Publications by authors named "Baiyu Chen"

45 Publications

Calcium channelopathies and intellectual disability: a systematic review.

Orphanet J Rare Dis 2021 May 13;16(1):219. Epub 2021 May 13.

Department of Pediatrics, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.

Background: Calcium ions are involved in several human cellular processes including corticogenesis, transcription, and synaptogenesis. Nevertheless, the relationship between calcium channelopathies (CCs) and intellectual disability (ID)/global developmental delay (GDD) has been poorly investigated. We hypothesised that CCs play a major role in the development of ID/GDD and that both gain- and loss-of-function variants of calcium channel genes can induce ID/GDD. As a result, we performed a systematic review to investigate the contribution of CCs, potential mechanisms underlying their involvement in ID/GDD, advancements in cell and animal models, treatments, brain anomalies in patients with CCs, and the existing gaps in the knowledge. We performed a systematic search in PubMed, Embase, ClinVar, OMIM, ClinGen, Gene Reviews, DECIPHER and LOVD databases to search for articles/records published before March 2021. The following search strategies were employed: ID and calcium channel, mental retardation and calcium channel, GDD and calcium channel, developmental delay and calcium channel.

Main Body: A total of 59 reports describing 159 cases were found in PubMed, Embase, ClinVar, and LOVD databases. Variations in ten calcium channel genes including CACNA1A, CACNA1C, CACNA1I, CACNA1H, CACNA1D, CACNA2D1, CACNA2D2, CACNA1E, CACNA1F, and CACNA1G were found to be associated with ID/GDD. Most variants exhibited gain-of-function effect. Severe to profound ID/GDD was observed more for the cases with gain-of-function variants as compared to those with loss-of-function. CACNA1E, CACNA1G, CACNA1F, CACNA2D2 and CACNA1A associated with more severe phenotype. Furthermore, 157 copy number variations (CNVs) spanning calcium genes were identified in DECIPHER database. The leading genes included CACNA1C, CACNA1A, and CACNA1E. Overall, the underlying mechanisms included gain- and/ or loss-of-function, alteration in kinetics (activation, inactivation) and dominant-negative effects of truncated forms of alpha1 subunits. Forty of the identified cases featured cerebellar atrophy. We identified only a few cell and animal studies that focused on the mechanisms of ID/GDD in relation to CCs. There is a scarcity of studies on treatment options for ID/GDD both in vivo and in vitro.

Conclusion: Our results suggest that CCs play a major role in ID/GDD. While both gain- and loss-of-function variants are associated with ID/GDD, the mechanisms underlying their involvement need further scrutiny.
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http://dx.doi.org/10.1186/s13023-021-01850-0DOI Listing
May 2021

Cardiofaciocutaneous syndrome with BRAF gene mutation: A case report and literature review.

Zhong Nan Da Xue Xue Bao Yi Xue Ban 2021 Apr;46(4):432-437

Department of Pediatrics, Xiangya Hospital, Central South University; Research Center of Children Intellectual Disability of Hunan Province, Changsha 410008, China.

Cardio-facio-cutaneous (CFC) syndrome is an extremely rare autosomal dominant genetic disease due to BRAF and other gene mutations. The main characteristics of the patients are craniofacial deformities, cardiac malformations, skin abnormalities, delay of language and motor development, gastrointestinal dysfunction, intellectual disability, and epilepsy. In this case, the child has a typical CFC syndrome face and developmental delay. The gene results of the second-generation sequencing technology showed that there was a mutation site c.1741A>G (p. Asn581Asp) (heterozygous) in exon 14 of the BRAF (NM_004333.5) gene. The mutation was not observed in the child's parents. The above-mentioned mutation may be a de novo mutation. There is no effective therapy for this disease so far.
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http://dx.doi.org/10.11817/j.issn.1672-7347.2021.190756DOI Listing
April 2021

De novo variants of DEAF1 cause intellectual disability in six Chinese patients.

Clin Chim Acta 2021 Mar 9;518:17-21. Epub 2021 Mar 9.

Department of Pediatrics, Xiangya Hospital of Central South University, Changsha, China; Hunan Intellectual and Developmental Disabilities Research Center, Changsha, China. Electronic address:

Background: It has been reported that de novo heterozygous variants of DEAF1 can cause DEAF1-associated neurodevelopmental disorder. The purpose of this article is to explore the clinical and genetic characteristics of Chinese patients harboring de novo DEAF1 variants.

Methods: We assembled a cohort of six unrelated patients with de novo variants in DEAF1. Clinical and genetic features of these patients were summarized.

Results: Each child showed intellectual disability (ID)/ global developmental delay (GDD). Severe language impairment was prominent. Behavior problems, seizures, sleep disturbance, and a high pain threshold were common features. DEAF1-related seizures were reported to be difficult to treat or intractable. Seizures in our cohort were almost all treatable. Valproic acid was the most commonly used drug. Five heterozygous missense mutations of DEAF1 gene were identified, three of which (p.W234C, p.L203P, p.H275Q) were not published in literature before.

Conclusion: Mutations of DEAF1 gene should be considered in ID/GDD patients with a nonspecific phenotype, comprising intellectual disability, prominent speech delay, abnormal behaviors, especially autism. In our study, DEAF1-related epilepsy is completely treatable in Eastern-Asian individuals when compared to patients in other regions, and valproic acid can be used as a first choice. The knowledge of DEAF1-related neurodevelopmental disorder and the de novo variant database of DEAF1 were expanded.
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http://dx.doi.org/10.1016/j.cca.2021.02.026DOI Listing
March 2021

Low-dose CT image and projection dataset.

Med Phys 2021 Feb 16;48(2):902-911. Epub 2020 Dec 16.

Department of Radiology, Mayo Clinic, Rochester, MN, USA.

Purpose: To describe a large, publicly available dataset comprising computed tomography (CT) projection data from patient exams, both at routine clinical doses and simulated lower doses.

Acquisition And Validation Methods: The library was developed under local ethics committee approval. Projection and image data from 299 clinically performed patient CT exams were archived for three types of clinical exams: noncontrast head CT scans acquired for acute cognitive or motor deficit, low-dose noncontrast chest scans acquired to screen high-risk patients for pulmonary nodules, and contrast-enhanced CT scans of the abdomen acquired to look for metastatic liver lesions. Scans were performed on CT systems from two different CT manufacturers using routine clinical protocols. Projection data were validated by reconstructing the data using several different reconstruction algorithms and through use of the data in the 2016 Low Dose CT Grand Challenge. Reduced dose projection data were simulated for each scan using a validated noise-insertion method. Radiologists marked location and diagnosis for detected pathologies. Reference truth was obtained from the patient medical record, either from histology or subsequent imaging.

Data Format And Usage Notes: Projection datasets were converted into the previously developed DICOM-CT-PD format, which is an extended DICOM format created to store CT projections and acquisition geometry in a nonproprietary format. Image data are stored in the standard DICOM image format and clinical data in a spreadsheet. Materials are provided to help investigators use the DICOM-CT-PD files, including a dictionary file, data reader, and user manual. The library is publicly available from The Cancer Imaging Archive (https://doi.org/10.7937/9npb-2637).

Potential Applications: This CT data library will facilitate the development and validation of new CT reconstruction and/or denoising algorithms, including those associated with machine learning or artificial intelligence. The provided clinical information allows evaluation of task-based diagnostic performance.
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http://dx.doi.org/10.1002/mp.14594DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985836PMC
February 2021

The Recommendations for the Management of Chinese Children With Epilepsy During the COVID-19 Outbreak.

Front Pediatr 2020 25;8:495. Epub 2020 Aug 25.

Department of Pediatrics, Xiangya Hospital, Central South University, Changsha, China.

The coronavirus disease (COVID-19) is the most severe public health problem facing the world currently. Social distancing and avoidance of unnecessary movements are preventive strategies that are being advocated to prevent the spread of the causative virus [severe acute respiratory syndrome (SARS)-CoV2]. It is known that epileptic children need long term treatments (antiepileptic drugs and/or immunosuppressive agents) as well as close follow up due to the nature of the disease. In addition, it is clear that epilepsy can concur with other chronic illnesses which can lower body immunity. As a result, epileptic children have high risk of acquiring this novel disease due to weak/immature immune system. Of concern, the management of children with epilepsy has become more challenging during this outbreak due to the prevention measures that are being taken. Although children with controlled seizures can be managed at home, it is challenging for pediatricians when it comes to cases with uncontrolled seizures/severe cases. To this end, we provide recommendations for the management of epileptic children at home, outpatient and inpatient settings.
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http://dx.doi.org/10.3389/fped.2020.00495DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7477110PMC
August 2020

Intellectual Disability and Potassium Channelopathies: A Systematic Review.

Front Genet 2020 23;11:614. Epub 2020 Jun 23.

Department of Pediatrics, Xiangya Hospital, Central South University, Changsha, China.

Intellectual disability (ID) manifests prior to adulthood as severe limitations to intellectual function and adaptive behavior. The role of potassium channelopathies in ID is poorly understood. Therefore, we aimed to evaluate the relationship between ID and potassium channelopathies. We hypothesized that potassium channelopathies are strongly associated with ID initiation, and that both gain- and loss-of-function mutations lead to ID. This systematic review explores the burden of potassium channelopathies, possible mechanisms, advancements using animal models, therapies, and existing gaps. The literature search encompassed both PubMed and Embase up to October 2019. A total of 75 articles describing 338 cases were included in this review. Nineteen channelopathies were identified, affecting the following genes: , and . Twelve of these genes presented both gain- and loss-of-function properties, three displayed gain-of-function only, three exhibited loss-of-function only, and one had unknown function. How gain- and loss-of-function mutations can both lead to ID remains largely unknown. We identified only a few animal studies that focused on the mechanisms of ID in relation to potassium channelopathies and some of the few available therapeutic options (channel openers or blockers) appear to offer limited efficacy. In conclusion, potassium channelopathies contribute to the initiation of ID in several instances and this review provides a comprehensive overview of which molecular players are involved in some of the most prominent disease phenotypes.
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http://dx.doi.org/10.3389/fgene.2020.00614DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7324798PMC
June 2020

MiR-29b-3p cooperates with miR-29c-3p to affect the malignant biological behaviors in T-cell acute lymphoblastic leukemia via TFAP2C/GPX1 axis.

Biochem Biophys Res Commun 2020 06 15;527(2):511-517. Epub 2020 May 15.

Department of Pediatrics, The Affiliated Hospital of Inner Mongolia Medical University, NO.1 Gangdao Street, Huimin District, Hohhot, 010050, Inner Mongolia, China. Electronic address:

Mounting evidence has illustrated the tumor regulatory roles of microRNAs (miRNAs) in T-cell acute lymphoblastic leukemia (T-ALL), a malignant carcinoma originated from T-cell precursors. However, the possible regulation mechanisms underlying miR-29b/29c-3p in T-ALL have not been interrogated yet. The aim of our study was to probe the association and possible molecular mechanism of miR-29b/29c-3p and Glutathione Peroxidase 1 (GPX1), a predicted highly expressed gene in acute myeloid leukemia (LAML) tissues on the cancer genome atlas (TCGA) website. In our paper, it was observed that GPX1 was relatively overexpressed in T-ALL cells, compared with normal T cells. Loss-of-function assays demonstrated that GPX1 knockdown inhibited the proliferation and activated the apoptosis in T-ALL cells. Then miR-29b/29c-3p was confirmed to regulate GPX1 mRNA and protein expression via decreasing Transcription Factor AP-2 Gamma (TFAP2C) expression. In summary, miR-29b-3p and miR-29c-3p targeted TFAP2C so as to repress GPX1 transcription, thereafter inhibiting GPXA expression. In the end, rescue experiments proved the whole regulation mechanism of miR-29b/29c-3p in T-ALL. Overall, the miR-29b/29c-3p -TFAP2C-GPX1 axis helped us to have a better understanding of T-ALL pathogenesis.
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http://dx.doi.org/10.1016/j.bbrc.2020.03.170DOI Listing
June 2020

Image reconstruction for interrupted-beam x-ray CT on diagnostic clinical scanners.

Phys Med Biol 2019 08 7;64(15):155007. Epub 2019 Aug 7.

New York University School of Medicine, New York, NY, United States of America.

Low-dose x-ray CT is a major research area with high clinical impact. Compressed sensing using view-based sparse sampling and sparsity-promoting regularization has shown promise in simulations, but these methods can be difficult to implement on diagnostic clinical CT scanners since the x-ray beam cannot be switched on and off rapidly enough. An alternative to view-based sparse sampling is interrupted-beam sparse sampling. SparseCT is a recently-proposed interrupted-beam scheme that achieves sparse sampling by blocking a portion of the beam using a multislit collimator (MSC). The use of an MSC necessitates a number of modifications to the standard compressed sensing reconstruction pipeline. In particular, we find that SparseCT reconstruction is feasible within a model-based image reconstruction framework that incorporates data fidelity weighting to consider penumbra effects and source jittering to consider the effect of partial source obstruction. Here, we present these modifications and demonstrate their application in simulations and real-world prototype scans. In simulations compared to conventional low-dose acquisitions, SparseCT is able to achieve smaller normalized root-mean square differences and higher structural similarity measures on two reduction factors. In prototype experiments, we successfully apply our reconstruction modifications and maintain image resolution at quarter-dose reduction level. The SparseCT design requires only small hardware modifications to current diagnostic clinical scanners, opening up new possibilities for CT dose reduction.
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http://dx.doi.org/10.1088/1361-6560/ab2df1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927037PMC
August 2019

Localization of liver lesions in abdominal CT imaging: II. Mathematical model observer performance correlates with human observer performance for localization of liver lesions in abdominal CT imaging.

Phys Med Biol 2019 05 10;64(10):105012. Epub 2019 May 10.

Department of Radiology, Mayo Clinic, Rochester, MN, United States of America.

Determination of the effect of protocol modifications on diagnostic performance in CT with human observers is extremely time-consuming, limiting the applicability of such methods in routine clinical practice. In this work, we sought to determine whether a channelized Hotelling observer (CHO) could predict human observer performance for the task of liver lesion localization as background, reconstruction algorithm, dose, and lesion size were varied. Liver lesions (5 mm, 7 mm, and 9 mm) were digitally inserted into the CT projection data of patients with normal livers and water phantoms. The projection data were reconstructed with filtered back projection (FBP) and iterative reconstruction (IR) algorithms for three dose levels: full dose (liver CTDIvol  =  10.5  ±  8.5 mGy, water phantom CTDIvol  =  9.6  ±  0.1 mGy) and simulated half and quarter doses. For each of 36 datasets (3 dose levels  ×  2 reconstruction algorithms  ×  2 backgrounds  ×  3 sizes), 66 signal-present and 34 signal-absent 2D images were extracted from the reconstructed volumes. Three medical physicists independently reviewed each dataset and noted the lesion location and a confidence score for each image. A CHO with Gabor channels was calculated to estimate the performance for each of the 36 localization tasks. The CHO performances, quantified using localization receiver operating characteristic (LROC) analysis, were compared to the human observer performances. Performance values between human and model observers were highly correlated for equivalent parameters (same lesion size, dose, background, and reconstruction), with a Spearman's correlation coefficient of 0.93 (95% CI: 0.82-0.98). CHO performance values for the uniform background were strongly correlated (ρ  =  0.94, CI: 0.80-1.0) with the human observer performance values for the liver background. Performance values between human observers and CHO were highly correlated as dose, reconstruction type and object size were varied for the task of localization of patient liver lesions in both uniform and liver backgrounds.
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http://dx.doi.org/10.1088/1361-6560/ab1a62DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598689PMC
May 2019

Localization of liver lesions in abdominal CT imaging: I. Correlation of human observer performance between anatomical and uniform backgrounds.

Phys Med Biol 2019 05 10;64(10):105011. Epub 2019 May 10.

Department of Radiology, Mayo Clinic, Rochester, MN, United States of America.

The purpose of this study was to determine the correlation between human observer performance for localization of small low contrast lesions within uniform water background versus an anatomical liver background, under the conditions of varying dose, lesion size, and reconstruction algorithm. Liver lesions (5 mm, 7 mm, and 9 mm, contrast:  -21 HU) were digitally inserted into CT projection data of ten normal patients in vessel-free liver regions. Noise was inserted into the projection data to create three image sets: full dose and simulated half and quarter doses. Images were reconstructed with a standard filtered back projection (FBP) and an iterative reconstruction (IR) algorithm. Lesion and noise insertion procedures were repeated with water phantom data. Two-dimensional regions of interest (66 lesion-present, 34 lesion-absent) were selected, randomized, and independently reviewed by three medical physicists to identify the most likely location of the lesion and provide a confidence score. Locations and confidence scores were assessed using the area under the localization receiver operating characteristic curve (Az). We examined the correlation between human performance for the liver and uniform water backgrounds as dose, lesion size, and reconstruction algorithm varied. As lesion size or dose increased, reader localization performance improved. For full dose IR images, the Az for 5, 7, and 9 mm lesions were 0.53, 0.91, and 0.97 (liver) and 0.51, 0.96, and 0.99 (uniform water), respectively. Similar trends were seen with other parameters. Performance values for liver and uniform backgrounds were highly correlated for both reconstruction algorithms, with a Spearman correlation of ρ  =  0.97, and an average difference in Az of 0.05  ±  0.04. For the task of localizing low contrast liver lesions, human observer performance was highly correlated between anatomical and uniform backgrounds, suggesting that lesion localization studies emulating a clinical test of liver lesion detection can be performed using a uniform background.
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http://dx.doi.org/10.1088/1361-6560/ab1a45DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598706PMC
May 2019

SparseCT: System concept and design of multislit collimators.

Med Phys 2019 Jun 6;46(6):2589-2599. Epub 2019 May 6.

Department of Radiology, NYU School of Medicine, New York, NY, 10016, USA.

Purpose: SparseCT, an undersampling scheme for compressed sensing (CS) computed tomography (CT), has been proposed to reduce radiation dose by acquiring undersampled projection data from clinical CT scanners (Koesters et al. in, SparseCT: Interrupted-Beam Acquisition and Sparse Reconstruction for Radiation Dose Reduction; 2017). SparseCT partially blocks the x-ray beam with a multislit collimator (MSC) to perform a multidimensional undersampling along the view and detector row dimensions. SparseCT undersamples the projection data within each view and moves the MSC along the z-direction during gantry rotation to change the undersampling pattern. It enables reconstruction of images from undersampled data using CS algorithms. The purpose of this work is to design the spacing and width of the MSC slits and the MSC motion patterns based on beam separation, undersampling efficiency, and image quality. The development and testing of a SparseCT prototype with the designed MSC will be described in a following paper.

Methods: We chose a few initial MSC designs based on the guidance from two metrics: beam separation and undersampling efficiency. Both beam separation and undersampling efficiency were measured from numerically simulated photon distribution with MSC taken into consideration. Beam separation measures the separation between x-ray beams from consecutive slits, taking into account penumbra effects on both sides of each slit. Undersampling efficiency measures the dose-weighted similarity between penumbra undersampling and binary undersampling, in other words, the effective contribution of the incident dose to the signal to noise ratio of the projection data. We then compared the initially chosen MSC designs in terms of their reconstruction image quality. SparseCT projections were simulated from fully sampled patient projection data according to the MSC design and motion pattern, reconstructed iteratively using a sparsity-enforcing penalized weighted least squares cost function with ordered subsets/momentum algorithm, and compared visually and quantitatively.

Results: Simulated photon distributions indicate that the size of the penumbra is dominated by the size of the focal spot. Therefore, a wider MSC slit and a smaller focal spot lead to increased beam separation and undersampling efficiency. For fourfold undersampling with a 1.2 mm focal spot, a minimum MSC slit width of three detector rows (projected to the detector surface) is needed for beam separation; for threefold undersampling, a minimum slit width of four detector rows is needed. Simulations of SparseCT projection and reconstruction indicate that the motion pattern of the MSC does not have a visible impact on image quality. An MSC slit width of three or four detector rows yields similar image quality.

Conclusion: The MSC is the key component of the SparseCT method. Simulations of MSC designs incorporating x-ray beam penumbra effects showed that for threefold and fourfold dose reductions, an MSC slit width of four detector rows provided reasonable beam separation, undersampling efficiency, and image quality.
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http://dx.doi.org/10.1002/mp.13544DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6561820PMC
June 2019

Double Entropy Joint Distribution Function and Its Application in Calculation of Design Wave Height.

Entropy (Basel) 2019 Jan 14;21(1). Epub 2019 Jan 14.

School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA.

Wave height and wave period are important oceanic environmental factors that are used to describe the randomness of a wave. Within the field of ocean engineering, the calculation of design wave height is of great significance. In this paper, a periodic maximum entropy distribution function with four undetermined parameters is derived by means of coordinate transformation and solving conditional variational problems. A double entropy joint distribution function of wave height and wave period is also derived. The function is derived from the maximum entropy wave height function and the maximum entropy periodic function, with the help of structures of the Copula function. The double entropy joint distribution function of wave height and wave period is not limited by weak nonlinearity, nor by normal stochastic process and narrow spectrum. Besides, it can fit the observed data more carefully and be more widely applicable to nonlinear waves in various cases, owing to the many undetermined parameters it contains. The engineering cases show that the recurrence level derived from the double entropy joint distribution function is higher than that from the extreme value distribution using the single variables of wave height or wave period. It is also higher than that from the traditional joint distribution function of wave height and wave period.
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http://dx.doi.org/10.3390/e21010064DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514171PMC
January 2019

A novel mutation of SGSH and clinical features analysis of mucopolysaccharidosis type IIIA.

Medicine (Baltimore) 2018 Dec;97(52):e13758

Department of Gastroenterology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, P.R. China.

Rationale: The aim of this study was to analyze the clinical and imaging features of a pediatric patient with mucopolysaccharidosis type IIIA (MPS IIIA) and a novel mutation of the N-sulfoglucosamine sulfohydrolase (SGSH) in 1 pedigree.

Patient Concerns: An 8-year-old female patient presented with developmental regression, seizures, cerebral atrophy, thickened calvarial diploe, apathy, esotropia, slender build, thick hair, prominent eyebrows, hepatomegaly, ankle clonus, muscle and joint contractures, and funnel chest.

Diagnoses: The patient was diagnosed as autosomal recessive (AR) MPS IIIA with a novel mutation in the SGSH gene.

Interventions: Genomic DNA was extracted from the peripheral blood and next-generation sequencing (NGS) technology was used to detect pathogenic genes, and the Sanger method was applied to perform pedigree verification for the detected suspicious pathogenic mutations.

Outcomes: The NGS done for the girl and her family showed 2 variations that were both missense mutations in SGSH. The c.1298G > A (p.Arg433Gln) was a known mutation, and the c.630 G > T (p.Trp210Cys) was a novel variation.

Lessons: The common clinical manifestations of MPS IIIA were rapid developmental regression, seizures, cerebral atrophy, and thickened calvarial diploe. The results showed that the c.630 G > T was likely pathogenic according to bioinformatics analysis, which probably was a novel mutation. This study reports 1 case of MPS IIIA with some clinical features as determined via clinical and genetic analysis, and found a new mutation in the SGSH gene.
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http://dx.doi.org/10.1097/MD.0000000000013758DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314651PMC
December 2018

Estimability index for volume quantification of homogeneous spherical lesions in computed tomography.

J Med Imaging (Bellingham) 2018 Jul 11;5(3):031404. Epub 2017 Dec 11.

Duke University, Department of Radiology, Durham, North Carolina, United States.

Volume of lung nodules is an important biomarker, quantifiable from computed tomography (CT) images. The usefulness of volume quantification, however, depends on the precision of quantification. Experimental assessment of precision is time consuming. A mathematical estimability model was used to assess the quantification precision of CT nodule volumetry in terms of an index ([Formula: see text]), incorporating image noise and resolution, nodule properties, and segmentation software. The noise and resolution were characterized in terms of noise power spectrum and task transfer function. The nodule properties and segmentation algorithm were modeled in terms of a task function and a template function, respectively. The [Formula: see text] values were benchmarked against experimentally acquired precision values from an anthropomorphic chest phantom across 54 acquisition protocols, 2 nodule sizes, and 2 volume segmentation softwares. [Formula: see text] exhibited correlation with experimental precision across nodule sizes and acquisition protocols but dependence on segmentation software. Compared to the assessment of empirical precision, which required [Formula: see text] to perform the segmentation, the [Formula: see text] method required [Formula: see text] from data collection to mathematical computation. A mathematical modeling of volume quantification provides efficient prediction of quantitative performance. It establishes a method to verify quantitative compliance and to optimize clinical protocols for chest CT volumetry.
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http://dx.doi.org/10.1117/1.JMI.5.3.031404DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5724552PMC
July 2018

XIST promotes gastric cancer (GC) progression through TGF-β1 via targeting miR-185.

J Cell Biochem 2018 03 4;119(3):2787-2796. Epub 2017 Dec 4.

Department of Radiation Oncology, Huai'an First People's Hospital, Nanjing Medical University, Huai'an, China.

LncRNAs and microRNAs can play significant roles in various cancers, including gastric cancer (GC). In our study, we investigated the role of lncRNA XIST in GC. We observed that XIST was increased in MGC803 and BGC823 cells compared to human normal gastric epithelial GES-1 cells. It was also shown that miR-185 was decreased in GC cell lines. Silencing XIST can inhibit the growth of GC cells and bioinformatics analysis was performed to confirm the correlation between XIST and miR-185. Interestingly, a negative correlation was indicated between XIST and miR-185 in GC cells. In addition, TGF-β1 was predicted as a target gene of miR-185. miR-185 can modulate TGF-β1 expression negatively in vitro. Moreover, we found that sh-XIST inhibited GC development via decreasing TGF-β1 by upregulating miR-185 in vitro. Therefore, we speculated that XIST can act as a competing endogenous lncRNA (ceRNA) to regulate TGF-β1 by sponging miR-185 in GC. Taken these together, it was indicated that XIST/miR-185/TGF-β1 axis participated in the development of GC. XIST could act as a potential prognostic biomarker in GC development.
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http://dx.doi.org/10.1002/jcb.26447DOI Listing
March 2018

Low-dose CT for the detection and classification of metastatic liver lesions: Results of the 2016 Low Dose CT Grand Challenge.

Med Phys 2017 Oct;44(10):e339-e352

Department of Radiology, Mayo Clinic, Rochester, MN, 55920, USA.

Purpose: Using common datasets, to estimate and compare the diagnostic performance of image-based denoising techniques or iterative reconstruction algorithms for the task of detecting hepatic metastases.

Methods: Datasets from contrast-enhanced CT scans of the liver were provided to participants in an NIH-, AAPM- and Mayo Clinic-sponsored Low Dose CT Grand Challenge. Training data included full-dose and quarter-dose scans of the ACR CT accreditation phantom and 10 patient examinations; both images and projections were provided in the training data. Projection data were supplied in a vendor-neutral standardized format (DICOM-CT-PD). Twenty quarter-dose patient datasets were provided to each participant for testing the performance of their technique. Images were provided to sites intending to perform denoising in the image domain. Fully preprocessed projection data and statistical noise maps were provided to sites intending to perform iterative reconstruction. Upon return of the denoised or iteratively reconstructed quarter-dose images, randomized, blinded evaluation of the cases was performed using a Latin Square study design by 11 senior radiology residents or fellows, who marked the locations of identified hepatic metastases. Markings were scored against reference locations of clinically or pathologically demonstrated metastases to determine a per-lesion normalized score and a per-case normalized score (a faculty abdominal radiologist established the reference location using clinical and pathological information). Scores increased for correct detections; scores decreased for missed or incorrect detections. The winner for the competition was the entry that produced the highest total score (mean of the per-lesion and per-case normalized score). Reader confidence was used to compute a Jackknife alternative free-response receiver operating characteristic (JAFROC) figure of merit, which was used for breaking ties.

Results: 103 participants from 90 sites and 26 countries registered to participate. Training data were shared with 77 sites that completed the data sharing agreements. Subsequently, 41 sites downloaded the 20 test cases, which included only the 25% dose data (CTDIvol = 3.0 ± 1.8 mGy, SSDE = 3.5 ± 1.3 mGy). 22 sites submitted results for evaluation. One site provided binary images and one site provided images with severe artifacts; cases from these sites were excluded from review and the participants removed from the challenge. The mean (range) per-lesion and per-case normalized scores were -24.2% (-75.8%, 3%) and 47% (10%, 70%), respectively. Compared to reader results for commercially reconstructed quarter-dose images with no noise reduction, 11 of the 20 sites showed a numeric improvement in the mean JAFROC figure of merit. Notably two sites performed comparably to the reader results for full-dose commercial images. The study was not designed for these comparisons, so wide confidence intervals surrounded these figures of merit and the results should be used only to motivate future testing.

Conclusion: Infrastructure and methodology were developed to rapidly estimate observer performance for liver metastasis detection in low-dose CT examinations of the liver after either image-based denoising or iterative reconstruction. The results demonstrated large differences in detection and classification performance between noise reduction methods, although the majority of methods provided some improvement in performance relative to the commercial quarter-dose images with no noise reduction applied.
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http://dx.doi.org/10.1002/mp.12345DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5656004PMC
October 2017

Correlation between a 2D channelized Hotelling observer and human observers in a low-contrast detection task with multislice reading in CT.

Med Phys 2017 Aug 13;44(8):3990-3999. Epub 2017 Jul 13.

Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA.

Purpose: Model observers have been successfully developed and used to assess the quality of static 2D CT images. However, radiologists typically read images by paging through multiple 2D slices (i.e., multislice reading). The purpose of this study was to correlate human and model observer performance in a low-contrast detection task performed using both 2D and multislice reading, and to determine if the 2D model observer still correlate well with human observer performance in multislice reading.

Methods: A phantom containing 18 low-contrast spheres (6 sizes × 3 contrast levels) was scanned on a 192-slice CT scanner at five dose levels (CTDI = 27, 13.5, 6.8, 3.4, and 1.7 mGy), each repeated 100 times. Images were reconstructed using both filtered-backprojection (FBP) and an iterative reconstruction (IR) method (ADMIRE, Siemens). A 3D volume of interest (VOI) around each sphere was extracted and placed side-by-side with a signal-absent VOI to create a 2-alternative forced choice (2AFC) trial. Sixteen 2AFC studies were generated, each with 100 trials, to evaluate the impact of radiation dose, lesion size and contrast, and reconstruction methods on object detection. In total, 1600 trials were presented to both model and human observers. Three medical physicists acted as human observers and were allowed to page through the 3D volumes to make a decision for each 2AFC trial. The human observer performance was compared with the performance of a multislice channelized Hotelling observer (CHO_MS), which integrates multislice image data, and with the performance of previously validated CHO, which operates on static 2D images (CHO_2D). For comparison, the same 16 2AFC studies were also performed in a 2D viewing mode by the human observers and compared with the multislice viewing performance and the two CHO models.

Results: Human observer performance was well correlated with the CHO_2D performance in the 2D viewing mode [Pearson product-moment correlation coefficient R = 0.972, 95% confidence interval (CI): 0.919 to 0.990] and with the CHO_MS performance in the multislice viewing mode (R = 0.952, 95% CI: 0.865 to 0.984). The CHO_2D performance, calculated from the 2D viewing mode, also had a strong correlation with human observer performance in the multislice viewing mode (R = 0.957, 95% CI: 879 to 0.985). Human observer performance varied between the multislice and 2D modes. One reader performed better in the multislice mode (P = 0.013); whereas the other two readers showed no significant difference between the two viewing modes (P = 0.057 and P = 0.38).

Conclusions: A 2D CHO model is highly correlated with human observer performance in detecting spherical low contrast objects in multislice viewing of CT images. This finding provides some evidence for the use of a simpler, 2D CHO to assess image quality in clinically relevant CT tasks where multislice viewing is used.
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http://dx.doi.org/10.1002/mp.12380DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5553707PMC
August 2017

Evaluation of a projection-domain lung nodule insertion technique in thoracic computed tomography.

J Med Imaging (Bellingham) 2017 Jan 31;4(1):013510. Epub 2017 Mar 31.

Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.

Task-based assessment of computed tomography (CT) image quality requires a large number of cases with ground truth. Prospective case acquisition can be time-consuming. Inserting lesions into existing cases to simulate positive cases is a promising alternative. The aim was to evaluate a recently developed projection-based lesion insertion technique in thoracic CT. In total, 32 lung nodules of various attenuations were segmented from 21 patient cases, forward projected, inserted into projections, and reconstructed. Two experienced radiologists and two residents independently evaluated these nodules in two substudies. First, the 32 inserted and the 32 original nodules were presented in a randomized order and each received a score from 1 to 10 (1 = absolutely artificial to 10 = absolutely realistic). Second, the inserted and the corresponding original lesions were presented side-by-side to each reader. For the randomized evaluation, discrimination of real versus inserted nodules was poor with areas under the receiver operative characteristic curves being 0.57 [95% confidence interval (CI): 0.46 to 0.68], 0.69 (95% CI: 0.58 to 0.78), and 0.62 (95% CI: 0.54 to 0.69) for the two residents, two radiologists, and all four readers, respectively. Our projection-based lung nodule insertion technique provides a robust method to artificially generate positive cases that prove to be difficult to differentiate from real cases.
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http://dx.doi.org/10.1117/1.JMI.4.1.013510DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374359PMC
January 2017

A virtual clinical trial using projection-based nodule insertion to determine radiologist reader performance in lung cancer screening CT.

Proc SPIE Int Soc Opt Eng 2017 Feb 9;10132. Epub 2017 Mar 9.

Department of Radiology, Mayo Clinic, Rochester, MN.

Task-based image quality assessment using model observers is promising to provide an efficient, quantitative, and objective approach to CT dose optimization. Before this approach can be reliably used in practice, its correlation with radiologist performance for the same clinical task needs to be established. Determining human observer performance for a well-defined clinical task, however, has always been a challenge due to the tremendous amount of efforts needed to collect a large number of positive cases. To overcome this challenge, we developed an accurate projection-based insertion technique. In this study, we present a virtual clinical trial using this tool and a low-dose simulation tool to determine radiologist performance on lung-nodule detection as a function of radiation dose, nodule type, nodule size, and reconstruction methods. The lesion insertion and low-dose simulation tools together were demonstrated to provide flexibility to generate realistically-appearing clinical cases under well-defined conditions. The reader performance data obtained in this virtual clinical trial can be used as the basis to develop model observers for lung nodule detection, as well as for dose and protocol optimization in lung cancer screening CT.
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http://dx.doi.org/10.1117/12.2255593DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384330PMC
February 2017

Validation study of a new semi-automated software program for CT body composition analysis.

Abdom Radiol (NY) 2017 09;42(9):2369-2375

Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, USA.

Background: Computed tomography (CT) has been increasingly used to quantify abdominal muscle and fat in clinical research studies, and multiple studies have shown importance of body composition in predicting clinical outcome. The purpose of study is to compare newly developed semi-automated software (BodyCompSlicer) to commercially available validated software (Slice-O-Matic) for CT body composition analysis.

Methods: CT scans of abdomen at L3 level in 30 patients were analyzed by two reviewers and using two softwares (BodyCompSlicer and Slice-O-Matic). Body composition analysis using BodyCompSlicer was semi-automated. The program automatically segmented subcutaneous fat (SF), skeletal muscle (SM), and visceral fat (VF) areas. Reviewers manually corrected the segmentation using computer-mouse interface as necessary. Body composition analysis using Slice-O-Matic was performed by manually segmenting each area using computer-mouse interface (brush tool). After segmentation, SM, SF, and VF areas were calculated using CT attenuation thresholds. Inter-observer and inter-software variability of measurements were analyzed using intraclass correlation coefficients (ICC) and coefficient of variation (COV).

Results: Inter-observer ICC and COV using BodyCompSlicer were 0.997 and 1.5% for SM, 1.000 and 0.8% for SF, and 1.000 and 1.0% for VF, whereas those using Slice-O-Matic were 0.993 and 2.5% for SM, 0.995 and 3.1% for SF, and 0.999 and 2.3% for VF. Inter-software ICCs and COV were 0.995-0.995 and 2.0-2.1% for SM, 0.991-0.994 and 3.4-3.9% for SF, and 0.998-0.998 and 2.8-3.3% for VF. Time to analyze 30 cases was 70-100 min and 150-180 min using BodyCompSlicer and Slice-O-Matic, respectively.

Conclusion: BodyCompSlicer is comparable to Slice-O-Matic for CT body composition analysis.
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http://dx.doi.org/10.1007/s00261-017-1123-6DOI Listing
September 2017

Technical Note: Insertion of digital lesions in the projection domain for dual-source, dual-energy CT.

Med Phys 2017 May 17;44(5):1655-1660. Epub 2017 Apr 17.

Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA.

Purpose: To compare algorithms performing material decomposition and classification in dual-energy CT, it is desirable to know the ground truth of the lesion to be analyzed in real patient data. In this work, we developed and validated a framework to insert digital lesions of arbitrary chemical composition into patient projection data acquired on a dual-source, dual-energy CT system.

Methods: A model that takes into account beam-hardening effects was developed to predict the CT number of objects with known chemical composition. The model utilizes information about the x-ray energy spectra, the patient/phantom attenuation, and the x-ray detector energy response. The beam-hardening model was validated on samples of iodine (I) and calcium (Ca) for a second-generation dual-source, dual-energy CT scanner for all tube potentials available and a wide range of patient sizes. The seven most prevalent mineral components of renal stones were modeled and digital stones were created with CT numbers computed for each patient/phantom size and x-ray energy spectra using the developed beam-hardening model. Each digital stone was inserted in the dual-energy projection data of a water phantom scanned on a dual-source scanner and reconstructed with the routine algorithms in use in our practice. The geometry of the forward projection for dual-energy data was validated by comparing CT number accuracy and high-contrast resolution of simulated dual-energy CT data of the ACR phantom with experimentally acquired data.

Results: The beam-hardening model and forward projection method accurately predicted the CT number of I and Ca over a wide range of tube potentials and phantom sizes. The images reconstructed after the insertion of digital kidney stones were consistent with the images reconstructed from the scanner, and the CT number ratios for different kidney stone types were consistent with data in the literature. A sample application of the proposed tool was also demonstrated.

Conclusion: A framework was developed and validated for the creation of digital objects of known mineral composition, and for inserting the digital objects into projection data from a commercial dual-source, dual-energy CT scanner. Among other applications, it will allow a systematic investigation of the impact of scan and reconstruction parameters on kidney stone dual-energy properties under rigorously controlled conditions.
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http://dx.doi.org/10.1002/mp.12185DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5462480PMC
May 2017

Evaluation of a projection-domain lung nodule insertion technique in thoracic CT.

Proc SPIE Int Soc Opt Eng 2016 Feb 4;9783. Epub 2016 Apr 4.

Department of Radiology, Mayo Clinic, Rochester, MN.

Task-based assessment of computed tomography (CT) image quality requires a large number of cases with ground truth. Inserting lesions into existing cases to simulate positive cases is a promising alternative approach. The aim of this study was to evaluate a recently-developed raw-data based lesion insertion technique in thoracic CT. Lung lesions were segmented from patient CT images, forward projected, and reinserted into the same patient CT projection data. In total, 32 nodules of various attenuations were segmented from 21 CT cases. Two experienced radiologists and 2 residents blinded to the process independently evaluated these inserted nodules in two sub-studies. First, the 32 inserted and the 32 original nodules were presented in a randomized order and each received a rating score from 1 to 10 (1=absolutely artificial to 10=absolutely realistic). Second, the inserted and the corresponding original lesions were presented side-by-side to each reader, who identified the inserted lesion and provided a confidence score (1=no confidence to 5=completely certain). For the randomized evaluation, discrimination of real versus artificial nodules was poor with areas under the receiver operative characteristic curves being 0.69 (95% CI: 0.58-0.78), 0.57 (95% CI: 0.46-0.68), and 0.62 (95% CI: 0.54-0.69) for the 2 radiologists, 2 residents, and all 4 readers, respectively. For the side-by-side evaluation, although all 4 readers correctly identified inserted lesions in 103/128 pairs, the confidence score was moderate (2.6). Our projection-domain based lung nodule insertion technique provides a robust method to artificially generate clinical cases that prove to be difficult to differentiate from real cases.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5045053PMC
http://dx.doi.org/10.1117/12.2217009DOI Listing
February 2016

Validation of a Projection-domain Insertion of Liver Lesions into CT Images.

Acad Radiol 2016 10 16;23(10):1221-9. Epub 2016 Jul 16.

Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905. Electronic address:

Rationale And Objectives: The aim of this study was to validate a projection-domain lesion-insertion method with observer studies.

Materials And Methods: A total of 51 proven liver lesions were segmented from computed tomography images, forward projected, and inserted into patient projection data. The images containing inserted and real lesions were then reconstructed and examined in consensus by two radiologists. First, 102 lesions (51 original, 51 inserted) were viewed in a randomized, blinded fashion and scored from 1 (absolutely inserted) to 10 (absolutely real). Statistical tests were performed to compare the scores for inserted and real lesions. Subsequently, a two-alternative-forced-choice test was conducted, with lesions viewed in pairs (real vs. inserted) in a blinded fashion. The radiologists selected the inserted lesion and provided a confidence level of 1 (no confidence) to 5 (completely certain). The number of lesion pairs that were incorrectly classified was calculated.

Results: The scores for inserted and proven lesions had the same median (8) and similar interquartile ranges (inserted, 5.5-8; real, 6.5-8). The mean scores were not significantly different between real and inserted lesions (P value = 0.17). The receiver operating characteristic curve was nearly diagonal, with an area under the curve of 0.58 ± 0.06. For the two-alternative-forced-choice study, the inserted lesions were incorrectly identified in 49% (25 out of 51) of pairs; radiologists were incorrect in 38% (3 out of 8) of pairs even when they felt very confident in identifying the inserted lesion (confidence level ≥4).

Conclusions: Radiologists could not distinguish between inserted and real lesions, thereby validating the lesion-insertion technique, which may be useful for conducting virtual clinical trials to optimize image quality and radiation dose.
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http://dx.doi.org/10.1016/j.acra.2016.05.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5026898PMC
October 2016

Construction of realistic phantoms from patient images and a commercial three-dimensional printer.

J Med Imaging (Bellingham) 2016 Jul 7;3(3):033501. Epub 2016 Jul 7.

Mayo Clinic , Department of Radiology, 200 First Street SW, Rochester, Minnesota 55905, United States.

The purpose of this study was to use three-dimensional (3-D) printing techniques to construct liver and brain phantoms having realistic pathologies, anatomic structures, and heterogeneous backgrounds. Patient liver and head computed tomography (CT) images were segmented into tissue, vessels, liver lesion, white and gray matter, and cerebrospinal fluid (CSF). Stereolithography files of each object were created and imported into a commercial 3-D printer. Printing materials were assigned to each object after test scans, which showed that the printing materials had CT numbers ranging from 70 to 121 HU at 120 kV. Printed phantoms were scanned on a CT scanner and images were evaluated. CT images of the liver phantom had measured CT numbers of 77.8 and 96.6 HU for the lesion and background, and 137.5 to 428.4 HU for the vessels channels, which were filled with iodine solutions. The difference in CT numbers between lesions and background (18.8 HU) was representative of the low-contrast values needed for optimization tasks. The liver phantom background was evaluated with Haralick features and showed similar texture between patient and phantom images. CT images of the brain phantom had CT numbers of 125, 134, and 108 HU for white matter, gray matter, and CSF, respectively. The CT number differences were similar to those in patient images.
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http://dx.doi.org/10.1117/1.JMI.3.3.033501DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935810PMC
July 2016

Impact of number of repeated scans on model observer performance for a low-contrast detection task in computed tomography.

J Med Imaging (Bellingham) 2016 Apr 26;3(2):023504. Epub 2016 May 26.

Mayo Clinic , Department of Radiology, 200 First Street SW, Rochester, Minnesota 55905, United States.

Channelized Hotelling observer (CHO) models have been shown to correlate well with human observers for several phantom-based detection/classification tasks in clinical computed tomography (CT). A large number of repeated scans were used to achieve an accurate estimate of the model's template. The purpose of this study is to investigate how the experimental and CHO model parameters affect the minimum required number of repeated scans. A phantom containing 21 low-contrast objects was scanned on a 128-slice CT scanner at three dose levels. Each scan was repeated 100 times. For each experimental configuration, the low-contrast detectability, quantified as the area under receiver operating characteristic curve, [Formula: see text], was calculated using a previously validated CHO with randomly selected subsets of scans, ranging from 10 to 100. Using [Formula: see text] from the 100 scans as the reference, the accuracy from a smaller number of scans was determined. Our results demonstrated that the minimum number of repeated scans increased when the radiation dose level decreased, object size and contrast level decreased, and the number of channels increased. As a general trend, it increased as the low-contrast detectability decreased. This study provides a basis for the experimental design of task-based image quality assessment in clinical CT using CHO.
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http://dx.doi.org/10.1117/1.JMI.3.2.023504DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4886187PMC
April 2016

An Open Library of CT Patient Projection Data.

Proc SPIE Int Soc Opt Eng 2016 Feb 25;9783. Epub 2016 Mar 25.

Department of Radiology, Mayo Clinic, Rochester, MN 55905 USA.

Lack of access to projection data from patient CT scans is a major limitation for development and validation of new reconstruction algorithms. To meet this critical need, we are building a library of CT patient projection data in an open and vendor-neutral format, DICOM-CT-PD, which is an extended DICOM format that contains sinogram data, acquisition geometry, patient information, and pathology identification. The library consists of scans of various types, including head scans, chest scans, abdomen scans, electrocardiogram (ECG)-gated scans, and dual-energy scans. For each scan, three types of data are provided, including DICOM-CT-PD projection data at various dose levels, reconstructed CT images, and a free-form text file. Several instructional documents are provided to help the users extract information from DICOM-CT-PD files, including a dictionary file for the DICOM-CT-PD format, a DICOM-CT-PD reader, and a user manual. Radiologist detection performance based on the reconstructed CT images is also provided. So far 328 head cases, 228 chest cases, and 228 abdomen cases have been collected for potential inclusion. The final library will include a selection of 50 head, chest, and abdomen scans each from at least two different manufacturers, and a few ECG-gated scans and dual-source, dual-energy scans. It will be freely available to academic researchers, and is expected to greatly facilitate the development and validation of CT reconstruction algorithms.
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http://dx.doi.org/10.1117/12.2216823DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881843PMC
February 2016

Predicting detection performance with model observers: Fourier domain or spatial domain?

Proc SPIE Int Soc Opt Eng 2016 Feb 30;9783. Epub 2016 Mar 30.

Department of Radiology, Mayo Clinic, Rochester, MN 55905.

The use of Fourier domain model observer is challenged by iterative reconstruction (IR), because IR algorithms are nonlinear and IR images have noise texture different from that of FBP. A modified Fourier domain model observer, which incorporates nonlinear noise and resolution properties, has been proposed for IR and needs to be validated with human detection performance. On the other hand, the spatial domain model observer is theoretically applicable to IR, but more computationally intensive than the Fourier domain method. The purpose of this study is to compare the modified Fourier domain model observer to the spatial domain model observer with both FBP and IR images, using human detection performance as the gold standard. A phantom with inserts of various low contrast levels and sizes was repeatedly scanned 100 times on a third-generation, dual-source CT scanner at 5 dose levels and reconstructed using FBP and IR algorithms. The human detection performance of the inserts was measured via a 2-alternative-forced-choice (2AFC) test. In addition, two model observer performances were calculated, including a Fourier domain non-prewhitening model observer and a spatial domain channelized Hotelling observer. The performance of these two mode observers was compared in terms of how well they correlated with human observer performance. Our results demonstrated that the spatial domain model observer correlated well with human observers across various dose levels, object contrast levels, and object sizes. The Fourier domain observer correlated well with human observers using FBP images, but overestimated the detection performance using IR images.
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http://dx.doi.org/10.1117/12.2216962DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4879813PMC
February 2016

Evaluation of conventional imaging performance in a research whole-body CT system with a photon-counting detector array.

Phys Med Biol 2016 Feb 2;61(4):1572-95. Epub 2016 Feb 2.

Department of Radiology, Mayo Clinic; Rochester, Minnesota, 55905, USA.

This study evaluated the conventional imaging performance of a research whole-body photon-counting CT system and investigated its feasibility for imaging using clinically realistic levels of x-ray photon flux. This research system was built on the platform of a 2nd generation dual-source CT system: one source coupled to an energy integrating detector (EID) and the other coupled to a photon-counting detector (PCD). Phantom studies were conducted to measure CT number accuracy and uniformity for water, CT number energy dependency for high-Z materials, spatial resolution, noise, and contrast-to-noise ratio. The results from the EID and PCD subsystems were compared. The impact of high photon flux, such as pulse pile-up, was assessed by studying the noise-to-tube-current relationship using a neonate water phantom and high x-ray photon flux. Finally, clinical feasibility of the PCD subsystem was investigated using anthropomorphic phantoms, a cadaveric head, and a whole-body cadaver, which were scanned at dose levels equivalent to or higher than those used clinically. Phantom measurements demonstrated that the PCD subsystem provided comparable image quality to the EID subsystem, except that the PCD subsystem provided slightly better longitudinal spatial resolution and about 25% improvement in contrast-to-noise ratio for iodine. The impact of high photon flux was found to be negligible for the PCD subsystem: only subtle high-flux effects were noticed for tube currents higher than 300 mA in images of the neonate water phantom. Results of the anthropomorphic phantom and cadaver scans demonstrated comparable image quality between the EID and PCD subsystems. There were no noticeable ring, streaking, or cupping/capping artifacts in the PCD images. In addition, the PCD subsystem provided spectral information. Our experiments demonstrated that the research whole-body photon-counting CT system is capable of providing clinical image quality at clinically realistic levels of x-ray photon flux.
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http://dx.doi.org/10.1088/0031-9155/61/4/1572DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4782185PMC
February 2016

Lesion insertion in the projection domain: Methods and initial results.

Med Phys 2015 Dec;42(12):7034-42

Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905.

Purpose: To perform task-based image quality assessment in CT, it is desirable to have a large number of realistic patient images with known diagnostic truth. One effective way of achieving this objective is to create hybrid images that combine patient images with inserted lesions. Because conventional hybrid images generated in the image domain fails to reflect the impact of scan and reconstruction parameters on lesion appearance, this study explored a projection-domain approach.

Methods: Lesions were segmented from patient images and forward projected to acquire lesion projections. The forward-projection geometry was designed according to a commercial CT scanner and accommodated both axial and helical modes with various focal spot movement patterns. The energy employed by the commercial CT scanner for beam hardening correction was measured and used for the forward projection. The lesion projections were inserted into patient projections decoded from commercial CT projection data. The combined projections were formatted to match those of commercial CT raw data, loaded onto a commercial CT scanner, and reconstructed to create the hybrid images. Two validations were performed. First, to validate the accuracy of the forward-projection geometry, images were reconstructed from the forward projections of a virtual ACR phantom and compared to physically acquired ACR phantom images in terms of CT number accuracy and high-contrast resolution. Second, to validate the realism of the lesion in hybrid images, liver lesions were segmented from patient images and inserted back into the same patients, each at a new location specified by a radiologist. The inserted lesions were compared to the original lesions and visually assessed for realism by two experienced radiologists in a blinded fashion.

Results: For the validation of the forward-projection geometry, the images reconstructed from the forward projections of the virtual ACR phantom were consistent with the images physically acquired for the ACR phantom in terms of Hounsfield unit and high-contrast resolution. For the validation of the lesion realism, lesions of various types were successfully inserted, including well circumscribed and invasive lesions, homogeneous and heterogeneous lesions, high-contrast and low-contrast lesions, isolated and vessel-attached lesions, and small and large lesions. The two experienced radiologists who reviewed the original and inserted lesions could not identify the lesions that were inserted. The same lesion, when inserted into the projection domain and reconstructed with different parameters, demonstrated a parameter-dependent appearance.

Conclusions: A framework has been developed for projection-domain insertion of lesions into commercial CT images, which can be potentially expanded to all geometries of CT scanners. Compared to conventional image-domain methods, the authors' method reflected the impact of scan and reconstruction parameters on lesion appearance. Compared to prior projection-domain methods, the authors' method has the potential to achieve higher anatomical complexity by employing clinical patient projections and real patient lesions.
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http://dx.doi.org/10.1118/1.4935530DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4654739PMC
December 2015

Technical Note: Development and validation of an open data format for CT projection data.

Med Phys 2015 Dec;42(12):6964-72

Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905.

Purpose: Lack of access to projection data from patient CT scans is a major limitation for development and validation of new reconstruction algorithms. To meet this critical need, this work developed and validated a vendor-neutral format for CT projection data, which will further be employed to build a library of patient projection data for public access.

Methods: A digital imaging and communication in medicine (DICOM)-like format was created for CT projection data (CT-PD), named the DICOM-CT-PD format. The format stores attenuation information in the DICOM image data block and stores parameters necessary for reconstruction in the DICOM header under various tags (51 tags to store the geometry and scan parameters and 9 tags to store patient information). To validate the accuracy and completeness of the new format, CT projection data from helical scans of the ACR CT accreditation phantom were acquired from two clinical CT scanners (Somatom Definition Flash, Siemens Healthcare, Forchheim, Germany and Discovery CT750 HD, GE Healthcare, Waukesha, WI). After decoding (by the authors for Siemens, by the manufacturer for GE), the projection data were converted to the DICOM-CT-PD format. Off-line CT reconstructions were performed by internal and external reconstruction researchers using only the information stored in the DICOM-CT-PD files and the DICOM-CT-PD field definitions.

Results: Compared with the commercially reconstructed CT images, the off-line reconstructed images created using the DICOM-CT-PD format are similar in terms of CT numbers (differences of 5 HU for the bone insert and -9 HU for the air insert), image noise (±1 HU), and low contrast detectability (6 mm rods visible in both). Because of different reconstruction approaches, slightly different in-plane and cross-plane high contrast spatial resolution were obtained compared to those reconstructed on the scanners (axial plane: GE off-line, 7 lp/cm; GE commercial, 7 lp/cm; Siemens off-line, 8 lp/cm; Siemens commercial, 7 lp/cm. Coronal plane: Siemens off-line, 6 lp/cm; Siemens commercial, 8 lp/cm).

Conclusions: A vendor-neutral extended DICOM format has been developed that enables open sharing of CT projection data from third-generation CT scanners. Validation of the format showed that the geometric parameters and attenuation information in the DICOM-CT-PD file were correctly stored, could be retrieved with use of the provided instructions, and contained sufficient data for reconstruction of CT images that approximated those from the commercial scanner.
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http://dx.doi.org/10.1118/1.4935406DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4644156PMC
December 2015