Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis.

The objective of this study is to define CT imaging derived phenotypes for patients with hepatic steatosis, a common metabolic liver condition, and determine its association with patient data from a medical biobank. There is a need to further characterize hepatic steatosis in lean patients, as its epidemiology may differ from that in overweight patients. A deep learning method determined the spleen-hepatic attenuation difference (SHAD) in Hounsfield Units (HU) on abdominal CT scans as a quantitative measure of hepatic steatosis. The patient cohort was stratified by BMI with a threshold of 25 kg/m2 and hepatic steatosis with threshold SHAD ≥ - 1 HU or liver mean attenuation ≤ 40 HU. Patient characteristics, diagnoses, and laboratory results representing metabolism and liver function were investigated. A phenome-wide association study (PheWAS) was performed for the statistical interaction between SHAD and the binary characteristic LEAN. The cohort contained 8914 patients-lean patients with (N = 278, 3.1%) and without (N = 1867, 20.9%) steatosis, and overweight patients with (N = 1863, 20.9%) and without (N = 4906, 55.0%) steatosis. Among all lean patients, those with steatosis had increased rates of cardiovascular disease (41.7 vs 27.8%), hypertension (86.7 vs 49.8%), and type 2 diabetes mellitus (29.1 vs 15.7%) (all p < 0.0001). Ten phenotypes were significant in the PheWAS, including chronic kidney disease, renal failure, and cardiovascular disease. Hepatic steatosis was found to be associated with cardiovascular, kidney, and metabolic conditions, separate from overweight BMI.

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.

The Importance of Quality Assurance in Radiation Oncology Clinical Trials.

Clinical trials have been the center of progress in modern medicine. In oncology, we are fortunate to have a structure in place through the National Clinical Trials Network (NCTN). The NCTN provides the infrastructure and a forum for scientific discussion to develop clinical concepts for trial design. The NCTN also provides a network group structure to administer trials for successful trial management and outcome analyses. There are many important aspects to trial design and conduct. Modern trials need to ensure appropriate trial conduct and secure data management processes. Of equal importance is the quality assurance of a clinical trial. If progress is to be made in oncology clinical medicine, investigators and patient care providers of service need to feel secure that trial data is complete, accurate, and well-controlled in order to be confident in trial analysis and move trial outcome results into daily practice. As our technology has matured, so has our need to apply technology in a uniform manner for appropriate interpretation of trial outcomes. In this article, we review the importance of quality assurance in clinical trials involving radiation therapy. We will include important aspects of institution and investigator credentialing for participation as well as ongoing processes to ensure that each trial is being managed in a compliant manner. We will provide examples of the importance of complete datasets to ensure study interpretation. We will describe how successful strategies for quality assurance in the past will support new initiatives moving forward.

Prospective Correlation of Magnetic Resonance Tumor Regression Grade With Pathologic Outcomes in Total Neoadjuvant Therapy for Rectal Adenocarcinoma.

PURPOSE: Total neoadjuvant therapy (TNT) is a newly established standard treatment for rectal adenocarcinoma. Current methods to communicate magnitudes of regression during TNT are subjective and imprecise. Magnetic resonance tumor regression grade (MR-TRG) is an existing, but rarely used, regression grading system. Prospective validation of MR-TRG correlation with pathologic response in patients undergoing TNT is lacking. Utility of adding diffusion-weighted imaging to MR-TRG is also unknown. METHODS: We conducted a multi-institutional prospective imaging substudy within NRG-GI002 (ClinicalTrials.gov identifier: NCT02921256) examining the ability of MR-based imaging to predict pathologic complete response (pCR) and correlate MR-TRG with the pathologic neoadjuvant response score (NAR). Serial MRIs were needed from 110 patients. Three radiologists independently, then collectively, reviewed each MRI for complete response (mriCR), which was tested for positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity with pCR. MR-TRG was examined for association with the pathologic NAR score. All team members were blinded to pathologic data. RESULTS: A total of 121 patients from 71 institutions met criteria: 28% were female (n = 34), 84% White (n = 101), and median age was 55 (24-78 years). Kappa scores for T- and N-stage after TNT were 0.38 and 0.88, reflecting fair agreement and near-perfect agreement, respectively. Calling an mriCR resulted in a kappa score of 0.82 after chemotherapy and 0.56 after TNT reflected near-perfect agreement and moderate agreement, respectively. MR-TRG scores were associated with pCR (P < .01) and NAR (P < .0001), PPV for pCR was 40% (95% CI, 26 to 53), and NPV was 84% (95% CI, 75 to 94). CONCLUSION: MRI alone is a poor tool to distinguish pCR in rectal adenocarcinoma undergoing TNT. However, the MR-TRG score presents a now validated method, correlated with pathologic NAR, which can objectively measure regression magnitude during TNT.

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.

Impact of Arterial Input Function and Pharmacokinetic Models on DCE-MRI Biomarkers for Detection of Vascular Effect Induced by Stroma-Directed Drug in an Orthotopic Mouse Model of Pancreatic Cancer.

PURPOSE: We demonstrated earlier in mouse models of pancreatic ductal adenocarcinoma (PDA) that Ktrans derived from dynamic contrast-enhanced (DCE) MRI detected microvascular effect induced by PEGPH20, a hyaluronidase which removes stromal hyaluronan, leading to reduced interstitial fluid pressure in the tumor (Clinical Cancer Res (2019) 25: 2314-2322). How the choice of pharmacokinetic (PK) model and arterial input function (AIF) may impact DCE-derived markers for detecting such an effect is not known. PROCEDURES: Retrospective analyses of the DCE-MRI of the orthotopic PDA model are performed to examine the impact of individual versus group AIF combined with Tofts model (TM), extended-Tofts model (ETM), or shutter-speed model (SSM) on the ability to detect the microvascular changes induced by PEGPH20 treatment. RESULTS: Individual AIF exhibit a marked difference in peak gadolinium concentration. However, across all three PK models, kep values show a significant correlation between individual versus group-AIF (p < 0.01). Regardless individual or group AIF, when kep is obtained from fitting the DCE-MRI data using the SSM, kep shows a significant increase after PEGPH20 treatment (p < 0.05 compared to the baseline); %change of kep from baseline to post-treatment is also significantly different between PEGPH20 versus vehicle group (p < 0.05). In comparison, when kep is derived from the TM, only the use of individual AIF leads to a significant increase of kep after PEGPH20 treatment, whereas the %change of kep is not different between PEGPH20 versus vehicle group. Group AIF but not individual AIF allows detection of a significant increase of Vp (derived from the ETM) in PEGPH20 versus vehicle group (p < 0.05). Increase of Vp is consistent with a large increase of mean capillary lumen area estimated from immunostaining. CONCLUSION: Our results suggest that kep derived from SSM and Vp from ETM, both using group AIF, are optimal for the detection of microvascular changes induced by stroma-directed drug PEGPH20. These analyses provide insights in the choice of PK model and AIF for optimal DCE protocol design in mouse pancreatic cancer models.

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.

Quality improvements in radiation oncology clinical trials.

Clinical trials have become the primary mechanism to validate process improvements in oncology clinical practice. Over the past two decades there have been considerable process improvements in the practice of radiation oncology within the structure of a modern department using advanced technology for patient care. Treatment planning is accomplished with volume definition including fusion of multiple series of diagnostic images into volumetric planning studies to optimize the definition of tumor and define the relationship of tumor to normal tissue. Daily treatment is validated by multiple tools of image guidance. Computer planning has been optimized and supported by the increasing use of artificial intelligence in treatment planning. Informatics technology has improved, and departments have become geographically transparent integrated through informatics bridges creating an economy of scale for the planning and execution of advanced technology radiation therapy. This serves to provide consistency in department habits and improve quality of patient care. Improvements in normal tissue sparing have further improved tolerance of treatment and allowed radiation oncologists to increase both daily and total dose to target. Radiation oncologists need to define a priori dose volume constraints to normal tissue as well as define how image guidance will be applied to each radiation treatment. These process improvements have enhanced the utility of radiation therapy in patient care and have made radiation therapy an attractive option for care in multiple primary disease settings. In this chapter we review how these changes have been applied to clinical practice and incorporated into clinical trials. We will discuss how the changes in clinical practice have improved the quality of clinical trials in radiation therapy. We will also identify what gaps remain and need to be addressed to offer further improvements in radiation oncology clinical trials and patient care.

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.

The Course of LIRADS 3 and 4 Hepatic Abnormalities as Correlated With Explant Pathology: A Single Center Experience.

Background and aims: The Liver Reporting and Data System (LI-RADS) is the standard classification of imaging findings of hepatic abnormalities for hepatocellular carcinoma (HCC) surveillance. We aimed to study the course of LI-RADS 3 and 4 (LR-3 and LR-4) abnormalities through correlations with explant pathology. Methods: A single center retrospective study of liver transplant recipients between January 2016 and September 2019 with HCC on explant pathology was conducted. Eligible patients were divided into three subgroups based on their LI-RADS classification: LR-3/4, LR-5 only, and combination of LR-3/4/5. Results: There were 116 eligible patients with 99 LR-3/4 observations (60 LR-3 and 39 LR-4); the rest had LR-5 lesions. LR-4 more often than LR-3 observations progressed to LR-5 (36% vs 12%) and with shorter duration during follow-up (median 175 days and 196 days). Mean size growth of LR-3 and LR-4 abnormalities were 2.6 and 3.8 mm; median growth rates were 0.2 and 0.4 mm/month, respectively. Numbers of HCC lesions per explant, largest HCC lesion size, and cumulative size were higher in LR-3/4/5 subgroup than LR-5 subgroup (P = 0.007, 0.007 and 0.006, respectively); 68% of LR-3 and 82% of LR-4 abnormalities were confirmed HCC on explant (P = 0.09). Conclusion: Compared to LR-3, more LR-4 abnormalities progressed to LR-5 (12% and 36%, respectively) in a shorter time and with faster growth rate. A high proportion of LR-3 and LR-4 lesions (68% and 82%, respectively) were confirmed HCC on explant, raising the question of whether excluding HCC based on radiologic criteria alone is adequate in those with LR-3/4 abnormalities.

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.

Germinal center responses to SARS-CoV-2 mRNA vaccines in healthy and immunocompromised individuals.

Vaccine-mediated immunity often relies on the generation of protective antibodies and memory B cells, which commonly stem from germinal center (GC) reactions. An in-depth comparison of the GC responses elicited by SARS-CoV-2 mRNA vaccines in healthy and immunocompromised individuals has not yet been performed due to the challenge of directly probing human lymph nodes. Herein, through a fine-needle aspiration-based approach, we profiled the immune responses to SARS-CoV-2 mRNA vaccines in lymph nodes of healthy individuals and kidney transplant recipients (KTXs). We found that, unlike healthy subjects, KTXs presented deeply blunted SARS-CoV-2-specific GC B cell responses coupled with severely hindered T follicular helper cell, SARS-CoV-2 receptor binding domain-specific memory B cell, and neutralizing antibody responses. KTXs also displayed reduced SARS-CoV-2-specific CD4 and CD8 T cell frequencies. Broadly, these data indicate impaired GC-derived immunity in immunocompromised individuals and suggest a GC origin for certain humoral and memory B cell responses following mRNA vaccination.

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.

Germinal center responses to SARS-CoV-2 mRNA vaccines in healthy and immunocompromised individuals.

Vaccine-mediated immunity often relies on the generation of protective antibodies and memory B cells, which commonly stem from germinal center (GC) reactions. An in-depth comparison of the GC responses elicited by SARS-CoV-2 mRNA vaccines in healthy and immunocompromised individuals has not yet been performed due to the challenge of directly probing human lymph nodes. In this study, through a fine-needle-aspiration-based approach, we profiled the immune responses to SARS-CoV-2 mRNA vaccines in lymph nodes of healthy individuals and kidney transplant (KTX) recipients. We found that, unlike healthy subjects, KTX recipients presented deeply blunted SARS-CoV-2-specific GC B cell responses coupled with severely hindered T follicular helper cells, SARS-CoV-2 receptor-binding-domain-specific memory B cells and neutralizing antibodies. KTX recipients also displayed reduced SARS-CoV-2-specific CD4 and CD8 T cell frequencies. Broadly, these data indicate impaired GC-derived immunity in immunocompromised individuals, and suggest a GC-origin for certain humoral and memory B cell responses following mRNA vaccination.

Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response.

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.

Adaptive convolutional neural networks for accelerating magnetic resonance imaging via k-space data interpolation.

Deep learning in k-space has demonstrated great potential for image reconstruction from undersampled k-space data in fast magnetic resonance imaging (MRI). However, existing deep learning-based image reconstruction methods typically apply weight-sharing convolutional neural networks (CNNs) to k-space data without taking into consideration the k-space data's spatial frequency properties, leading to ineffective learning of the image reconstruction models. Moreover, complementary information of spatially adjacent slices is often ignored in existing deep learning methods. To overcome such limitations, we have developed a deep learning algorithm, referred to as adaptive convolutional neural networks for k-space data interpolation (ACNN-k-Space), which adopts a residual Encoder-Decoder network architecture to interpolate the undersampled k-space data by integrating spatially contiguous slices as multi-channel input, along with k-space data from multiple coils if available. The network is enhanced by self-attention layers to adaptively focus on k-space data at different spatial frequencies and channels. We have evaluated our method on two public datasets and compared it with state-of-the-art existing methods. Ablation studies and experimental results demonstrate that our method effectively reconstructs images from undersampled k-space data and achieves significantly better image reconstruction performance than current state-of-the-art techniques. Source code of the method is available at https://gitlab.com/qgpmztmf/acnn-k-space.

Occult Hepatocellular Carcinoma Associated With Transjugular Intrahepatic Portosystemic Shunts in Liver Transplant Recipients.

Transplant eligibility for hepatocellular carcinoma (HCC) is determined by the imaging identification of tumor burden within the Milan criteria. Transjugular intrahepatic portosystemic shunt(s) (TIPS) reduce portal hypertension but may impact HCC visualization. It was hypothesized that the presence of pretransplant TIPS would correlate with occult HCC and reduced survival. A single-center, retrospective, case control study was performed among liver transplant recipients with HCC (2000-2017). The primary endpoint was occult disease on explant pathology. Backward stepwise logistic regression was performed. The secondary endpoints disease-free survival (DFS) and overall survival (OS) were evaluated with Kaplan-Meier curves and Cox regression analysis. Of 640 patients, 40 had TIPS and more frequently exhibited occult disease (80.0% versus 43.1%; P < 0.001; odds ratio [OR], 4.16; P < 0.001). Portal vein thrombosis (PVT) similarly correlated with occult disease (OR, 1.97; P = 0.02). Explant tumor burden was equivalent between TIPS subgroups; accordingly, TIPS status was not independently associated with reduced DFS or OS. However, exceeding the Milan criteria was associated with reduced DFS (hazard ratio, 3.21; P = 0.001), and TIPS status in patients with a single suspected lesion (n = 316) independently correlated with explant tumor burdens beyond these criteria (OR, 13.47; P = 0.001). TIPS on pretransplant imaging are associated with occult HCC on explant pathology. Comparable occult disease findings in patients with PVT suggest that the mechanism may involve altered hepatic perfusion, obscuring imaging diagnosis. TIPS are not independently associated with reduced DFS or OS but are associated with exceeding the Milan criteria for patients with a single suspected lesion. The presence of TIPS may necessitate a higher index of suspicion for occult HCC.