Development and multicenter validation of a multiparametric imaging model to predict treatment response in rectal cancer.

OBJECTIVES: To develop and validate a multiparametric model to predict neoadjuvant treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI dataset. METHODS: Baseline staging MRIs (T2W (T2-weighted)-MRI, diffusion-weighted imaging (DWI) / apparent diffusion coefficient (ADC)) of 509 patients (9 centres) treated with neoadjuvant chemoradiotherapy (CRT) were collected. Response was defined as (1) complete versus incomplete response, or (2) good (Mandard tumor regression grade (TRG) 1-2) versus poor response (TRG3-5). Prediction models were developed using combinations of the following variable groups: (1) Non-imaging: age/sex/tumor-location/tumor-morphology/CRT-surgery interval (2) Basic staging: cT-stage/cN-stage/mesorectal fascia involvement, derived from (2a) original staging reports, or (2b) expert re-evaluation (3) Advanced staging: variables from 2b combined with cTN-substaging/invasion depth/extramural vascular invasion/tumor length (4) Quantitative imaging: tumour volume + first-order histogram features (from T2W-MRI and DWI/ADC) Models were developed with data from 6 centers (n = 412) using logistic regression with the Least Absolute Shrinkage and Selector Operator (LASSO) feature selection, internally validated using repeated (n = 100) random hold-out validation, and externally validated using data from 3 centers (n = 97). RESULTS: After external validation, the best model (including non-imaging and advanced staging variables) achieved an area under the curve of 0.60 (95%CI=0.48-0.72) to predict complete response and 0.65 (95%CI=0.53-0.76) to predict a good response. Quantitative variables did not improve model performance. Basic staging variables consistently achieved lower performance compared to advanced staging variables. CONCLUSIONS: Overall model performance was moderate. Best results were obtained using advanced staging variables, highlighting the importance of good-quality staging according to current guidelines. Quantitative imaging features had no added value (in this heterogeneous dataset). CLINICAL RELEVANCE STATEMENT: Predicting tumour response at baseline could aid in tailoring neoadjuvant therapies for rectal cancer. This study shows that image-based prediction models are promising, though are negatively affected by variations in staging quality and MRI acquisition, urging the need for harmonization. KEY POINTS: This multicenter study combining clinical information and features derived from MRI rendered disappointing performance to predict response to neoadjuvant treatment in rectal cancer. Best results were obtained with the combination of clinical baseline information and state-of-the-art image-based staging variables, highlighting the importance of good quality staging according to current guidelines and staging templates. No added value was found for quantitative imaging features in this multicenter retrospective study. This is likely related to acquisition variations, which is a major problem for feature reproducibility and thus model generalizability.

Sources of variation in multicenter rectal MRI data and their effect on radiomics feature reproducibility.

OBJECTIVES: To investigate sources of variation in a multicenter rectal cancer MRI dataset focusing on hardware and image acquisition, segmentation methodology, and radiomics feature extraction software. METHODS: T2W and DWI/ADC MRIs from 649 rectal cancer patients were retrospectively acquired in 9 centers. Fifty-two imaging features (14 first-order/6 shape/32 higher-order) were extracted from each scan using whole-volume (expert/non-expert) and single-slice segmentations using two different software packages (PyRadiomics/CapTk). Influence of hardware, acquisition, and patient-intrinsic factors (age/gender/cTN-stage) on ADC was assessed using linear regression. Feature reproducibility was assessed between segmentation methods and software packages using the intraclass correlation coefficient. RESULTS: Image features differed significantly (p < 0.001) between centers with more substantial variations in ADC compared to T2W-MRI. In total, 64.3% of the variation in mean ADC was explained by differences in hardware and acquisition, compared to 0.4% by patient-intrinsic factors. Feature reproducibility between expert and non-expert segmentations was good to excellent (median ICC 0.89-0.90). Reproducibility for single-slice versus whole-volume segmentations was substantially poorer (median ICC 0.40-0.58). Between software packages, reproducibility was good to excellent (median ICC 0.99) for most features (first-order/shape/GLCM/GLRLM) but poor for higher-order (GLSZM/NGTDM) features (median ICC 0.00-0.41). CONCLUSIONS: Significant variations are present in multicenter MRI data, particularly related to differences in hardware and acquisition, which will likely negatively influence subsequent analysis if not corrected for. Segmentation variations had a minor impact when using whole volume segmentations. Between software packages, higher-order features were less reproducible and caution is warranted when implementing these in prediction models. KEY POINTS: • Features derived from T2W-MRI and in particular ADC differ significantly between centers when performing multicenter data analysis. • Variations in ADC are mainly (> 60%) caused by hardware and image acquisition differences and less so (< 1%) by patient- or tumor-intrinsic variations. • Features derived using different image segmentations (expert/non-expert) were reproducible, provided that whole-volume segmentations were used. When using different feature extraction software packages with similar settings, higher-order features were less reproducible.

Short-term Results of the RAPID Randomized Trial of the Legflow Paclitaxel-Eluting Balloon With Supera Stenting vs Supera Stenting Alone for the Treatment of Intermediate and Long Superficial Femoral Artery Lesions.

PURPOSE: To report a randomized trial comparing the Legflow paclitaxel-eluting balloon (PEB) + Supera stenting to Supera stenting alone in patients with intermediate to long superficial femoral artery (SFA) lesions. METHODS: The multicenter RAPID trial ( controlled-trials.com ; identifier ISRCTN47846578) randomized (1:1) 160 patients (mean age 67 years; 102 men) with Rutherford category 2-6 ischemia to treatment with Legflow PEB + Supera stent or Supera stent alone in intermediate to long SFA lesions (mean lesion length 15.8±7.4 vs 15.8±7.6 cm, respectively). The efficacy outcome was primary patency, defined as freedom from restenosis on duplex ultrasound or angiography. RESULTS: Baseline characteristics including the percentage of occlusions were similar between groups. In the intention-to-treat analysis, the estimated primary patency at 1 year was 68.3% (95% CI 56.7% to 79.9%) in the PEB + Supera group vs 62.0% (95% CI 49.1% to 74.9%) in the Supera group (p=0.900). Per-protocol analysis showed a 12-month primary patency estimate of 74.7% (95% CI 63.1% to 86.3%) in the PEB + Supera group vs 62.0% (95% CI 49.1% to 74.9%) in the control group (p=0.273). Secondary patency estimates at 12 months (per-protocol analysis) were 89.0% (95% CI 80.6% to 97.4%) vs 98.0% (95% CI 94.1% to 100%; p=0.484); the estimates for freedom from clinically driven target lesion revascularization (CD-TLR) were 83.0% (95% CI 72.8% to 93.2%) and 77.8% (95% CI 66.6% to 89.0%; p=0.277), respectively. CONCLUSION: The short-term results from the multicenter RAPID randomized controlled trial indicate that the Legflow PEB is safe and feasible for the treatment of intermediate to long SFA lesions. In this trial, at least 70% of the patients suffered an occlusion. The PEB group had higher rates of primary patency and freedom from CD-TLR, although there were no statistically significant differences vs controls.

Association between microscopic brain damage as indicated by magnetization transfer imaging and anticardiolipin antibodies in neuropsychiatric lupus.

The pathogenetic role of anticardiolipin antibodies (aCLs) in patients with neuropsychiatric systemic lupus erythematosus (NPSLE) without cerebral infarcts remains elusive. Magnetization transfer imaging (MTI) has proved to be a sensitive tool for detecting diffuse microscopic brain damage in NPSLE patients. In this study we examined the correlation between grey and white matter magnetization transfer ratio (MTR) parameters and the presence of IgM and IgG aCLs and lupus anticoagulant in 18 patients with systemic lupus erythematosus and a history of NPSLE but without cerebral infarcts on conventional magnetic resonance imaging. Lower grey matter mean MTR (P < 0.05), white matter mean MTR (P < 0.05), white matter peak location (P < 0.05) and grey matter peak location (trend toward statistical significance) were observed in IgM aCL-positive patients than in IgM aCL-negative patients. No significant differences were found in MTR histogram parameters with respect to IgG aCL and lupus anticoagulant status, nor with respect to anti-dsDNA or anti-ENA (extractable nuclear antigen) status. This is the first report of an association between the presence of aCLs and cerebral damage in grey and white matter in NPSLE. Our findings suggest that aCLs are associated with diffuse brain involvement in NPSLE patients.

Systemic lupus erythematosus: diagnostic application of magnetization transfer ratio histograms in patients with neuropsychiatric symptoms--initial results.

PURPOSE: To explore the diagnostic potential of magnetization transfer ratio (MTR) histogram analysis in patients with neuropsychiatric systemic lupus erythematosus (SLE) by using multivariate discriminant analysis (MDA). MATERIALS AND METHODS: Volumetric magnetization transfer imaging was performed in nine patients with active non-thromboembolic, neuropsychiatric SLE, 10 patients with SLE who had had neuropsychiatric SLE previously, 10 patients with SLE but no history of neuropsychiatric SLE, 10 patients with inactive multiple sclerosis, and 10 healthy control subjects. For each subject, an MTR histogram of the whole brain was generated, and an MDA score was produced for each histogram. Each patient was assigned to a clinical subgroup on the basis of these MDA scores. For assignment, binary comparisons between subgroups were made. The accuracy of this classification method was assessed and compared with that of conventional MTR histogram analysis. RESULTS: With MDA, the success rate of binary classification was 60%-100%, depending on which two groups were compared. When the different clinical subgroups were separated, MDA parameters were always better than conventional MTR histogram parameters, with P values ranging from.05 to less than 1 x 10(-6) of those attained with the best conventional parameter. CONCLUSION: With MDA, MTR histograms of brain tissue may provide diagnostic information for individual patients in the clinical context of SLE.