PET/MRI detected all of the histopathological proven metastases without any false-positive findings, while 3 patients with bone metastases were missed in CT (sensitivity 57.1%, specificity 95.9%). Additionally, CT presented false-positive findings in 3 patients.

Conclusion: 18F-FDG PET/MRI has a high diagnostic potential and outperforms CT in assessing the N and M stage in patients with primary breast cancer.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0260804PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8638872PMC
January 2022

CAD-based hardware attenuation correction in PET/MRI: First methodical investigations and clinical application of a 16-channel RF breast coil.

Med Phys 2021 Nov 27;48(11):6696-6709. Epub 2021 Oct 27.

High-Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.

Purpose: Aim of this study was to evaluate the use of computer-aided design (CAD) models for attenuation correction (AC) of hardware components in positron emission tomography/magnetic resonance (PET/MR) imaging.

Methods: The technical feasibility and quantitative impact of CAD-AC compared to computer tomography (CT)-based AC (reference) was investigated on a modular phantom consisting of 19 different material samples (plastics and metals arranged around a cylindrical emission phantom) typically used in phantoms, patient tables, and radiofrequency (RF) coils in PET/MR. The clinical applicability of the CAD-AC method was then evaluated on a 16-channel RF breast coil in a PET/MR patient study. The RF breast coil in this study was specifically designed PET compatible. Using this RF breast coil, the impact on clinical PET/MR breast imaging was systematically evaluated in breast phantom measurements and, furthermore, in n = 10 PET/MR patients with breast cancer. PET data were reconstructed three times: (1) no AC (NAC), (2) established CT-AC, and (3) CAD-AC. For both phantom measurements, a scan without attenuating hardware components (material probes or RF breast coil) was acquired serving as reference. Relative differences in PET data were calculated for all experiments.

Results: In all phantom and patient measurements, significant gains in PET signal compared to NAC data were measurable with CT and CAD-AC. In initial phantom experiments, mean relative differences of -0.2% for CT-AC and 0.2% for CAD-AC were calculated compared to reference measurements without the material probes. The application to a RF breast coil depicts that CAD-AC results in significant gains compared to NAC data (10%) and a slight underestimation in PET signal of -1.3% in comparison to the no-coil reference measurement. In the patient study, a total of 15 congruent lesions in all 10 patients with a mean relative difference of 14% (CT and CAD-AC) in standardized uptake value compared to NAC data could be detected.

Conclusions: To ensure best possible PET image quality and accurate PET quantification in PET/MR imaging, the AC of hardware components such as phantoms and RF coils is important. In initial phantom experiments and in clinical application to an RF breast coil, it was found that CAD-based AC results in significant gains in PET signal compared to NAC data and provides comparably good results to the established method of CT-based AC.
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http://dx.doi.org/10.1002/mp.15284DOI Listing
November 2021

Pitfalls and Common Findings in Ga-FAPI PET: A Pictorial Analysis.

J Nucl Med 2022 06 7;63(6):890-896. Epub 2021 Oct 7.

Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.

Fibroblast activation protein inhibitor (FAPI) PET/CT is a new tool in the diagnostic workup of cancer. With a growing volume of applications, pitfalls and common findings need to be considered for Ga-FAPI PET/CT image interpretation. The aim of this study was to summarize common findings and report pitfalls in Ga-FAPI PET/CT. Ninety-one patients underwent whole-body PET/CT with either FAPI-04 ( = 25) or FAPI-46 ( = 66). Findings were rated in a consensus session of 2 experienced readers. Pitfalls and common findings were defined as focal or localized uptake above the background level and categorized as unspecific or nonmalignant and grouped into degenerative, muscular, scarring/wound-healing, uterine, mammary gland, and head-and-neck findings. The frequency of findings was reported on a per-patient and per-group basis, and SUV, SUV, and SUV were measured. Non-tumor-specific uptake was found in 81.3% of patients. The most frequent finding was uptake in degenerative lesions (51.6%), with a mean SUV of 7.7 ± 2.9, and head-and-neck findings (45.1%). Except for the salivary glands, the uptake values did not differ between 10 and 60 min after injection in most findings. Uterine uptake was found in most women (66.7%), with a mean SUV of 12.2 ± 7.3, and uptake correlated negatively with age (SUV, = -0.6, < 0.01; SUV, = -0.57, < 0.01; SUV, = -0.58, < 0.01). Pitfalls include non-tumor-specific Ga-FAPI uptake in degenerative lesions, muscle, the head and neck, scarring, the mammary glands, or the uterus. Here, we summarize the findings to help readers avoid common mistakes at centers introducing Ga-FAPI PET/CT.
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http://dx.doi.org/10.2967/jnumed.121.262808DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9157730PMC
June 2022

Generating Virtual Short Tau Inversion Recovery (STIR) Images from T1- and T2-Weighted Images Using a Conditional Generative Adversarial Network in Spine Imaging.

Diagnostics (Basel) 2021 Aug 25;11(9). Epub 2021 Aug 25.

Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, 45147 Essen, Germany.

Short tau inversion recovery (STIR) sequences are frequently used in magnetic resonance imaging (MRI) of the spine. However, STIR sequences require a significant amount of scanning time. The purpose of the present study was to generate virtual STIR (vSTIR) images from non-contrast, non-fat-suppressed T1- and T2-weighted images using a conditional generative adversarial network (cGAN). The training dataset comprised 612 studies from 514 patients, and the validation dataset comprised 141 studies from 133 patients. For validation, 100 original STIR and respective vSTIR series were presented to six senior radiologists (blinded for the STIR type) in independent A/B-testing sessions. Additionally, for 141 real or vSTIR sequences, the testers were required to produce a structured report of 15 different findings. In the A/B-test, most testers could not reliably identify the real STIR (mean error of tester 1-6: 41%; 44%; 58%; 48%; 39%; 45%). In the evaluation of the structured reports, vSTIR was equivalent to real STIR in 13 of 15 categories. In the category of the number of STIR hyperintense vertebral bodies ( = 0.08) and in the diagnosis of bone metastases ( = 0.055), the vSTIR was only slightly insignificantly equivalent. By virtually generating STIR images of diagnostic quality from T1- and T2-weighted images using a cGAN, one can shorten examination times and increase throughput.
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http://dx.doi.org/10.3390/diagnostics11091542DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8467788PMC
August 2021

Diagnostic Performance of I-Metaiodobenzylguanidine PET/CT in Patients with Pheochromocytoma.

J Nucl Med 2022 06 23;63(6):869-874. Epub 2021 Sep 23.

Department of Nuclear Medicine, University Hospital Essen, Essen, Germany.

I-metaiodobenzylguanidine (MIBG) scintigraphy has shown a high specificity for imaging pheochromocytoma and paraganglioma, but with low sensitivity because of low spatial resolution. I-MIBG PET may be able to overcome this limitation and improve the staging of patients with (suspected) pheochromocytoma. We analyzed the sensitivity, specificity, and positive and negative predictive values of I-MIBG PET in 43 consecutive patients with suspected (recurrence of) pheochromocytoma using histopathologic ( = 25) and clinical validation ( = 18) as the standard of truth. Furthermore, we compared the detection rate of I-MIBG PET versus contrast-enhanced (CE) CT on a per-patient and per-lesion basis in 13 additional patients with known metastatic malignant pheochromocytoma. I-MIBG PET/CT was positive in 19 (44%) of 43 patients with suspected pheochromocytoma. The presence of pheochromocytoma was confirmed in 22 (51%) of 43. I-MIBG PET/CT sensitivity, specificity, and positive and negative predictive values were 86%, 100%, 100%, and 88%, respectively. I-MIBG PET was positive in 11 (85%) of 13 patients with malignant pheochromocytoma. Combined I-MIBG PET and CE CT detected 173 lesions, of which 166 (96%) and 118 (68%) were visible on I-MIBG PET and CE CT, respectively. I-MIBG PET detects pheochromocytoma with high accuracy at initial staging and a high detection rate at restaging. Future assessment of I-MIBG PET for treatment guidance, including personalized I-MIBG therapy, is warranted.
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http://dx.doi.org/10.2967/jnumed.121.262797DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9157725PMC
June 2022

What about the others: differential diagnosis of COVID-19 in a German emergency department.

BMC Infect Dis 2021 Sep 17;21(1):969. Epub 2021 Sep 17.

Center of Emergency Medicine, University Hospital Essen, Hufelandstrasse 55, 45147, Essen, Germany.

Background: The ongoing COVID-19 pandemic remains a major challenge for worldwide health care systems and in particular emergency medicine. An early and safe triage in the emergency department (ED) is especially crucial for proper therapy. Clinical symptoms of COVID-19 comprise those of many common diseases; thus, differential diagnosis remains challenging.

Method: We performed a retrospective study of 314 ED patients presenting with conceivable COVID-19 symptoms during the first wave in Germany. All were tested for COVID-19 with SARS-Cov-2-nasopharyngeal swabs. Forty-seven patients were positive. We analyzed the 267 COVID-19 negative patients for their main diagnosis and compared COVID-19 patients with COVID-19 negative respiratory infections for differences in laboratory parameters, symptoms, and vital signs.

Results: Among the 267 COVID-19 negative patients, 42.7% had respiratory, 14.2% had other infectious, and 11.2% had cardiovascular diseases. Further, 9.0% and 6.7% had oncological and gastroenterological diagnoses, respectively. Compared to COVID-19 negative airway infections, COVID-19 patients showed less dyspnea (OR 0.440; p = 0.024) but more dysgeusia (OR 7.631; p = 0.005). Their hospital stay was significantly longer (9.0 vs. 5.6 days; p = 0.014), and their mortality significantly higher (OR 3.979; p = 0.014).

Conclusion: For many common ED diagnoses, COVID-19 should be considered a differential diagnosis. COVID-19 cannot be distinguished from COVID-19 negative respiratory infections by clinical signs, symptoms, or laboratory results. When hospitalization is necessary, the clinical course of COVID-19 airway infections seems to be more severe compared to other respiratory infections.

Trial Registration: German Clinical Trial Registry DRKS, DRKS-ID of the study: DRKS00021675 date of registration: May 8th, 2020, retrospectively registered.
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http://dx.doi.org/10.1186/s12879-021-06663-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8446739PMC
September 2021

Patterns of nodal spread in stage III NSCLC: importance of EBUS-TBNA and F-FDG PET/CT for radiotherapy target volume definition.

Radiat Oncol 2021 Sep 15;16(1):176. Epub 2021 Sep 15.

Department of Radiation Therapy, University Hospital Essen, West German Cancer Center, University Duisburg-Essen, Essen, Germany.

Purpose: The aim of this study was to compare the pattern of intra-patient spread of lymph-node (LN)-metastases within the mediastinum as assessed by F-FDG PET/CT and systematic endobronchial ultrasound-guided transbronchial-needle aspiration (EBUS-TBNA) for precise target volume definition in stage III NSCLC.

Methods: This is a single-center study based on our preceding investigation, including all consecutive patients with initial diagnosis of stage IIIA-C NSCLC, receiving concurrent radiochemotherapy (12/2011-06/2018). Inclusion criteria were curative treatment intent, F-FDG PET/CT and EBUS-TBNA prior to start of treatment. The lymphatic drainage was classified into echelon-1 (ipsilateral hilum), echelon-2 (ipsilateral LN-stations 4 and 7) and echelon-3 (rest of the mediastinum, contralateral hilum). The pattern of spread was classified according to all permutations of echelon-1, echelon-2, and echelon-3 EBUS-TBNA findings.

Results: In total, 180 patients were enrolled. Various patterns of LN-spread could be identified. Skip lesions with an involved echelon distal from an uninvolved one were detected in less than 10% of patients by both EBUS-TBNA and PET. The pattern with largest asymmetry was detected in cases with EBUS-TBNA- or PET-positivity at all three echelons (p < 0.0001, exact symmetry test). In a multivariable logistic model for EBUS-positivity at echelon-3, prognostic factors were PET-positivity at echelon-3 (Hazard ratio (HR) = 12.1; 95%-CI: 3.2-46.5), EBUS-TBNA positivity at echelon-2 (HR = 6.7; 95%-CI: 1.31-31.2) and left-sided tumor location (HR = 4.0; 95%-CI: 1.24-13.2). There were significantly less combined ipsilateral upper (LN-stations 2 and 4) and lower (LN-station 7) mediastinal involvements (16.8% of patients) with EBUS-TBNA than with PET (38.9%, p < 0.0001, exact symmetry test). EBUS-TBNA detected a lobe specific heterogeneity between the odds ratios of LN-positivity in the upper versus lower mediastinum (p = 0.0021, Breslow-Day test), while PET did not (p = 0.19).

Conclusion: Frequent patterns of LN-metastatic spread could be defined by EBUS-TBNA and PET and discrepancies in the pattern were seen between both methods. EBUS-TBNA showed more lobe and tumor laterality specific patterns of LN-metastases than PET and skipped lymph node stations were rare. These systematic relations offer the opportunity to further refine multi-parameter risk of LN-involvement models for target volume delineation based on pattern of spread by EBUS-TBNA and PET.
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http://dx.doi.org/10.1186/s13014-021-01904-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8442338PMC
September 2021
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