Predicting cytogenetic risk in multiple myeloma using conventional whole-body MRI, spinal dynamic contrast-enhanced MRI, and spinal diffusion-weighted imaging.

OBJECTIVES: Cytogenetic abnormalities are predictors of poor prognosis in multiple myeloma (MM). This paper aims to build and validate a multiparametric conventional and functional whole-body MRI-based prediction model for cytogenetic risk classification in newly diagnosed MM. METHODS: Patients with newly diagnosed MM who underwent multiparametric conventional whole-body MRI, spinal dynamic contrast-enhanced (DCE-)MRI, spinal diffusion-weighted MRI (DWI) and had genetic analysis were retrospectively included (2011-2020/Ghent University Hospital/Belgium). Patients were stratified into standard versus intermediate/high cytogenetic risk groups. After segmentation, 303 MRI features were extracted. Univariate and model-based methods were evaluated for feature and model selection. Testing was performed using receiver operating characteristic (ROC) and precision-recall curves. Models comparing the performance for genetic risk classification of the entire MRI protocol and of all MRI sequences separately were evaluated, including all features. Four final models, including only the top three most predictive features, were evaluated. RESULTS: Thirty-one patients were enrolled (mean age 66 ± 7 years, 15 men, 13 intermediate-/high-risk genetics). None of the univariate models and none of the models with all features included achieved good performance. The best performing model with only the three most predictive features and including all MRI sequences reached a ROC-area-under-the-curve of 0.80 and precision-recall-area-under-the-curve of 0.79. The highest statistical performance was reached when all three MRI sequences were combined (conventional whole-body MRI + DCE-MRI + DWI). Conventional MRI always outperformed the other sequences. DCE-MRI always outperformed DWI, except for specificity. CONCLUSIONS: A multiparametric MRI-based model has a better performance in the noninvasive prediction of high-risk cytogenetics in newly diagnosed MM than conventional MRI alone. CRITICAL RELEVANCE STATEMENT: An elaborate multiparametric MRI-based model performs better than conventional MRI alone for the noninvasive prediction of high-risk cytogenetics in newly diagnosed multiple myeloma; this opens opportunities to assess genetic heterogeneity thus overcoming sampling bias. KEY POINTS: • Standard genetic techniques in multiple myeloma patients suffer from sampling bias due to tumoral heterogeneity. • Multiparametric MRI noninvasively predicts genetic risk in multiple myeloma. • Combined conventional anatomical MRI, DCE-MRI, and DWI had the highest statistical performance to predict genetic risk. • Conventional MRI alone always outperformed DCE-MRI and DWI separately to predict genetic risk. DCE-MRI alone always outperformed DWI separately, except for the parameter specificity to predict genetic risk. • This multiparametric MRI-based genetic risk prediction model opens opportunities to noninvasively assess genetic heterogeneity thereby overcoming sampling bias in predicting genetic risk in multiple myeloma.

Prospective longitudinal evaluation of hospitalised COVID-19 survivors 3 and 12 months after discharge.

Background: Long-term outcome data of coronavirus disease 2019 (COVID-19) survivors are needed to understand their recovery trajectory and additional care needs. Methods: A prospective observational multicentre cohort study was carried out of adults hospitalised with COVID-19 from March through May 2020. Workup at 3 and 12 months following admission consisted of clinical review, pulmonary function testing, 6-min walk distance (6MWD), muscle strength, chest computed tomography (CT) and quality of life questionnaires. We evaluated factors correlating with recovery by linear mixed effects modelling. Results: Of 695 patients admitted, 299 and 226 returned at 3 and 12 months, respectively (median age 59 years, 69% male, 31% severe disease). About half and a third of the patients reported fatigue, dyspnoea and/or cognitive impairment at 3 and 12 months, respectively. Reduced 6MWD and quadriceps strength were present in 20% and 60% at 3 months versus 7% and 30% at 12 months. A high anxiety score and body mass index correlated with poor functional recovery. At 3 months, diffusing capacity for carbon monoxide (D LCO) and total lung capacity were below the lower limit of normal in 35% and 18%, decreasing to 21% and 16% at 12 months; predictors of poor D LCO recovery were female sex, pre-existing lung disease, smoking and disease severity. Chest CT improved over time; 10% presented non-progressive fibrotic changes at 1 year. Conclusion: Many COVID-19 survivors, especially those with severe disease, experienced limitations at 3 months. At 1 year, the majority showed improvement to almost complete recovery. To identify additional care or rehabilitation needs, we recommend a timely multidisciplinary follow-up visit following COVID-19 admission.

Myxoid hepatocellular adenoma, a rare variant of hepatocellular adenoma with distinct imaging features: A case report with immunohistochemical and molecular analysis and literature review.

Preoperative imaging and histopathology, immunohistochemistry and molecular analysis after resection of 2 hepatocellular adenomas (HCAs) (20 and 2cm) in a 53-year-old female patient were performed. On imaging, the large lesion resembled a myxoid HCA, while the small lesion resembled a more conventional HCA with a small myxoid/fluid area. On microscopy, the large lesion showed cords and nests of hepatocytes embedded in abundant myxoid matrix, while the small lesion resembled a conventional HCA with small foci of myxoid change and serosities; both consistent with a myxoid HCA. Immunophenotyping and molecular subtyping excluded inflammatory HCA, CTNNB1 mutated HCA and sonic hedgehog HCA, and was consistent with HNF1A mutated HCA. The myxoid change as well as the serosities may allow imaging diagnosis of myxoid HCA. As fluid vacuoles can also be present in ASS1+HCA, sonic hedgehog HCA has to be considered in the differential diagnosis.

Performance of liver surface nodularity quantification for the diagnosis of portal hypertension in patients with cirrhosis: comparison between MRI with hepatobiliary phase sequences and CT.

PURPOSE: To assess and compare the performance of liver surface nodularity (LSN) quantification using Gd-BOPTA-enhanced MRI and contrast-enhanced CT for the diagnosis of clinically significant portal hypertension (CSPH) in patients with cirrhosis. METHODS: This retrospective study included 30 patients with compensated histologically proven cirrhosis who underwent hepatic venous pressure gradient (HVPG), abdominal CT and Gd-BOPTA-MRI within a 60-day interval during pre-surgery workup for hepatocellular carcinoma (HCC) between January 2016 and August 2018. LSN score was derived from CT portal venous phase (PVP), axial T2- and T1-weighted PVP and hepatobiliary phase (HBP). Accuracy for the detection of CSPH was evaluated for each set of images by ROC curve analysis. Intra-observer, inter-observer and inter-method reproducibilities were assessed by the intraclass correlation coefficient (ICC) and coefficient of variation (CV). RESULTS: Thirty patients were analysed (23 men [77%], mean age 60 ± 11 years old), including 15 (50%) with CSPH. All CT- and MRI-derived LSN quantifications were correlated to HVPG (CT-PVP: r = 0.63, p = 0.001, AUROC = 0.908 ± 0.06; T1-w-PVP: r = 0.43, p = 0.028, AUROC = 0.876 ± 0.07; T1-w-HBP: r = 0.50, p = 0.012, AUROC = 0.823 ± 0.08; T2-w: r = 0.51, p = 0.007, AUROC = 0.801 ± 0.09). There was no significant difference in AUROC pairwise comparisons (p = 0.12-0.88). Patients with CSPH had higher LSN than those without (CT-PVP: 3.2 ± 0.6 vs 2.4 ± 0.5, p < 0.001; T1-w-PVP: 2.7 ± 0.4 vs 2.2 ± 0.4, p = 0.002; T1-w-HBP: 3.0 ± 0.6 vs 2.3 ± 0.3, p < 0.001; T2-w: 3.0 ± 0.6 vs 2.2 ± 0.3, p = 0.001) and 86%, 82%, 85% and 82% of patients were correctly classified, respectively. Reproducibility of inter-image set comparisons was excellent (ICC = 0.84-0.96 and CV = 8.3-14.2%). CONCLUSION: The diagnostic performance of MRI-based LSN for detecting CSPH is strong and similar to that of CT-based LSN.

Common Mistakes and Pitfalls in Magnetic Resonance Imaging of the Knee.

This pictorial review presents an overview of common interpretation errors and pitfalls in magnetic resonance imaging (MRI) of the knee. Instead of being exhaustive, we will emphasize those pitfalls that are most commonly encountered by young residents or less experienced radiologists.