Quality Improvement Report: Design and Implementation of a Radiology E-Consult Service.

Electronic consultations (e-consults) mediated through an electronic health record system or web-based platform allow synchronous or asynchronous physician-to-physician communication. E-consults have been explored in various clinical specialties, but relatively few instances in the literature describe e-consults to connect health care providers directly with radiologists.The authors outline how a radiology department can implement an e-consult service and review the development of such a service in a large academic health system. They describe the logistics, workflow, turnaround time expectations, stakeholder management, and pilot implementation and highlight challenges and lessons learned.

Outcomes After Preoperative Chemoradiation With or Without Pazopanib in Non-Rhabdomyosarcoma Soft Tissue Sarcoma: A Report From Children's Oncology Group and NRG Oncology.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.ARST1321 was a phase II study designed to compare the near complete pathologic response rate after preoperative chemoradiation with/without pazopanib in children and adults with intermediate-/high-risk chemotherapy-sensitive body wall/extremity non-Rhabdomyosarcoma Soft Tissue Sarcoma (ClinicalTrials.gov identifier: NCT02180867). Enrollment was stopped early following a predetermined interim analysis that found the rate of near complete pathologic response to be significantly greater with the addition of pazopanib. As a planned secondary aim of the study, the outcome data for this cohort were analyzed. Eight-five eligible patients were randomly assigned to receive (regimen A) or not receive (regimen B) pazopanib in combination with ifosfamide and doxorubicin + preoperative radiotherapy followed by primary resection at week 13 and then further chemotherapy at week 25. As of December 31, 2021, at a median survivor follow-up of 3.3 years (range, 0.1-5.8 years), the 3-year event-free survival for all patients in the intent-to-treat analysis was 52.5% (95% CI, 34.8 to 70.2) for regimen A and 50.6% (95% CI, 32 to 69.2) for regimen B (P = .8677, log-rank test); the 3-year overall survival was 75.7% (95% CI, 59.7 to 91.7) for regimen A and 65.4% (95% CI, 48.1 to 82.7) for regimen B (P = .1919, log-rank test). Although the rate of near complete pathologic response was significantly greater with the addition of pazopanib, outcomes were not statistically significantly different between the two regimens.

Interpretable Machine Learning for Choosing Radiation Dose-volume Constraints on Cardio-pulmonary Substructures Associated with Overall Survival in NRG Oncology RTOG 0617.

PURPOSE: Our objective was to use interpretable machine learning for choosing dose-volume constraints on cardiopulmonary substructures (CPSs) associated with overall survival (OS) in radiation therapy for locally advanced non-small cell lung cancer. METHODS AND MATERIALS: A total of 428 patients with non-small cell lung cancer were randomly divided into training/validation/test subsets (n = 230/149/49) in Radiation Therapy Oncology Group 0617. Manual or automated contouring was performed to segment CPSs, including heart, atria, ventricles, aorta, left/right ventricle/atrium (LV+RV+LA+RA), inferior/superior vena cava, pulmonary artery, and pericardium. Peri (pericardium-heart), rest (heart-[LV+RV+LA+RA]), clinical target volume (CTV), and lungs-CTV contours were also obtained. Dose-volume histogram features were extracted, including minimum/mean dose to the hottest x% volume (Dx%[Gy]/MOHx%[Gy]), minimum/mean/maximum dose, percent volume receiving at least xGy (VxGy[%]), and overlapping volume of each CPS with planning target volume (PTV_Voverlap[%]). Clinical parameters were collected from the National Clinical Trials Network/Community oncology research program data archive. Feature selection was performed using a series of multiblock sparse partial least squares regression, stability selection supervised principal component analysis, and Boruta. Explainable boosting machine (EBM) was trained using a conditional survival distribution-based approach for imputing censored data, treating survival analysis as a regression problem. Harrell's C-index was used to evaluate OS discrimination performance of EBM, Cox proportional hazards (CPH), random survival forest, extreme gradient boosting survival embeddings, and CPH deep neural network (DeepSurv) models in the test set. Dose-volume constraints were selected using the binary change point detection algorithm in Shapley additive explanations-based partial dependence functions. RESULTS: Selected features included LA_V60Gy(%), pericardium_D30%(Gy), lungs-CTV_PTV_Voverlap(%), RA_V55Gy(%), and received_cons_chemo. All models ranked LA_V60Gy(%) as the most important feature. EBM achieved the best performance for predicting OS, followed by extreme gradient boosting survival embeddings, random survival forest, DeepSurv, and CPH (C-index = 0.653, 0.646, 0.642, 0.638, and 0.632). EBM global explanations suggested that LA_V60Gy(%) < 25.6, lungs-CTV_PTV_Voverlap(%) < 1.1, pericardium_D30%(Gy) < 18.9, RA_V55Gy(%) < 19.5, and received_cons_chemo = 'Yes' for improved OS. CONCLUSIONS: EBM can be used to discriminate OS while also guiding dose-volume constraint selection for optimal management of cardiac toxicity in lung cancer radiation therapy.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials.

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

Myofibroblastoma in the Liver: A Case Report and Review of Literature.

Myofibroblastoma is a rare benign mesenchymal tumor first described in the breast. It is also known as mammary-type myofibroblastoma outside of the breast, more frequently located along the embryonic milk line. Exceptionally, myofibroblastoma can occur at visceral locations. We present a case of myofibroblastoma detected incidentally in the liver. A well-circumscribed mass, grossly measuring 6.2 cm in the liver parenchyma, was found on imaging studies. Histologically, the lesion is characterized by benign spindle cells in a hyalinized collagenous stroma, with positive staining for SMA and ER, focal positivity for CD34, negative for desmin, and loss of RB1. This rare tumor at such an unusual location makes it diagnostically challenging, especially on core biopsy of the lesion. To our knowledge, this is the second case of myofibroblastoma in the liver reported in the English literature and the first such case with a detailed pathology description.

DWI Metrics Differentiating Benign Intraductal Papillary Mucinous Neoplasms from Invasive Pancreatic Cancer: A Study in GEM Models.

KPC (KrasG12D:Trp53R172H:Pdx1-Cre) and CKS (KrasG12D:Smad4L/L:Ptf1a-Cre) mice are genetically engineered mouse (GEM) models that capture features of human pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasms (IPMN), respectively. We compared these autochthonous tumors using quantitative imaging metrics from diffusion-weighted MRI (DW-MRI) and dynamic contrast enhanced (DCE)-MRI in reference to quantitative histological metrics including cell density, fibrosis, and microvasculature density. Our results revealed distinct DW-MRI metrics between the KPC vs. CKS model (mimicking human PDAC vs. IPMN lesion): the apparent diffusion coefficient (ADC) of CKS tumors is significantly higher than that of KPC, with little overlap (mean ± SD 2.24±0.2 vs. 1.66±0.2, p<10−10) despite intratumor and intertumor variability. Kurtosis index (KI) is also distinctively separated in the two models. DW imaging metrics are consistent with growth pattern, cell density, and the cystic nature of the CKS tumors. Coregistration of ex vivo ADC maps with H&E-stained sections allowed for regional comparison and showed a correlation between local cell density and ADC value. In conclusion, studies in GEM models demonstrate the potential utility of diffusion-weighted MRI metrics for distinguishing pancreatic cancer from benign pancreatic cysts such as IPMN.

Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial.

In diffusion-weighted MRI (DW-MRI), choice of b-value influences apparent diffusion coefficient (ADC) values by probing different aspects of the tissue microenvironment. As a secondary analysis of the multicenter ECOG-ACRIN A6698 trial, the purpose of this study was to investigate the impact of alternate b-value combinations on the performance and repeatability of tumor ADC as a predictive marker of breast cancer treatment response. The final analysis included 210 women who underwent standardized 4-b-value DW-MRI (b = 0/100/600/800 s/mm2) at multiple timepoints during neoadjuvant chemotherapy treatment and a subset (n = 71) who underwent test−retest scans. Centralized tumor ADC and perfusion fraction (fp) measures were performed using variable b-value combinations. Prediction of pathologic complete response (pCR) based on the mid-treatment/12-week percent change in each metric was estimated by area under the receiver operating characteristic curve (AUC). Repeatability was estimated by within-subject coefficient of variation (wCV). Results show that two-b-value ADC calculations provided non-inferior predictive value to four-b-value ADC calculations overall (AUCs = 0.60−0.61 versus AUC = 0.60) and for HR+/HER2− cancers where ADC was most predictive (AUCs = 0.75−0.78 versus AUC = 0.76), p < 0.05. Using two b-values (0/600 or 0/800 s/mm2) did not reduce ADC repeatability over the four-b-value calculation (wCVs = 4.9−5.2% versus 5.4%). The alternate metrics ADCfast (b ≤ 100 s/mm2), ADCslow (b ≥ 100 s/mm2), and fp did not improve predictive performance (AUCs = 0.54−0.60, p = 0.08−0.81), and ADCfast and fp demonstrated the lowest repeatability (wCVs = 6.71% and 12.4%, respectively). In conclusion, breast tumor ADC calculated using a simple two-b-value approach can provide comparable predictive value and repeatability to full four-b-value measurements as a marker of treatment response.

Repeatability and Reproducibility Assessment of the Apparent Diffusion Coefficient in the Prostate: A Trial of the ECOG-ACRIN Research Group (ACRIN 6701).

BACKGROUND: Uncertainty regarding the reproducibility of the apparent diffusion coefficient (ADC) hampers the use of quantitative diffusion-weighted imaging (DWI) in evaluation of the prostate with magnetic resonance imaging MRI. The quantitative imaging biomarkers alliance (QIBA) profile for quantitative DWI claims a within-subject coefficient of variation (wCV) for prostate lesion ADC of 0.17. Improved understanding of ADC reproducibility would aid the use of quantitative diffusion in prostate MRI evaluation. PURPOSE: Evaluation of the repeatability (same-day) and reproducibility (multi-day) of whole-prostate and focal-lesion ADC assessment in a multi-site setting. STUDY TYPE: Prospective multi-institutional. SUBJECTS: Twenty-nine males, ages 53 to 80 (median 63) years, following diagnosis of prostate cancer, 10 with focal lesions. FIELD STRENGTH/SEQUENCE: 3T, single-shot spin-echo diffusion-weighted echo-planar sequence with four b-values. ASSESSMENT: Sites qualified for the study using an ice-water phantom with known ADC. Readers performed DWI analyses at visit 1 ("V1") and visit 2 ("V2," 2-14 days after V1), where V2 comprised scans before ("V2pre") and after ("V2post") a "coffee-break" interval with subject removal and repositioning. A single reader segmented the whole prostate. Two readers separately placed region-of-interests for focal lesions. STATISTICAL TESTS: Reproducibility and repeatability coefficients for whole prostate and focal lesions derived from median pixel ADC. We estimated the wCV and 95% confidence interval using a variance stabilizing transformation and assessed interreader reliability of focal lesion ADC using the intraclass correlation coefficient (ICC). RESULTS: The ADC biases from b0 -b600 and b0 -b800 phantom scans averaged 1.32% and 1.44%, respectively; mean b-value dependence was 0.188%. Repeatability and reproducibility of whole prostate median pixel ADC both yielded wCVs of 0.033 (N = 29). In 10 subjects with an evaluable focal lesion, the individual reader wCVs were 0.148 and 0.074 (repeatability) and 0.137 and 0.078 (reproducibility). All time points demonstrated good to excellent interreader reliability for focal lesion ADC (ICCV1  = 0.89; ICCV2pre  = 0.76; ICCV2post  = 0.94). DATA CONCLUSION: This study met the QIBA claim for prostate ADC. Test-retest repeatability and multi-day reproducibility were largely equivalent. Interreader reliability for focal lesion ADC was high across time points. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2 TOC CATEGORY: Pelvis.

Effect of contrast dose on diagnostic performance in DCE-MR breast imaging.

OBJECTIVE: To assess the diagnostic performance of breast magnetic resonance (MR) imaging as a function of gadolinium contrast dose using a retrospective reader study. MATERIAL AND METHODS: IRB approval was obtained prior to the start of this study and was HIPAA compliant. One-hundred and fifty MR breast examinations were included that were acquired between January 2001 and December 2006. Seventy-five patients received contrast doses (gadopentetate dimeglumine) by weight of 0.10 mmol/kg and 75 patients were imaged using fixed volumes of 20 ml. The images were assessed by two radiologists with performance calculated for each reader as well as a combined assessment. Dose response was measured by comparing performance between cases binned by dose: <=0.10; >0.10; and >0.13 mmol/kg. Statistical significance was calculated using a one-sided Z-test for differences in proportions with interobserver agreement calculated using Cohen's kappa statistics. RESULTS: In the combined reader assessment with equivocal lesions classified as negative, sensitivity rose from 66% (19/29) to 92% (24/26, P < 0.01) and 95% (18/19, P < 0.01) with the specificity also increasing from 65% (32/49) to 87% (40/46, P < 0.01) and 86% (32/37, P = 0.01) corresponding to doses <=0.10, >0.10, >0.13 mmol/kg. With equivocal lesions classified as positive, sensitivity rose from 79% (23/29) to 92% (24/26, P < 0.10) and 95% (18/19, P < 0.10) Specificity also increased from 53% (26/49) to 72% (33/46, P < 0.05) and 70% (26/37, P = 0.05) with increasing dose. Interobserver agreement also improved at the higher doses.

Pathological response in children and adults with large unresected intermediate-grade or high-grade soft tissue sarcoma receiving preoperative chemoradiotherapy with or without pazopanib (ARST1321): a multicentre, randomised, open-label, phase 2 trial.

BACKGROUND: Outcomes for children and adults with advanced soft tissue sarcoma are poor with traditional therapy. We investigated whether the addition of pazopanib to preoperative chemoradiotherapy would improve pathological near complete response rate compared with chemoradiotherapy alone. METHODS: In this joint Children's Oncology Group and NRG Oncology multicentre, randomised, open-label, phase 2 trial, we enrolled eligible adults (aged ≥18 years) and children (aged between 2 and <18 years) from 57 hospitals in the USA and Canada with unresected, newly diagnosed trunk or extremity chemotherapy-sensitive soft tissue sarcoma, which were larger than 5 cm in diameter and of intermediate or high grade. Eligible patients had Lansky (if aged ≤16 years) or Karnofsky (if aged >16 years) performance status score of at least 70. Patients received ifosfamide (2·5 g/m2 per dose intravenously on days 1-3 with mesna) and doxorubicin (37·5 mg/m2 per dose intravenously on days 1-2) with 45 Gy preoperative radiotherapy, followed by surgical resection at week 13. Patients were randomly assigned (1:1) using a web-based system, in an unmasked manner, to receive oral pazopanib (if patients <18 years 350 mg/m2 once daily; if patients ≥18 years 600 mg once daily) or not (control group), with pazopanib not given immediately before or after surgery at week 13. The study projected 100 randomly assigned patients were needed to show an improvement in the number of participants with a 90% or higher pathological response at week 13 from 40% to 60%. Analysis was done per protocol. This study has completed accrual and is registered with ClinicalTrials.gov, NCT02180867. FINDINGS: Between July 7, 2014, and Oct 1, 2018, 81 eligible patients were enrolled and randomly assigned to the pazopanib group (n=42) or the control group (n=39). At the planned second interim analysis with 42 evaluable patients and a median follow-up of 0·8 years (IQR 0·3-1·6) in the pazopanib group and 1 year (0·3-1·6) in the control group, the number of patients with a 90% pathological response or higher was 14 (58%) of 24 patients in the pazopanib group and four (22%) of 18 patients in the control group, with a between-group difference in the number of 90% or higher pathological response of 36·1% (83·8% CI 16·5-55·8). On the basis of an interim analysis significance level of 0·081 (overall one-sided significance level of 0·20, power of 0·80, and O'Brien-Fleming-type cumulative error spending function), the 83·8% CI for response difference was between 16·5% and 55·8% and thus excluded 0. The improvement in pathological response rate with the addition of pazopanib crossed the predetermined boundary and enrolment was stopped. The most common grade 3-4 adverse events were leukopenia (16 [43%] of 37 patients), neutropenia (15 [41%]), and febrile neutropenia (15 [41%]) in the pazopanib group, and neutropenia (three [9%] of 35 patients) and febrile neutropenia (three [9%]) in the control group. 22 (59%) of 37 patients in the pazopanib group had a pazopanib-related serious adverse event. Paediatric and adult patients had a similar number of grade 3 and 4 toxicity. There were seven deaths (three in the pazopanib group and four in the control group), none of which were treatment related. INTERPRETATION: In this presumed first prospective trial of soft tissue sarcoma spanning nearly the entire age spectrum, adding pazopanib to neoadjuvant chemoradiotherapy improved the rate of pathological near complete response, suggesting that this is a highly active and feasible combination in children and adults with advanced soft tissue sarcoma. The comparison of survival outcomes requires longer follow-up. FUNDING: National Institutes of Health, St Baldrick's Foundation, Seattle Children's Foundation.

Dextran-Coated Cerium Oxide Nanoparticles: A Computed Tomography Contrast Agent for Imaging the Gastrointestinal Tract and Inflammatory Bowel Disease.

Computed tomography (CT) is an X-ray-based medical imaging technique commonly used for noninvasive gastrointestinal tract (GIT) imaging. Iodine- and barium-based CT contrast agents are used in the clinic for GIT imaging; however, inflammatory bowel disease (IBD) imaging is challenging since iodinated and barium-based CT agents are not specific for sites of inflammation. Cerium oxide nanoparticles (CeNP) can produce strong X-ray attenuation due to cerium's k-edge at 40.4 keV but have not yet been explored for CT imaging. In addition, we hypothesized that the use of dextran as a coating material on cerium oxide nanoparticles would encourage accumulation in IBD inflammation sites in a similar fashion to other inflammatory diseases. In this study, therefore, we sought to develop a CT contrast agent, i.e., dextran-coated cerium oxide nanoparticles (Dex-CeNP) for GIT imaging with IBD. We synthesized Dex-CeNP, characterized them using various analytical tools, and examined their in vitro biocompatibility, CT contrast generation, and protective effect against oxidative stress. In vivo CT imaging was done with both healthy mice and a dextran sodium sulfate induced colitis mouse model. Dex-CeNP's CT contrast generation and accumulation in inflammation sites were compared with iopamidol, an FDA approved CT contrast agent. Dex-CeNP was found to be protective against oxidative damage. Dex-CeNP produced strong CT contrast and accumulated in the colitis area of large intestines. In addition, >97% of oral doses were cleared from the body within 24 h. Therefore, Dex-CeNP can be used as a potential CT contrast agent for imaging GIT with IBD while protecting against oxidative damage.

Platinum response characteristics of patients with pancreatic ductal adenocarcinoma and a germline BRCA1, BRCA2 or PALB2 mutation.

BACKGROUND: Retrospective studies suggest a survival benefit when platinum-based chemotherapy is administered to patients with pancreatic cancer harbouring a germline mutation in BRCA1, BRCA2 or PALB2 (mut-positive PDAC). However, the objective response rate (ORR) and real-world progression free survival (rwPFS) achieved with such treatment remain ill-defined. METHODS: Twenty-six patients with advanced-stage mut-positive PDAC who had been treated with platinum-based therapy were matched by age, race and sex to 52 platinum-treated control PDAC patients. Responses to therapy were determined by RECIST v1.1, performed by blinded radiology review. Measured outcomes included ORR and rwPFS. RESULTS: The ORR in mut-positive patients was 58% compared to 21% in the control group (p = 0.0022). There was no significant difference in ORR between platinum regimens in mut-positive patients (p = 0.814), whereas in control patients, the only observed responses were to FOLFIRINOX. rwPFS was 10.1 mo. for mut-positive patients and 6.9 mo. for controls (HR 0.43; 95% CI 0.25-0.74; 0.0068). CONCLUSION: Mut-positive PDAC has a high ORR and prolonged rwPFS to platinum-based chemotherapy. These findings may have implications particularly in the neoadjuvant setting, and for future clinical trial design, and highlight the importance of early germline testing in patients with PDAC.

Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study.

BACKGROUND: For most computer-aided diagnosis (CAD) problems involving prostate cancer detection via medical imaging data, the choice of classifier has been largely ad hoc, or been motivated by classifier comparison studies that have involved large synthetic datasets. More significantly, it is currently unknown how classifier choices and trends generalize across multiple institutions, due to heterogeneous acquisition and intensity characteristics (especially when considering MR imaging data). In this work, we empirically evaluate and compare a number of different classifiers and classifier ensembles in a multi-site setting, for voxel-wise detection of prostate cancer (PCa) using radiomic texture features derived from high-resolution in vivo T2-weighted (T2w) MRI. METHODS: Twelve different supervised classifier schemes: Quadratic Discriminant Analysis (QDA), Support Vector Machines (SVMs), naïve Bayes, Decision Trees (DTs), and their ensemble variants (bagging, boosting), were compared in terms of classification accuracy as well as execution time. Our study utilized 85 prostate cancer T2w MRI datasets acquired from across 3 different institutions (1 for discovery, 2 for independent validation), from patients who later underwent radical prostatectomy. Surrogate ground truth for disease extent on MRI was established by expert annotation of pre-operative MRI through spatial correlation with corresponding ex vivo whole-mount histology sections. Classifier accuracy in detecting PCa extent on MRI on a per-voxel basis was evaluated via area under the ROC curve. RESULTS: The boosted DT classifier yielded the highest cross-validated AUC (= 0.744) for detecting PCa in the discovery cohort. However, in independent validation, the boosted QDA classifier was identified as the most accurate and robust for voxel-wise detection of PCa extent (AUCs of 0.735, 0.683, 0.768 across the 3 sites). The next most accurate and robust classifier was the single QDA classifier, which also enjoyed the advantage of significantly lower computation times compared to any of the other methods. CONCLUSIONS: Our results therefore suggest that simpler classifiers (such as QDA and its ensemble variants) may be more robust, accurate, and efficient for prostate cancer CAD problems, especially in the context of multi-site validation.

Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial.

BACKGROUND: Quantitative diffusion-weighted imaging (DWI) MRI is a promising technique for cancer characterization and treatment monitoring. Knowledge of the reproducibility of DWI metrics in breast tumors is necessary to apply DWI as a clinical biomarker. PURPOSE: To evaluate the repeatability and reproducibility of breast tumor apparent diffusion coefficient (ADC) in a multi-institution clinical trial setting, using standardized DWI protocols and quality assurance (QA) procedures. STUDY TYPE: Prospective. SUBJECTS: In all, 89 women from nine institutions undergoing neoadjuvant chemotherapy for invasive breast cancer. FIELD STRENGTH/SEQUENCE: DWI was acquired before and after patient repositioning using a four b-value, single-shot echo-planar sequence at 1.5T or 3.0T. ASSESSMENT: A QA procedure by trained operators assessed artifacts, fat suppression, and signal-to-noise ratio, and determine study analyzability. Mean tumor ADC was measured via manual segmentation of the multislice tumor region referencing DWI and contrast-enhanced images. Twenty cases were evaluated multiple times to assess intra- and interoperator variability. Segmentation similarity was assessed via the Sørenson-Dice similarity coefficient. STATISTICAL TESTS: Repeatability and reproducibility were evaluated using within-subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), agreement index (AI), and repeatability coefficient (RC). Correlations were measured by Pearson's correlation coefficients. RESULTS: In all, 71 cases (80%) passed QA evaluation: 44 at 1.5T, 27 at 3.0T; 60 pretreatment, 11 after 3 weeks of taxane-based treatment. ADC repeatability was excellent: wCV = 4.8% (95% confidence interval [CI] 4.0, 5.7%), ICC = 0.97 (95% CI 0.95, 0.98), AI = 0.83 (95% CI 0.76, 0.87), and RC = 0.16 * 10-3 mm2 /sec (95% CI 0.13, 0.19). The results were similar across field strengths and timepoint subgroups. Reproducibility was excellent: interreader ICC = 0.92 (95% CI 0.80, 0.97) and intrareader ICC = 0.91 (95% CI 0.78, 0.96). DATA CONCLUSION: Breast tumor ADC can be measured with excellent repeatability and reproducibility in a multi-institution setting using a standardized protocol and QA procedure. Improvements to DWI image quality could reduce loss of data in clinical trials. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1617-1628.

Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial.

Purpose To determine if the change in tumor apparent diffusion coefficient (ADC) at diffusion-weighted (DW) MRI is predictive of pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer. Materials and Methods In this prospective multicenter study, 272 consecutive women with breast cancer were enrolled at 10 institutions (from August 2012 to January 2015) and were randomized to treatment with 12 weekly doses of paclitaxel (with or without an experimental agent), followed by 12 weeks of treatment with four cycles of anthracycline. Each woman underwent breast DW MRI before treatment, at early treatment (3 weeks), at midtreatment (12 weeks), and after treatment. Percentage change in tumor ADC from that before treatment (ΔADC) was measured at each time point. Performance for predicting pCR was assessed by using the area under the receiver operating characteristic curve (AUC) for the overall cohort and according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. Results The final analysis included 242 patients with evaluable serial imaging data, with a mean age of 48 years ± 10 (standard deviation); 99 patients had HR-positive (hereafter, HR+)/HER2-negative (hereafter, HER2-) disease, 77 patients had HR-/HER2- disease, 42 patients had HR+/HER2+ disease, and 24 patients had HR-/HER2+ disease. Eighty (33%) of 242 patients experienced pCR. Overall, ΔADC was moderately predictive of pCR at midtreatment/12 weeks (AUC = 0.60; 95% confidence interval [CI]: 0.52, 0.68; P = .017) and after treatment (AUC = 0.61; 95% CI: 0.52, 0.69; P = .013). Across the four disease subtypes, midtreatment ΔADC was predictive only for HR+/HER2- tumors (AUC = 0.76; 95% CI: 0.62, 0.89; P < .001). In a test subset, a model combining tumor subtype and midtreatment ΔADC improved predictive performance (AUC = 0.72; 95% CI: 0.61, 0.83) over ΔADC alone (AUC = 0.57; 95% CI: 0.44, 0.70; P = .032.). Conclusion After 12 weeks of therapy, change in breast tumor apparent diffusion coefficient at MRI predicts complete pathologic response to neoadjuvant chemotherapy. © RSNA, 2018 Online supplemental material is available for this article.

MRI, Clinical Examination, and Mammography for Preoperative Assessment of Residual Disease and Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer: ACRIN 6657 Trial.

OBJECTIVE: The objective of our study was to determine the accuracy of preoperative measurements for detecting pathologic complete response (CR) and assessing residual disease after neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer. SUBJECTS AND METHODS: The American College of Radiology Imaging Network 6657 Trial prospectively enrolled women with ≥ 3 cm invasive breast cancer receiving NACT. Preoperative measurements of residual disease included longest diameter by mammography, MRI, and clinical examination and functional volume on MRI. The accuracy of preoperative measurements for detecting pathologic CR and the association with final pathology size were assessed for all lesions, separately for single masses and nonmass enhancements (NMEs), multiple masses, and lesions without ductal carcinoma in situ (DCIS). RESULTS: In the 138 women with all four preoperative measures, longest diameter by MRI showed the highest accuracy for detecting pathologic CR for all lesions and NME (AUC = 0.76 and 0.84, respectively). There was little difference across preoperative measurements in the accuracy of detecting pathologic CR for single masses (AUC = 0.69-0.72). Longest diameter by MRI and longest diameter by clinical examination showed moderate ability for detecting pathologic CR for multiple masses (AUC = 0.78 and 0.74), and longest diameter by MRI and longest diameter by mammography showed moderate ability for detecting pathologic CR for tumors without DCIS (AUC = 0.74 and 0.71). In subjects with residual disease, longest diameter by MRI exhibited the strongest association with pathology size for all lesions and single masses (r = 0.33 and 0.47). Associations between preoperative measures and pathology results were not significantly influenced by tumor subtype or mammographic density. CONCLUSION: Our results indicate that measurement of longest diameter by MRI is more accurate than by mammography and clinical examination for preoperative assessment of tumor residua after NACT and may improve surgical planning.

Antiangiogenic tyrosine kinase inhibitors in colorectal cancer: is there a path to making them more effective?

Antiangiogenic therapy has a proven survival benefit in metastatic colorectal cancer. Inhibition of the VEGF pathway using a variety of extracellular antibody approaches has clear benefit in combination with chemotherapy, while intracellular blockade using tyrosine kinase inhibitors (TKIs) such as sorafenib and regorafenib has had more limited success. Pharmacodynamic modeling using modalities such as DCE-MRI indicates potent antiangiogenic effects of these TKIs, yet numerous combination therapies, primarily with chemotherapy, have failed to demonstrate an additive benefit. The sole comparative study of a single agent TKI against placebo showed a survival benefit of regorafenib in patients with advanced, refractory disease. Preclinical data demonstrate synergy between antiantiogenic TKIs and targeted interventions including autophagy inhibition, and together with a renewed effort to define markers of susceptibility, such combinations may be a way to improve the limited efficacy of this once-promising drug class.