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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.
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OBJECTIVE: To investigate in an unselected, systemic sclerosis (SSc) cohort if baseline laser speckle contrast analysis (LASCA) peripheral blood perfusion (PBP) measurements differ between 'early' SSc (without skin involvement, or 'limited' SSc-LSSc) and 'clinically overt' SSc (with skin involvement, limited cutaneous SSc-LcSSc and diffuse cutaneous SSc-DcSSc) in routine setting. METHODS: A group of twenty consecutive 'early' SSc patients and forty consecutive 'clinically overt' SSc patients (twenty LcSSc and twenty DcSSc) underwent clinical and LASCA examinations (to assess the peripheral blood perfusion [PBP] of both hands volar). RESULTS: No statistically significant difference in adjusted PBP was found in the 'early' versus the 'clinically overt' group (p = 0.77) when adjusted for possible confounding factors (e.g., vasoactive medication, active smoking, history of DTL and disease duration). A wide variability was noted when observing the individual datapoints of each subset. CONCLUSION: This study with an unselected SSc population in daily routine, non-research setting, showed there was no difference in adjusted PBP at baseline between 'early' SSc and 'clinically overt' SSc when corrected for possible confounding factors. Interestingly a wide variation of individual datapoints were observed in each subset, which emphasizes the heterogeneity of SSc.
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Objectives: The aim is to evaluate the incidental dose to the lymphatic regions in prostate-only radiotherapy (PORT) and to compare hematological outcome between PORT and whole pelvic radiotherapy (WPRT) in node-positive prostate cancer (pN1 PCa), in the era of modern radiotherapy techniques. Methods: We performed a prospective phase 3 trial in which a total of 64 pN1 PCa patients were randomized between PORT (ARM A) and WPRT (ARM B) delivered with volumetric-modulated arc therapy (VMAT). The lymph node (LN) regions were delineated separately and differences between groups were calculated using Welch t-tests. Hematological toxicity was scored according to common terminology criteria for adverse events (CTCAE) version 4.03. To evaluate differences in the evolution of red blood cell (RBC), white blood cell (WBC), and platelet count over time between PORT and WPRT, 3 linear mixed models with a random intercept for the patient was fit with model terms randomization group, study time point, and the interaction between both categorical predictors. Results: Except for dose to the obturator region, the incidental dose to the surrounding LN areas was low in ARM A. None of the patients developed severe hematological toxicity. The change in RBC from time point pre-external beam radiotherapy (EBRT) to month 3 and for WBC from time point pre-EBRT to months 3 and 12 was significantly different with ARM B showing a larger decrease. Conclusion: The incidental dose to the lymphatic areas becomes neglectable when PORT is delivered with VMAT. Hematological toxicity is very low after WPRT with VMAT and when bone marrow constraints are used for planning, although WPRT causes a decrease in RBC and WBC count over time.