Reinterpretation of Hepatopancreaticobiliary Imaging Exams: Assessment of Clinical Impact, Peer Learning, and Physician Satisfaction.

OBJECTIVES: To assess the impact on clinical management, potential for peer learning, and referring physician satisfaction with subspecialist reinterpretations of hepatopancreaticobiliary (HPB) imaging examinations. MATERIALS AND METHODS: HPB CTs and MRIs from outside hospitals were reinterpreted by two subspecialty radiologists between March 2021 and August 2022. Reinterpretation reports were mailed to radiologists that issued primary reports. The electronic record was reviewed to assess for changes in clinical management based on the reinterpretations (yes/no/unavailable). To assess the potential for peer learning, a survey using a 5-point Likert scale was sent to radiologists who issued primary reports. A separate survey was sent to referring physicians to assess satisfaction with reinterpretations. RESULTS: Two hundred fifty imaging examinations (122 CT, 128 MRI) were reinterpreted at the request of 19 referring physicians. Ninety-six radiologists issued primary reports. RADPEER scores 1-3 were assigned to 131/250 (52%), 86/250 (34%), and 33/250 (13%) examinations, respectively. Of 213 reinterpretations with adequate records for assessment, 75/213 (35%) were associated with a change in management; of these, 71/75 (95%) were classified as RADPEER 2 or 3. Most radiologists agreed or strongly agreed with the following: prefer to receive reinterpretations (34/36, 94%); reinterpretations changed practice of reporting HPB imaging examinations (23/36, 64%); and reinterpretations offer opportunities for peer learning (34/36, 94%). Referring physicians agreed or strongly agreed (7/7, 100%) that reinterpretations are valuable and often change or clarify management of patients with complex HPB disease, and offer an opportunity for peer learning. CONCLUSION: Radiologists and referring physicians strongly agree that HPB imaging reinterpretations help support peer learning and patient management, respectively.

Canadian Association of Radiologists Prostate MRI White Paper.

Prostate cancer is the most common malignancy and the third most common cause of death in Canadian men. In light of evolving diagnostic pathways for prostate cancer and the increased use of MRI, which now includes its use in men prior to biopsy, the Canadian Association of Radiologists established a Prostate MRI Working Group to produce a white paper to provide recommendations on establishing and maintaining a Prostate MRI Programme in the context of the Canadian healthcare system. The recommendations, which are based on available scientific evidence and/or expert consensus, are intended to maintain quality in image acquisition, interpretation, reporting and targeted biopsy to ensure optimal patient care. The paper covers technique, reporting, quality assurance and targeted biopsy considerations and includes appendices detailing suggested reporting templates, quality assessment tools and sample image acquisition protocols relevant to the Canadian healthcare context.

Diagnostic Performance and Interreader Agreement of the MRI Clear Cell Likelihood Score for Characterization of cT1a and cT1b Solid Renal Masses: An External Validation Study.

BACKGROUND. The clear cell likelihood score (ccLS) has been proposed for the noninvasive differentiation of clear cell renal cell carcinoma (ccRCC) from other renal neoplasms on multiparametric MRI (mpMRI), though further external validation remains needed. OBJECTIVE. The purpose of our study was to evaluate the diagnostic performance and interreader agreement of the ccLS version 2.0 (v2.0) for characterizing solid renal masses as ccRCC. METHODS. This retrospective study included 102 patients (67 men, 35 women; mean age, 56.9 ± 12.8 [SD] years) who underwent mpMRI between January 2013 and February 2018, showing a total of 108 (≥ 25% enhancing tissue) solid renal masses measuring 7 cm or smaller (83 cT1a [≤ 4 cm] and 25 cT1b [> 4 cm and ≤ 7 cm]), all with a histologic diagnosis. Three abdominal radiologists independently reviewed the MRI examinations using ccLS v2.0. Median reader sensitivity, specificity, and accuracy were computed for predicting ccRCC by ccLS of 4 or greater, and individual reader AUCs were derived. The percentage of masses that were ccRCC was calculated, stratified by ccLS. Interobserver agreement was assessed by the Fleiss kappa statistic. RESULTS. The sample included 45 ccRCCs (34 cT1a, 11 cT1b), 30 papillary renal cell carcinomas (RCCs), 13 chromophobe RCCs, 14 oncocytomas, and six fat-poor angiomyolipomas. Median reader sensitivity, specificity, and accuracy for predicting ccRCC by ccLS of 4 or greater were 85%, 82%, and 83% among cT1a masses and 82%, 100%, and 92% among cT1b masses. The three readers' AUCs for predicting ccRCC by ccLS for cT1a masses were 0.90, 0.84, and 0.89 and for cT1b masses were 0.99, 0.97, and 0.92. Across readers, the percentage of masses that were ccRCC among cT1a masses was 0%, 0%, 20%, 68%, and 93% for ccLS of 1, 2, 3, 4, and 5, respectively; among cT1b masses, the percentage of masses that were ccRCC was 0%, 0%, 32%, 90%, and 100% for ccLS of 1, 2, 3, 4, and 5, respectively. Interobserver agreement among cT1a and cT1b masses for ccLS of 4 or greater was 0.82 and 0.83 and for ccLS of 1-5 overall was 0.65 and 0.62, respectively. CONCLUSION. This study provides external validation of the ccLS, finding overall high measures of diagnostic performance and interreader agreement. CLINICAL IMPACT. The ccLS provides a standardized approach to the noninvasive diagnosis of ccRCC by MRI.

Prospective Evaluation of Virtual MR Elastography With Diffusion-Weighted Imaging in Subjects With Nonalcoholic Fatty Liver Disease.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is increasingly common worldwide and can lead to the development of cirrhosis, liver failure and cancer. Virtual magnetic resonance elastography (VMRE), which is based on a shifted apparent diffusion coefficient (sADC), is a potential noninvasive method to assess liver fibrosis without the specialized hardware and expertise required to implement traditional MR elastography (MRE). Although hepatic steatosis is known to confound ADC measurements, previous studies using VMRE have not corrected for hepatic fat fraction. PURPOSE: To compare VMRE, corrected for the confounding effects of unsuppressed fat signal, to MRE and biopsy in subjects with suspected NAFLD. STUDY TYPE: Prospective, cross-sectional. POPULATION: A total of 49 adult subjects with suspected NAFLD (18 male; median age 55 years, range 33-74 years) who underwent liver biopsy. FIELD STRENGTH/SEQUENCE: 3T, diffusion-weighted spin echo planar, chemical-shift encoded (IDEAL IQ) and MRE sequences. ASSESSMENT: Two observers drew regions of interest on sADC, proton density fat fraction and MRE-derived stiffness maps. Fat-corrected sADC values were used to calculate the diffusion-based shear modulus according to the VMRE method. Predicted fibrosis stage for MRE and VMRE was determined using previously published cut-off values. STATISTICAL TESTS: The relationship between VMRE and MRE was assessed with least-squares linear regression (coefficient of determination, R2 ). Agreement between MRE and VMRE-predicted fibrosis stage was evaluated with a kappa coefficient and accuracy compared using McNemar's test. A one-way ANOVA determined if the fat-corrected sADC (VMRE) and MRE differed by fibrosis stage. A P value < 0.05 was considered statistically significant. RESULTS: Least squares regression of VMRE vs. MRE revealed R2  = 0.046 and a slope that was not significantly different from zero (P = 0.14). There was no agreement between MRE and VMRE-predicted fibrosis stage (kappa = -0.01). The proportion of correctly predicted fibrosis stage was significantly higher for MRE compared to VMRE. MRE was significantly associated with fibrosis stage, but fat-corrected sADC was not (P = 0.24). DATA CONCLUSION: Fat-corrected VMRE was not associated with fibrosis stage in NAFLD. Further investigation is required if VMRE is to be considered in subjects with NAFLD. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Canadian Association of Radiologists Recommendations for the Safe Use of MRI During Pregnancy.

The use of magnetic resonance imaging (MRI) during pregnancy is associated with concerns among patients and health professionals with regards to fetal safety. In this work, the Canadian Association of Radiologists (CAR) Working Group on MRI in Pregnancy presents recommendations for the use of MRI in pregnancy, derived from literature review as well as expert panel opinions and discussions. The working group, which consists of academic subspecialty radiologists and obstetrician-gynaecologists, aimed to provide updated, evidence-based recommendations addressing safety domains related to energy deposition, acoustic noise, and gadolinium-based contrast agent use based on magnetic field strength (1.5T and 3T) and trimester scanned, in addition to the effects of sedative use and occupational exposure.

US LI-RADS Visualization Score: Interobserver Variability and Association With Cause of Liver Disease, Sex, and Body Mass Index.

OBJECTIVES: To evaluate the interobserver agreement between radiologists using the Ultrasound Liver Reporting And Data System (US LI-RADS) visualization score and assess association between visualization score and cause of liver disease, sex, and body mass index (BMI). METHODS: This retrospective, single institution, cross-sectional study evaluated 237 consecutive hepatocellular carcinoma surveillance US examinations between March 4, 2017 and September 4, 2017. Five abdominal radiologists independently assigned a US LI-RADS visualization score (A, no or minimal limitations; B, moderate limitations; C, severe limitations). Interobserver agreement was assessed with a weighted Kappa statistic. Association between US visualization score (A vs B or C) and cause of liver disease, sex, and BMI (< or ≥ 25 kg/m2) was evaluated using univariate and multivariate analyses. RESULTS: The average weighted Kappa statistic for all raters was 0.51. A score of either B or C was assigned by the majority of radiologists in 148/237 cases and was significantly associated with cause of liver disease (P = 0.014) and elevated BMI (P < 0.001). Subjects with viral liver disease were 3.32 times (95% CI: 1.44-8.38) more likely to have a score of A than those with non-alcoholic steatohepatitis (P = 0.007). The adjusted odds ratio of visualization score A was 0.249 (95% CI: 0.13-0.48) among those whose BMI was ≥25 kg/m2 vs. BMI < 25 kg/m2. CONCLUSION: Interobserver agreement between radiologists using US LI-RADS score was moderate. The majority of US examinations were scored as having moderate or severe limitations, and this was significantly associated with non-alcoholic steatohepatitis and increased BMI.

Combined Transfer Learning and Test-Time Augmentation Improves Convolutional Neural Network-Based Semantic Segmentation of Prostate Cancer from Multi-Parametric MR Images.

PURPOSE: Multiparametric MRI (mp-MRI) is a widely used tool for diagnosing and staging prostate cancer. The purpose of this study was to evaluate whether transfer learning, unsupervised pre-training and test-time augmentation significantly improved the performance of a convolutional neural network (CNN) for pixel-by-pixel prediction of cancer vs. non-cancer using mp-MRI datasets. METHODS: 154 subjects undergoing mp-MRI were prospectively recruited, 16 of whom subsequently underwent radical prostatectomy. Logistic regression, random forest and CNN models were trained on mp-MRI data using histopathology as the gold standard. Transfer learning, unsupervised pre-training and test-time augmentation were used to boost CNN performance. Models were evaluated using Dice score and area under the receiver operating curve (AUROC) with leave-one-subject-out cross validation. Permutation feature importance testing was performed to evaluate the relative value of each MR contrast to CNN model performance. Statistical significance (p<0.05) was determined using the paired Wilcoxon signed rank test with Benjamini-Hochberg correction for multiple comparisons. RESULTS: Baseline CNN outperformed logistic regression and random forest models. Transfer learning and unsupervised pre-training did not significantly improve CNN performance over baseline; however, test-time augmentation resulted in significantly higher Dice scores over both baseline CNN and CNN plus either of transfer learning or unsupervised pre-training. The best performing model was CNN with transfer learning and test-time augmentation (Dice score of 0.59 and AUROC of 0.93). The most important contrast was apparent diffusion coefficient (ADC), followed by Ktrans and T2, although each contributed significantly to classifier performance. CONCLUSIONS: The addition of transfer learning and test-time augmentation resulted in significant improvement in CNN segmentation performance in a small set of prostate cancer mp-MRI data. Results suggest that these techniques may be more broadly useful for the optimization of deep learning algorithms applied to the problem of semantic segmentation in biomedical image datasets. However, further work is needed to improve the generalizability of the specific model presented herein.

Magnetic Resonance Imaging Based Radiomic Models of Prostate Cancer: A Narrative Review.

The management of prostate cancer (PCa) is dependent on biomarkers of biological aggression. This includes an invasive biopsy to facilitate a histopathological assessment of the tumor's grade. This review explores the technical processes of applying magnetic resonance imaging based radiomic models to the evaluation of PCa. By exploring how a deep radiomics approach further optimizes the prediction of a PCa's grade group, it will be clear how this integration of artificial intelligence mitigates existing major technological challenges faced by a traditional radiomic model: image acquisition, small data sets, image processing, labeling/segmentation, informative features, predicting molecular features and incorporating predictive models. Other potential impacts of artificial intelligence on the personalized treatment of PCa will also be discussed. The role of deep radiomics analysis-a deep texture analysis, which extracts features from convolutional neural networks layers, will be highlighted. Existing clinical work and upcoming clinical trials will be reviewed, directing investigators to pertinent future directions in the field. For future progress to result in clinical translation, the field will likely require multi-institutional collaboration in producing prospectively populated and expertly labeled imaging libraries.

The implications of missed or misinterpreted cases of pancreatic ductal adenocarcinoma on imaging: a multi-centered population-based study.

OBJECTIVES: To assess the proportion of missed/misinterpreted imaging examinations of pancreatic ductal adenocarcinoma (PDAC), and their association with the diagnostic interval and survival. METHODS: Two hundred fifty-seven patients (mean age, 71.8 years) diagnosed with PDAC in 2014-2015 were identified from the Nova Scotia Cancer Registry. Demographics, stage, tumor location, and dates of initial presentation, diagnosis, and, if applicable, surgery and death were recorded. US, CT, and MRI examinations during the diagnostic interval were independently graded by two radiologists using the RADPEER system; discordance was resolved in consensus. Mean diagnostic interval and survival were compared amongst RADPEER groups (one-way ANOVA). Kaplan-Meier analysis was performed for age (< 65, 65-79, ≥ 80), sex, tumor location (proximal/distal), stage (I-IV), surgery (yes/no), chemotherapy (yes/no), and RADPEER score (1-3). Association between these covariates and survival was assessed (multivariate Cox proportion hazards model). RESULTS: RADPEER 1-3 scores were assigned to 191, 27, and 39 patients, respectively. Mean diagnostic intervals were 53, 86, and 192 days, respectively (p = 0.018). There were only 3/257 (1.2%) survivors. Mean survival was not different between groups (p = 0.43). Kaplan-Meier analysis showed worse survival in RADPEER 1-2 (p = 0.007), older age (p < 0.001), distal PDAC (p = 0.016), stage (p < 0.0001), and no surgery (p < 0.001); survival was not different with sex (p = 0.083). Cox analysis showed better survival in RADPEER 3 (p = 0.005), women (p = 0.002), surgical patients (p < 0.001), and chemotherapy (p < 0.001), and worse survival in stage IV (p = 0.006). CONCLUSION: Imaging-related delays occurred in one-fourth of patients and were associated with longer diagnostic intervals but not worse survival, potentially due to overall poor survival in the cohort. KEY POINTS: • One-fourth of patients (66/257, 25.7%) with pancreatic ductal adenocarcinoma (PDAC) underwent imaging examinations that demonstrated manifestations of the disease, but findings were either missed or misinterpreted; RADPEER 2 and 3 scores were assigned to 10.5% and 15.2% of patients, respectively. • Patients with imaging examinations assigned RADPEER 3 scores were associated with significantly longer diagnostic intervals (192 ± 323 days) than RADPEER 1 (53 ± 86 days) and RADPEER 2 (86 ± 120 days) (p < 0.001). • Imaging-related diagnostic delays were not associated with worse survival; however, this may have been confounded by the overall poor survival in our cohort (only 3/257 (1.2%) survivors).

Mapping of fatty acid composition with free-breathing MR spectroscopic imaging and compressed sensing.

Nonalcoholic fatty liver disease (NAFLD) is a growing health problem, and a major challenge in NAFLD management is identifying which patients are at risk of progression to more serious disease. Simple measurements of liver fat content are not strong predictors of clinical outcome, but biomarkers related to fatty acid composition (ie, saturated vs. unsaturated fat) may be more effective. MR spectroscopic imaging (MRSI) methods allow spatially resolved, whole-liver measurements of chemical composition but are traditionally limited by slow acquisition times. In this work we present an accelerated MRSI acquisition based on spin echo single point imaging (SE-SPI), which, using appropriate sampling and compressed sensing reconstruction, allows free-breathing acquisition in a mouse model of fatty liver disease. After validating the technique's performance in oil/water phantoms, we imaged mice that had received a normal diet or a methionine and choline deficient (MCD) diet, some of which also received supplemental injections of iron to mimic hepatic iron overload. SE-SPI was more resistant to the line-broadening effects of iron than single-voxel spectroscopy measurements, and was consistently able to measure the amplitudes of low-intensity spectral peaks that are important to characterizing fatty acid composition. In particular, in the mice receiving the MCD diet, SE-SPI showed a significant decrease in a metric associated with unsaturated fat, which is consistent with the literature. This or other related metrics may therefore offer more a specific biomarker of liver health than fat content alone. This preclinical study is an important precursor to clinical testing of the proposed method. MR-based quantification of fatty acid composition may allow for improved characterization of non-alcoholic fatty liver disease. A spectroscopic imaging method with appropriate sampling strategy allows whole-liver mapping of fat composition metrics in a free-breathing mouse model. Changes in metrics like the surrogate unsaturation index (UIs) are visible in mice receiving a diet which induces fat accumulation in the liver, as compared to a normal diet; such metrics may prove useful in future clinical studies of liver disease.

Factors associated with missed and misinterpreted cases of pancreatic ductal adenocarcinoma.

OBJECTIVES: To retrospectively examine US, CT, and MR imaging examinations of missed or misinterpreted pancreatic ductal adenocarcinoma (PDAC), and identify factors which may have confounded detection or interpretation. METHODS: We reviewed 107 examinations in 66/257 patients (26%, mean age 73.7 years) diagnosed with PDAC in 2014 and 2015, with missed or misinterpreted imaging findings as determined by a prior study. For each patient, images and reports were independently reviewed by two radiologists, and in consensus, the following factors which may have confounded assessment were recorded: inherent tumor factors, concurrent pancreatic pathology, technical limitations, and cognitive biases. Secondary signs of PDAC associated with each examination were recorded and compared with the original report to determine which findings were missed. RESULTS: There were 66/107 (62%) and 49/107 (46%) cases with missed and misinterpreted imaging findings, respectively. A significant number of missed tumors were < 2 cm (45/107, 42%), isoattenuating on CT (32/72, 44%) or non-contour deforming (44/107, 41%). Most (29/49, 59%) misinterpreted examinations were reported as uncomplicated pancreatitis. Almost all examinations (94/107, 88%) demonstrated secondary signs; pancreatic duct dilation was the most common (65/107, 61%) and vascular invasion was the most commonly missed 35/39 (90%). Of the CT and MRIs, 28 of 88 (32%) had suboptimal contrast dosing. Inattentional blindness was the most common cognitive bias, identified in 55/107 (51%) of the exams. CONCLUSION: Recognizing pitfalls of PDAC detection and interpretation, including intrinsic tumor features, secondary signs, technical factors, and cognitive biases, can assist radiologists in making an early and accurate diagnosis. KEY POINTS: • There were 66/107 (62%) and 49/107 (46%) cases with missed and misinterpreted imaging findings, respectively, with tumoral, technical, and cognitive factors leading to the misdiagnosis of pancreatic ductal adenocarcinoma. • The majority (29/49, 59%) of misinterpreted cases of pancreatic ductal adenocarcinoma were mistaken for pancreatitis, where an underlying mass or secondary signs were not appreciated due to inflammatory changes. • The most common missed secondary sign of pancreatic ductal adenocarcinoma was vascular encasement, missed in 35/39 (90%) of cases, indicating the importance of evaluating the peri-pancreatic vasculature.

Benign Neoplasms, Mass-Like Infections, and Pseudotumors That Mimic Hepatic Malignancy at MRI.

A variety of conditions may mimic hepatic malignancy at MRI. These include benign hepatic tumors and tumor-like entities such as focal nodular hyperplasia-like lesions, hepatocellular adenoma, hepatic infections, inflammatory pseudotumor, vascular entities, and in the cirrhotic liver, confluent fibrosis, and hypertrophic pseudomass. These conditions demonstrate MRI features that overlap with hepatic malignancy, and can be challenging for radiologists to diagnose accurately. In this review we discuss the MRI manifestations of various conditions that mimic hepatic malignancy, and highlight features that may allow distinction from malignancy. Level of Evidence 5 Technical Efficacy Stage 3.

Pearls, Pitfalls, and Conditions that Mimic Mesenteric Ischemia at CT.

Acute mesenteric ischemia (AMI) is a life-threatening condition with a high mortality rate. The diagnosis of AMI is challenging because patient symptoms and laboratory test results are often nonspecific. A high degree of clinical and radiologic suspicion is required for accurate and timely diagnosis. CT angiography of the abdomen and pelvis is the first-line imaging test for suspected AMI and should be expedited. A systematic "inside-out" approach to interpreting CT angiographic images, beginning with the bowel lumen and proceeding outward to the bowel wall, mesentery, vasculature, and extraintestinal viscera, provides radiologists with a practical framework to improve detection and synthesis of imaging findings. The subtypes of AMI are arterial and venoocclusive disease, nonocclusive ischemia, and strangulating bowel obstruction; each may demonstrate specific imaging findings. Chronic mesenteric ischemia is more insidious at onset and almost always secondary to atherosclerosis. Potential pitfalls in the diagnosis of AMI include mistaking pneumatosis as a sign that is specific for AMI and not an imaging finding, misinterpretation of adynamic ileus as a benign finding, and pseudopneumatosis. Several enterocolitides can mimic AMI at CT angiography, such as inflammatory bowel disease, infections, angioedema, and radiation-induced enterocolitis. Awareness of pitfalls, conditions that mimic AMI, and potential distinguishing clinical and imaging features can assist radiologists in making an early and accurate diagnosis of AMI. ©RSNA, 2020.

Editorial for "Development of a Novel Multiparametric MRI Radiomic Nomogram for Preoperative Evaluation of Early Recurrence in Resectable Pancreatic Cancer".

LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2 J. Magn. Reson. Imaging 2020;52:246-247.

Comparison of Objective Image Quality Metrics to Expert Radiologists' Scoring of Diagnostic Quality of MR Images.

Image quality metrics (IQMs) such as root mean square error (RMSE) and structural similarity index (SSIM) are commonly used in the evaluation and optimization of accelerated magnetic resonance imaging (MRI) acquisition and reconstruction strategies. However, it is unknown how well these indices relate to a radiologist's perception of diagnostic image quality. In this study, we compare the image quality scores of five radiologists with the RMSE, SSIM, and other potentially useful IQMs: peak signal to noise ratio (PSNR) multi-scale SSIM (MSSSIM), information-weighted SSIM (IWSSIM), gradient magnitude similarity deviation (GMSD), feature similarity index (FSIM), high dynamic range visible difference predictor (HDRVDP), noise quality metric (NQM), and visual information fidelity (VIF). The comparison uses a database of MR images of the brain and abdomen that have been retrospectively degraded by noise, blurring, undersampling, motion, and wavelet compression for a total of 414 degraded images. A total of 1017 subjective scores were assigned by five radiologists. IQM performance was measured via the Spearman rank order correlation coefficient (SROCC) and statistically significant differences in the residuals of the IQM scores and radiologists' scores were tested. When considering SROCC calculated from combining scores from all radiologists across all image types, RMSE and SSIM had lower SROCC than six of the other IQMs included in the study (VIF, FSIM, NQM, GMSD, IWSSIM, and HDRVDP). In no case did SSIM have a higher SROCC or significantly smaller residuals than RMSE. These results should be considered when choosing an IQM in future imaging studies.

Evaluation of liver MRI examinations with two dosages of gadobenate dimeglumine: a blinded intra-individual study.

PURPOSE: There is discrepancy in the literature regarding the optimal dose of gadobenate for liver MRI. We evaluated the quality of liver MRIs performed in the same individual using two dosages. METHODS: With ethics approval, this retrospective study evaluated sixty patients who underwent liver MRIs between July 2015 and May 2017 (low dose, 0.06 mmol/kg) and May 2017 and September 2018 (standard dose, 0.10 mmol/kg). Regions of interest were drawn over the aorta, portal veins, and liver on unenhanced and post-contrast phases; relative enhancement values were compared (paired t-tests). Two blinded radiologists graded the arterial and portal venous sequences of each MRI from 1 to 4 (1 = suboptimal, 2 = adequate, 3 = good, 4 = excellent); grades were compared overall and in cirrhotic and non-cirrhotic subgroups (Wilcoxon signed-rank test). Radiologists graded each MRI pair from 1 to 5 (1 = substantially inferior, 2 = slightly inferior, 3 = equivalent, 4 = slightly improved, 5 = substantially improved). Inter-reader agreement was assessed (kappa statistic). RESULTS: Relative enhancement increased significantly with the standard dose for all structures on all phases (p < 0.05). For both radiologists and both post-contrast phases, individual grades of the low- and standard-dose MRIs were similar, including the cirrhotic and non-cirrhotic subgroups (p > 0.05). Compared to the low-dose MRIs, the number of standard-dose MRIs graded 1-5 were 9, 31, 97, 88, and 11 for all patients, and 6, 13, 26, 45, and 6 in cirrhotics. Inter-observer agreement was fair-moderate (Κ range 0.23-0.45). CONCLUSIONS: Although the standard dose of gadobenate yields greater relative enhancement, there is overall little improvement in subjective imaging quality. A trend towards better image quality is observed in cirrhotics.

Model-free prostate cancer segmentation from dynamic contrast-enhanced MRI with recurrent convolutional networks: A feasibility study.

Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is a method of temporal imaging that is commonly used to aid in prostate cancer (PCa) diagnosis and staging. Typically, machine learning models designed for the segmentation and detection of PCa will use an engineered scalar image called Ktrans to summarize the information in the DCE time-series images. This work proposes a new model that amalgamates the U-net and the convGRU neural network architectures for the purpose of interpreting DCE time-series in a temporal and spatial basis for segmenting PCa in MR images. Ultimately, experiments show that the proposed model using the DCE time-series images can outperform a baseline U-net segmentation model using Ktrans. However, when other types of scalar MR images are considered by the models, no significant advantage is observed for the proposed model.

Technical Note: Evaluation of kV CBCT enhancement using a liver-specific contrast agent for stereotactic body radiation therapy image guidance.

PURPOSE: To evaluate possible use for cone-beam computed tomography (CBCT) guidance, this phantom study evaluated the contrast enhancement provided by Gadoxetate Disodium (Primovist® CAN/EU, or Eovist® USA, Bayer Healthcare, Leverkusen, Germany), a contrast agent that is taken up selectively by liver cells and is retained for up to an hour. Image quality from CBCT was benchmarked against helical fan-beam computed tomography for two phantom geometries. METHODS AND MATERIALS: Concentrations were diluted to 0.0125-0.1 mmol per kilogram of body weight (mmol/kg) corresponding to expected physiological concentrations in the liver. Kilovoltage CBCT imaging parameters of x-ray tube potential, current, and filtration were investigated using clinically available options on a TrueBeam STx linear accelerator CBCT platform. Two phantoms were created, a cylindrical idealized imaging geometry and an ellipsoidal more realistic abdominal geometry. All parameters were optimized according to the contrast-to-noise ratio (CNR) image quality metric, as a function of concentration, following the Rose criterion for CNR. RESULTS: Acceptable CNR was defined as greater than or equal to three, in accordance with the Rose criterion for CNR. These were found in a range of expected liver concentrations of 0.025-0.1 mmol/kg for a tube potential of 100 kVp, half-fan bowtie filtration and tube currents giving exposures between 2025 and 5085 mAs. Linear correlations were found for all CNR as a function of concentration, in agreement with the literature. CONCLUSION: Based on this phantom study, with appropriate selection of imaging protocol, Gadoxetate Disodium may provide useful liver CBCT enhancement at physiologically achievable liver concentrations.

Fat-Containing Liver Lesions on Imaging: Detection and Differential Diagnosis.

OBJECTIVE: The purpose of this article is to review how fat is detected on imaging and to discuss the differential diagnosis of fat-containing liver lesions. CONCLUSION: Fat is a highly useful feature in characterizing liver lesions on imaging. Although a variety of liver lesions can show fat on cross-sectional imaging, the presence of fat usually indicates that the lesion is of hepatocellular origin. Less commonly, nonhepatocellular fatty lesions may be distinguished by ancillary clinical and imaging features.