Imaging Features of Arrhythmogenic Cardiomyopathies

Arrhythmogenic cardiomyopathy (ACM) is a genetic disease characterized by replacement of ventricular myocardium with fibrofatty tissue, predisposing the patient to ventricular arrhythmias and/or sudden cardiac death. Most cases of ACM are associated with pathogenic variants in genes that encode desmosomal proteins, an important cell-to-cell adhesion complex present in both the heart and skin tissue. Although ACM was first described as a disease predominantly of the right ventricle, it is now acknowledged that it can also primarily involve the left ventricle or both ventricles. The original right-dominant phenotype is traditionally diagnosed using the 2010 task force criteria, a multifactorial algorithm divided into major and minor criteria consisting of structural criteria based on two-dimensional echocardiographic, cardiac MRI, or right ventricular angiographic findings; tissue characterization based on endomyocardial biopsy results; repolarization and depolarization abnormalities based on electrocardiographic findings; arrhythmic features; and family history. Shortfalls in the task force criteria due to the modern understanding of the disease have led to development of the Padua criteria, which include updated criteria for diagnosis of the right-dominant phenotype and new criteria for diagnosis of the left-predominant and biventricular phenotypes. In addition to incorporating cardiac MRI findings of ventricular dilatation, systolic dysfunction, and regional wall motion abnormalities, the new Padua criteria emphasize late gadolinium enhancement at cardiac MRI as a key feature in diagnosis and imaging-based tissue characterization. Conditions to consider in the differential diagnosis of the right-dominant phenotype include various other causes of right ventricular dilatation such as left-to-right shunts and variants of normal right ventricular anatomy that can be misinterpreted as abnormalities. The left-dominant phenotype can mimic myocarditis at imaging and clinical examination. Additional considerations for the differential diagnosis of ACM, particularly for the left-dominant phenotype, include sarcoidosis and dilated cardiomyopathy. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Multimodality Imaging for 3D Printing and Surgical Rehearsal in Complex Spine Surgery

Surgery is the mainstay treatment of symptomatic spinal tumors. It aids in restoring functionality, managing pain and tumor growth, and improving overall quality of life. Over the past decade, advancements in medical imaging techniques combined with the use of three-dimensional (3D) printing technology have enabled improvements in the surgical management of spine tumors by significantly increasing the precision, accuracy, and safety of the surgical procedures. For complex spine surgical cases, the use of multimodality imaging is necessary to fully visualize the extent of disease, including both soft-tissue and bone involvement. Integrating the information provided by these examinations in a cohesive manner to facilitate surgical planning can be challenging, particularly when multiple surgical specialties work in concert. The digital 3-dimensional (3D) model or 3D rendering and the 3D printed model created from imaging examinations such as CT and MRI not only facilitate surgical planning but also allow the placement of virtual and physical surgical or osteotomy planes, further enhancing surgical planning and rehearsal. The authors provide practical information about the 3D printing workflow, from image acquisition to postprocessing of a 3D printed model, as well as optimal material selection and incorporation of quality management systems, to help surgeons utilize 3D printing for surgical planning. The authors also highlight the process of surgical rehearsal, how to prescribe digital osteotomy planes, and integration with intraoperative surgical navigation systems through a case-based discussion. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Incidental Ring-hyperenhancing Liver Micronodules at CT Hepatic Arteriography-guided Percutaneous Thermal Ablation of Colorectal Liver Metastases

CT during hepatic arteriography (CTHA) is a highly sensitive imaging method for detecting colorectal liver metastases (CLMs), which supports its use during percutaneous thermal liver ablation. In contrast to its high sensitivity, its specificity for incidental small CLMs not detected at preablation cross-sectional imaging is believed to be low given the absence of specific imaging signatures and the common presence of pseudolesions. In this retrospective study of 22 patients (mean age, 55 years ± 10.6 [SD]; 63.6% male, 36.4% female) with CLMs undergoing CTHA-guided microwave percutaneous thermal ablation between November 2017 and October 2022, the authors provided a definition of incidental ring-hyperenhancing liver micronodules (RHLMs) and investigated whether there is a correlation of RHLMs with histologic analysis or intrahepatic tumor progression at imaging follow-up after applying a biomechanical deformable image registration method. The analysis revealed 25 incidental RHLMs in 41.7% (10 of 24) of the CTHA images from the respective guided ablation sessions. Of those, four RHLMs were ablated. Among the remaining 21 RHLMs, 71.4% (15 of 21) were confirmed to be CLM with either histology (n = 3) or imaging follow-up (n = 12). The remaining 28.6% (six of 21) of RHLMs were not observed at follow-up imaging. This suggests that RHLMs at CTHA may be an early indicator of incidental small CLMs. Keywords: Colorectal Neoplasms, Liver, Angiography, CT, Incidental Findings, Ablation Supplemental material is available for this article. © RSNA, 2024.

Safety and Feasibility of Photodynamic Therapy for Percutaneous Image-guided Abdominopelvic Abscess Drainage: Phase 1 Trial

Background Standard-of-care abscess management includes image-guided percutaneous drainage and antibiotics; however, cure rates vary, and concern for antibiotic-resistant bacteria is growing. Photodynamic therapy (PDT), which uses light-activated dyes to generate cytotoxic reactive oxygen species, could complement the standard of care by sterilizing the abscess at the time of drainage. Purpose To evaluate safety and feasibility of PDT with methylene blue (hereafter, MB-PDT) at the time of percutaneous abscess drainage. Materials and Methods This prospective, open-label, dose-escalation, first-in-humans, registered phase 1 clinical study of MB-PDT included participants who underwent percutaneous abdominal or pelvic abscess drainage with CT or US guidance from January 2015 to March 2020 and September 2022 to September 2023. Following drainage, MB-PDT was performed with laser illumination at a fluence rate of 20 mW/cm2, with fluence groups of 6, 12, 18, 24, 30, and 36 J/cm2 (n = 3 each). The primary outcome was safety, indicated by absence of fat embolism, MB escape, abscess wall damage, and need for surgery to remove optical fibers. Preliminary efficacy end points included the time to drainage catheter removal, drainage catheter output volume, and clinical symptom and fever duration. Relationships between fluence and outcomes were analyzed with Spearman correlation and linear regression analyses, and ordinary one-way analysis of variance was used for group comparisons. Results MB-PDT was safe and feasible in all 18 participants (mean age, 60.1 years ± 18.3 [SD]; 10 female), with no negative safety outcomes observed for any participant. No study-related adverse events were encountered, and the procedure did not increase reported pain (P = .1). Clinical symptom and fever duration was shorter in participants receiving higher fluences (30 and 36 J/cm2 vs 6 J/cm2) (P = .03). The presence of antibiotic-resistant bacteria was not predictive of clinical symptom and fever duration (β = 0.13, P = .37). Conclusion MB-PDT was a safe and feasible adjunct to image-guided percutaneous abscess drainage. Clinical measures indicated a dose-dependent response to PDT. ClinicalTrials.gov registration no.: NCT02240498 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Johnston and Goldberg in this issue.

18F-FDG Dedicated Breast PET Complementary to Breast MRI for Evaluating Early Response to Neoadjuvant Chemotherapy

Purpose To compare quantitative measures of tumor metabolism and perfusion using fluorine 18 (18F) fluorodeoxyglucose (FDG) dedicated breast PET (dbPET) and breast dynamic contrast-enhanced (DCE) MRI during early treatment with neoadjuvant chemotherapy (NAC). Materials and Methods Prospectively collected DCE MRI and 18F-FDG dbPET examinations were analyzed at baseline (T0) and after 3 weeks (T1) of NAC in 20 participants with 22 invasive breast cancers. FDG dbPET-derived standardized uptake value (SUV), metabolic tumor volume, and total lesion glycolysis (TLG) and MRI-derived percent enhancement (PE), signal enhancement ratio (SER), and functional tumor volume (FTV) were calculated at both time points. Differences between FDG dbPET and MRI parameters were evaluated after stratifying by receptor status, Ki-67 index, and residual cancer burden. Parameters were compared using Wilcoxon signed rank and Mann-Whitney U tests. Results High Ki-67 tumors had higher baseline SUVmean (difference, 5.1; P = .01) and SUVpeak (difference, 5.5; P = .04). At T1, decreases were observed in FDG dbPET measures (pseudo-median difference T0 minus T1 value [95% CI]) of SUVmax (-6.2 [-10.2, -2.6]; P < .001), SUVmean (-2.6 [-4.9, -1.3]; P < .001), SUVpeak (-4.2 [-6.9, -2.3]; P < .001), and TLG (-29.1 mL3 [-71.4, -6.8]; P = .005) and MRI measures of SERpeak (-1.0 [-1.3, -0.2]; P = .02) and FTV (-11.6 mL3 [-22.2, -1.7]; P = .009). Relative to nonresponsive tumors, responsive tumors showed a difference (95% CI) in percent change in SUVmax of -34.3% (-55.9%, 1.5%; P = .06) and in PEpeak of -42.4% (95% CI: -110.5%, 8.5%; P = .08). Conclusion 18F-FDG dbPET was sensitive to early changes during NAC and provided complementary information to DCE MRI that may be useful for treatment response evaluation. Keywords: Breast, PET, Dynamic Contrast-enhanced MRI Clinical trial registration no. NCT01042379 Supplemental material is available for this article. © RSNA, 2024.

Interpretation, Reporting, and Clinical Applications of Liver MR Elastography

Chronic liver disease is highly prevalent and often leads to fibrosis or cirrhosis and complications such as liver failure and hepatocellular carcinoma. The diagnosis and staging of liver fibrosis is crucial to determine management and mitigate complications. Liver biopsy for histologic assessment has limitations such as sampling bias and high interreader variability that reduce precision, which is particularly challenging in longitudinal monitoring. MR elastography (MRE) is considered the most accurate noninvasive technique for diagnosing and staging liver fibrosis. In MRE, low-frequency vibrations are applied to the abdomen, and the propagation of shear waves through the liver is analyzed to measure liver stiffness, a biomarker for the detection and staging of liver fibrosis. As MRE has become more widely used in clinical care and research, different contexts of use have emerged. This review focuses on the latest developments in the use of MRE for the assessment of liver fibrosis; provides guidance for image acquisition and interpretation; summarizes diagnostic performance, along with thresholds for diagnosis and staging of liver fibrosis; discusses current and emerging clinical applications; and describes the latest technical developments.

Characterizing Metabolic Heterogeneity of Hepatocellular Carcinoma with Hyperpolarized 13C Pyruvate MRI and Mass Spectrometry

Purpose To characterize the metabolomic profiles of two hepatocellular carcinoma (HCC) rat models, track evolution of these profiles to a stimulated tumor state, and assess their effect on lactate flux with hyperpolarized (HP) carbon 13 (13C) MRI. Materials and Methods Forty-three female adult Fischer rats were implanted with N1S1 or McA-RH7777 HCC tumors. In vivo lactate-to-pyruvate ratio (LPR) was measured with HP 13C MRI at 9.4 T. Ex vivo mass spectrometry was used to measure intratumoral metabolites, and Ki67 labeling was used to quantify proliferation. Tumors were first compared with three normal liver controls. The tumors were then compared with stimulated variants via off-target hepatic thermal ablation treatment. All comparisons were made using the Mann-Whitney test. Results HP 13C pyruvate MRI showed greater LPR in N1S1 tumors compared with normal liver (mean [SD], 0.564 ± 0.194 vs 0.311 ± 0.057; P < .001 [n = 9]), but not for McA-RH7777 (P = .44 [n = 8]). Mass spectrometry confirmed that the glycolysis pathway was increased in N1S1 tumors and decreased in McA-RH7777 tumors. The pentose phosphate pathway was also decreased only in McA-RH7777 tumors. Increased proliferation in stimulated N1S1 tumors corresponded to a net increase in LPR (six stimulated vs six nonstimulated, 0.269 ± 0.148 vs 0.027 ± 0.08; P = .009), but not in McA-RH7777 (eight stimulated vs six nonstimulated, P = .13), despite increased proliferation and metastases. Mass spectrometry demonstrated relatively increased lactate production with stimulation in N1S1 tumors only. Conclusion Two HCC subtypes showed divergent glycolytic dependency at baseline and during transformation to a high proliferation state. This metabolic heterogeneity in HCC should be considered with use of HP 13C MRI for diagnosis and tracking. Keywords: Molecular Imaging-Probe Development, Liver, Abdomen/GI, Oncology, Hepatocellular Carcinoma © RSNA, 2024 See also commentary by Ohliger in this issue.

Curated and Annotated Dataset of Lung US Images in Zambian Children with Clinical Pneumonia

See also the commentary by Sitek in this issue. Supplemental material is available for this article.

Diagnostic Performance of Point-of-Care Apparent Diffusion Coefficient Measures to Reduce Biopsy in Breast Lesions at MRI: Clinical Validation

Background The Eastern Cooperative Oncology Group-American College of Radiology Imaging Network Cancer Research Group multicenter A6702 trial identified an optimal apparent diffusion coefficient (ADC) cutoff to potentially reduce biopsies by 21% without affecting sensitivity. Whether this performance can be achieved in clinical settings has not yet been established. Purpose To validate the performance of point-of-care ADC measurements with the A6702 trial ADC cutoff for reducing unnecessary biopsies in lesions detected at breast MRI. Materials and Methods Consecutive breast MRI examinations performed from May 2015 to January 2019 at a single medical center and showing biopsy-confirmed Breast Imaging Reporting and Data System category 4 or 5 lesions, without ipsilateral cancer, were identified. Point-of-care lesion ADC measurements collected at clinical interpretation were retrospectively evaluated. MRI examinations included axial T2-weighted, diffusion-weighted, and dynamic contrast-enhanced sequences. Sensitivity and biopsy reduction rates were calculated by applying the A6702 optimal (ADC, 1.53 × 10-3 mm2/sec) and alternate conservative (1.68 × 10-3 mm2/sec) cutoffs. Lesion pathologic outcomes were the reference standard. To assess reproducibility, one radiologist repeated ADC measurements, and agreement was summarized using the intraclass correlation coefficient. Results A total of 240 lesions in 201 women (mean age, 49 years ± 13 [SD]) with pathologic outcomes (63 malignant and 177 benign) were included. Applying the optimal ADC cutoff produced an overall biopsy reduction rate of 15.8% (38 of 240 lesions [95% CI: 11.2, 20.9]), with a sensitivity of 92.1% (58 of 63 lesions [95% CI: 82.4, 97.4]; sensitivity was 97.2% [35 of 36 lesions] [95% CI: 82.7, 99.6] for invasive cancers). Results were similar for screening versus diagnostic examinations (P = .92 and .40, respectively). Sensitivity was higher for masses than for nonmass enhancements (NMEs) (100% vs 85.3%; P = .009). Applying the conservative ADC cutoff achieved a sensitivity of 95.2% (60 of 63 lesions [95% CI: 86.7, 99.0]), with a biopsy reduction rate of 10.4% (25 of 240 lesions [95% CI: 6.7, 14.5]). Repeated single-reader measurements showed good agreement with clinical ADCs (intraclass correlation coefficient, 0.72 [95% CI: 0.58, 0.81]). Conclusion This study validated the clinical use of ADC cutoffs to reduce MRI-prompted biopsies by up to 16%, with a suggested tradeoff of lowered sensitivity for in situ and microinvasive disease manifesting as NME. Clinical trial registration no. NCT02022579 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Honda and Iima in this issue.

Effect of Incomplete Cryoablation and Matrix Metalloproteinase Inhibition on Intratumoral CD8+ T-Cell Infiltration in Murine Hepatocellular Carcinoma

Background Image-guided tumor ablation is the first-line therapy for early-stage hepatocellular carcinoma (HCC), with ongoing investigations into its combination with immunotherapies. Matrix metalloproteinase (MMP) inhibition demonstrates immunomodulatory potential and reduces HCC tumor growth when combined with ablative treatment. Purpose To evaluate the effect of incomplete cryoablation with or without MMP inhibition on the local immune response in residual tumors in a murine HCC model. Materials and Methods Sixty 8- to 10-week-old female BALB/c mice underwent HCC induction with use of orthotopic implantation of syngeneic Tib-75 cells. After 7 days, mice with a single lesion were randomized into treatment groups: (a) no treatment, (b) MMP inhibitor, (c) incomplete cryoablation, and (d) incomplete cryoablation and MMP inhibitor. Macrophage and T-cell subsets were assessed in tissue samples with use of immunohistochemistry and immunofluorescence (cell averages calculated using five 1-μm2 fields of view [FOVs]). C-X-C motif chemokine receptor type 3 (CXCR3)- and interferon γ (IFNγ)-positive T cells were assessed using flow cytometry. Groups were compared using unpaired Student t tests, one-way analysis of variance with Tukey correction, and the Kruskal-Wallis test with Dunn correction. Results Mice treated with incomplete cryoablation (n = 6) showed greater infiltration of CD206+ tumor-associated macrophages (mean, 1.52 cells per FOV vs 0.64 cells per FOV; P = .03) and MMP9-expressing cells (mean, 0.89 cells per FOV vs 0.11 cells per FOV; P = .03) compared with untreated controls (n = 6). Incomplete cryoablation with MMP inhibition (n = 6) versus without (n = 6) led to greater CD8+ T-cell (mean, 15.8% vs 8.29%; P = .04), CXCR3+CD8+ T-cell (mean, 11.64% vs 8.47%; P = .004), and IFNγ+CD8+ T-cell infiltration (mean, 11.58% vs 5.18%; P = .02). Conclusion In a mouse model of HCC, incomplete cryoablation and systemic MMP inhibition showed increased cytotoxic CD8+ T-cell infiltration into the residual tumor compared with either treatment alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Gemmete in this issue.

Comparison of Lung-RADS Version 1.1 and Lung-RADS Version 2022 in Classifying Airway Nodules Detected at Lung Cancer Screening CT

Purpose To compare the Lung Imaging Reporting and Data System (Lung-RADS) version 1.1 with version 2022 classification of airway nodules detected at lung cancer screening CT examinations. Materials and Methods This retrospective study included all patients who underwent a lung cancer screening CT examination in the authors' health care network between 2015 and 2021 with a reported airway or endobronchial nodule. A fellowship-trained cardiothoracic radiologist reviewed these CT images and characterized the airway nodules by size, location, multiplicity, morphology, dependent portions of airway, internal air, fluid attenuation, distal changes, outcome at follow-up, and final pathologic diagnosis, if malignant. Sensitivity and specificity of Lung-RADS version 1.1 in detecting malignant nodules were compared with those of Lung-RADS version 2022 using the McNemar test. Results A total of 174 patients were included. Of these, 163 (94%) had airway nodules that were deemed benign, while 11 (6%) had malignant nodules. Airway nodules in the trachea and mainstem bronchi were all benign, while lobar and segmental airway nodules had the highest risk for lung cancer (17.2% and 11.1%, respectively). Of the 12 subsegmental airway nodules that were obstructive, three (25%) were malignant and nine (75%) were benign. Nodules with nonobstructive morphologies, dependent portions of airway, internal air, or fluid attenuation were all benign. Only 10 of the 92 (10.9%) patients with positive Lung-RADS by clinical report had cancer. Lung-RADS version 2022 resulted in higher specificity than version 1.1 (82% vs 50%, P < .001), without sacrificing sensitivity (91% for both). Conclusion Compared with the previous version, Lung-RADS version 2022 reduced the number of false-positive screening CT examinations while still identifying malignant airway nodules. Keywords: CT, Lung, Primary Neoplasms, Pulmonary, Lung Cancer Screening, Lung-RADS, Nodule Risk, Airway Nodule, Endobronchial Nodule © RSNA, 2024.

Ultra-rapid, Free-breathing, Real-time Cardiac Cine MRI Using GRASP Amplified with View Sharing and KWIC Filtering

Purpose To achieve ultra-high temporal resolution (approximately 20 msec) in free-breathing, real-time cardiac cine MRI using golden-angle radial sparse parallel (GRASP) reconstruction amplified with view sharing (VS) and k-space-weighted image contrast (KWIC) filtering. Materials and Methods Fourteen pediatric patients with congenital heart disease (mean age [SD], 9 years ± 2; 13 male) and 10 adult patients with arrhythmia (mean age, 62 years ± 8; nine male) who underwent both standard breath-hold cine and free-breathing real-time cine using GRASP were retrospectively identified. To achieve high temporal resolution, each time frame was reconstructed using six radial spokes, corresponding to acceleration factors ranging from 24 to 32. To compensate for loss in spatial resolution resulting from over-regularization in GRASP, VS and KWIC filtering were incorporated. The blur metric, visual image quality scores, and biventricular parameters were compared between clinical and real-time cine images. Results In pediatric patients, the incorporation of VS and KWIC into GRASP (ie, GRASP + VS + KWIC) produced significantly (P < .05) sharper x-y-t (blur metric: 0.36 ± 0.03, 0.41 ± 0.03, 0.48 ± 0.03, respectively) and x-y-f (blur metric: 0.28 ± 0.02, 0.31 ± 0.03, 0.37 ± 0.03, respectively) component images compared with GRASP + VS and conventional GRASP. Only the noise score differed significantly between GRASP + VS + KWIC and clinical cine; all visual scores were above the clinically acceptable (3.0) cutoff point. Biventricular volumetric parameters strongly correlated (R2 > 0.85) between clinical and real-time cine images reconstructed with GRASP + VS + KWIC and were in good agreement (relative error < 6% for all parameters). In adult patients, the visual scores of all categories were significantly lower (P < .05) for clinical cine compared with real-time cine with GRASP + VS + KWIC, except for noise (P = .08). Conclusion Incorporating VS and KWIC filtering into GRASP reconstruction enables ultra-high temporal resolution (approximately 20 msec) without significant loss in spatial resolution. Keywords: Cine, View Sharing, k-Space-weighted Image Contrast Filtering, Radial k-Space, Pediatrics, Arrhythmia, GRASP, Compressed Sensing, Real-Time, Free-Breathing Supplemental material is available for this article. © RSNA, 2024.

Evaluation of Intracardiac Pressures Using Subharmonic-aided Pressure Estimation with Sonazoid Microbubbles

Purpose To investigate if the right ventricular (RV) systolic and left ventricular (LV) diastolic pressures can be obtained noninvasively using the subharmonic-aided pressure estimation (SHAPE) technique with Sonazoid microbubbles. Materials and Methods Individuals scheduled for a left and/or right heart catheterization were prospectively enrolled in this institutional review board-approved clinical trial from 2017 to 2020. A standard-of-care catheterization procedure was performed by advancing fluid-filled pressure catheters into the LV and aorta (n = 25) or RV (n = 22), and solid-state high-fidelity pressure catheters into the LV and aorta in a subset of participants (n = 18). Study participants received an infusion of Sonazoid microbubbles (GE HealthCare), and SHAPE data were acquired using a validated interface developed on a SonixTablet (BK Medical) US scanner, synchronously with the pressure catheter data. A conversion factor, derived using cuff-based pressure measurements with a SphygmoCor XCEL PWA (ATCOR) and subharmonic signal from the aorta, was used to convert the subharmonic signal into pressure values. Errors between the pressure measurements obtained using the SHAPE technique and pressure catheter were compared. Results The mean errors in pressure measurements obtained with the SHAPE technique relative to those of the fluid-filled pressure catheter were 1.6 mm Hg ± 1.5 [SD] (P = .85), 8.4 mm Hg ± 6.2 (P = .04), and 7.4 mm Hg ± 5.7 (P = .09) for RV systolic, LV minimum diastolic, and LV end-diastolic pressures, respectively. Relative to the measurements with the solid-state high-fidelity pressure catheter, the mean errors in LV minimum diastolic and LV end-diastolic pressures were 7.2 mm Hg ± 4.5 and 6.8 mm Hg ± 3.3 (P ≥ .44), respectively. Conclusion These results indicate that SHAPE with Sonazoid may have the potential to provide clinically relevant RV systolic and LV diastolic pressures. Keywords: Ultrasound-Contrast, Cardiac, Aorta, Left Ventricle, Right Ventricle ClinicalTrials.gov registration no.: NCT03245255 © RSNA, 2024.

Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge

Purpose To describe the design, conduct, and results of the Breast Multiparametric MRI for prediction of neoadjuvant chemotherapy Response (BMMR2) challenge. Materials and Methods The BMMR2 computational challenge opened on May 28, 2021, and closed on December 21, 2021. The goal of the challenge was to identify image-based markers derived from multiparametric breast MRI, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI, along with clinical data for predicting pathologic complete response (pCR) following neoadjuvant treatment. Data included 573 breast MRI studies from 191 women (mean age [±SD], 48.9 years ± 10.56) in the I-SPY 2/American College of Radiology Imaging Network (ACRIN) 6698 trial (ClinicalTrials.gov: NCT01042379). The challenge cohort was split into training (60%) and test (40%) sets, with teams blinded to test set pCR outcomes. Prediction performance was evaluated by area under the receiver operating characteristic curve (AUC) and compared with the benchmark established from the ACRIN 6698 primary analysis. Results Eight teams submitted final predictions. Entries from three teams had point estimators of AUC that were higher than the benchmark performance (AUC, 0.782 [95% CI: 0.670, 0.893], with AUCs of 0.803 [95% CI: 0.702, 0.904], 0.838 [95% CI: 0.748, 0.928], and 0.840 [95% CI: 0.748, 0.932]). A variety of approaches were used, ranging from extraction of individual features to deep learning and artificial intelligence methods, incorporating DCE and DWI alone or in combination. Conclusion The BMMR2 challenge identified several models with high predictive performance, which may further expand the value of multiparametric breast MRI as an early marker of treatment response. Clinical trial registration no. NCT01042379 Keywords: MRI, Breast, Tumor Response Supplemental material is available for this article. © RSNA, 2024.

Strategies for Implementing Machine Learning Algorithms in the Clinical Practice of Radiology

Despite recent advancements in machine learning (ML) applications in health care, there have been few benefits and improvements to clinical medicine in the hospital setting. To facilitate clinical adaptation of methods in ML, this review proposes a standardized framework for the step-by-step implementation of artificial intelligence into the clinical practice of radiology that focuses on three key components: problem identification, stakeholder alignment, and pipeline integration. A review of the recent literature and empirical evidence in radiologic imaging applications justifies this approach and offers a discussion on structuring implementation efforts to help other hospital practices leverage ML to improve patient care. Clinical trial registration no. 04242667 © RSNA, 2024 Supplemental material is available for this article.

Assessing Adherence to US LI-RADS Follow-up Recommendations in Vulnerable Patients Undergoing Hepatocellular Carcinoma Surveillance

Purpose To assess adherence to the US Liver Imaging Reporting and Data System (LI-RADS) recommendations for hepatocellular carcinoma (HCC) surveillance and associated patient-level factors in a vulnerable, diverse patient sample. Materials and Methods The radiology report database was queried retrospectively for patients who underwent US LI-RADS-based surveillance examinations at a single institution between June 1, 2020, and February 28, 2021. Initial US and follow-up liver imaging were included. Sociodemographic and clinical data were captured from electronic medical records. Adherence to radiologist recommendation was defined as imaging (US, CT, or MRI) follow-up in 5-7 months for US-1, imaging follow-up in 3-6 months for US-2, and CT or MRI follow-up in 2 months for US-3. Descriptive analysis and multivariable modeling that adjusted for age, sex, race, and time since COVID-19 pandemic onset were performed. Results Among 936 patients, the mean age was 59.1 years; 531 patients (56.7%) were male and 544 (58.1%) were Asian or Pacific Islander, 91 (9.7%) were Black, 129 (13.8%) were Hispanic, 147 (15.7%) were White, and 25 (2.7%) self-reported as other race. The overall adherence rate was 38.8% (95% CI: 35.7, 41.9). The most common liver disease etiology was hepatitis B (60.6% [657 of 936 patients]); 19.7% of patients (183 of 936) had current or past substance use disorder, and 44.8% (416 of 936) smoked. At adjusted multivariable analysis, older age (odds ratio [OR], 1.20; P = .02), male sex (OR, 1.62; P = .003), hepatology clinic attendance (OR, 3.81; P < .001), and recent prior US examination (OR, 2.44; P < .001) were associated with full adherence, while current smoking (OR, 0.39; P < .001) was negatively associated. Conclusion Adherence to HCC imaging surveillance was suboptimal, despite US LI-RADS implementation. Keywords: Liver, Ultrasound, Screening, Abdomen/GI, Cirrhosis, Metabolic Disorders, Socioeconomic Issues Supplemental material is available for this article. © RSNA, 2024.

Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk

Background Background parenchymal enhancement (BPE) at dynamic contrast-enhanced (DCE) MRI of cancer-free breasts increases the risk of developing breast cancer; implications of quantitative BPE in ipsilateral breasts with breast cancer are largely unexplored. Purpose To determine whether quantitative BPE measurements in one or both breasts could be used to predict recurrence risk in women with breast cancer, using the Oncotype DX recurrence score as the reference standard. Materials and Methods This HIPAA-compliant retrospective single-institution study included women diagnosed with breast cancer between January 2007 and January 2012 (development set) and between January 2012 and January 2017 (internal test set). Quantitative BPE was automatically computed using an in-house-developed computer algorithm in both breasts. Univariable logistic regression was used to examine the association of BPE with Oncotype DX recurrence score binarized into high-risk (recurrence score >25) and low- or intermediate-risk (recurrence score ≤25) categories. Models including BPE measures were assessed for their ability to distinguish patients with high risk versus those with low or intermediate risk and the actual recurrence outcome. Results The development set included 127 women (mean age, 58 years ± 10.2 [SD]; 33 with high risk and 94 with low or intermediate risk) with an actual local or distant recurrence rate of 15.7% (20 of 127) at a minimum 10 years of follow-up. The test set included 60 women (mean age, 57.8 years ± 11.6; 16 with high risk and 44 with low or intermediate risk). BPE measurements quantified in both breasts were associated with increased odds of a high-risk Oncotype DX recurrence score (odds ratio range, 1.27-1.66 [95% CI: 1.02, 2.56]; P < .001 to P = .04). Measures of BPE combined with tumor radiomics helped distinguish patients with a high-risk Oncotype DX recurrence score from those with a low- or intermediate-risk score, with an area under the receiver operating characteristic curve of 0.94 in the development set and 0.79 in the test set. For the combined models, the negative predictive values were 0.97 and 0.93 in predicting actual distant recurrence and local recurrence, respectively. Conclusion Ipsilateral and contralateral DCE MRI measures of BPE quantified in patients with breast cancer can help distinguish patients with high recurrence risk from those with low or intermediate recurrence risk, similar to Oncotype DX recurrence score. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Zhou and Rahbar in this issue.

Radiologic Features of Nodules Attached to the Mediastinal or Diaphragmatic Pleura at Low-Dose CT for Lung Cancer Screening

Background Pulmonary noncalcified nodules (NCNs) attached to the fissural or costal pleura with smooth margins and triangular or lentiform, oval, or semicircular (LOS) shapes at low-dose CT are recommended for annual follow-up instead of immediate workup. Purpose To determine whether management of mediastinal or diaphragmatic pleura-attached NCNs (M/DP-NCNs) with the same features as fissural or costal pleura-attached NCNs at low-dose CT can follow the same recommendations. Materials and Methods This retrospective study reviewed chest CT examinations in participants from two databases. Group A included 1451 participants who had lung cancer that was first present as a solid nodule with an average diameter of 3.0-30.0 mm. Group B included 345 consecutive participants from a lung cancer screening program who had at least one solid nodule with a diameter of 3.0-30.0 mm at baseline CT and underwent at least three follow-up CT examinations. Radiologists reviewed CT images to identify solid M/DP-NCNs, defined as nodules 0 mm in distance from the mediastinal or diaphragmatic pleura, and recorded average diameter, margin, and shape. General descriptive statistics were used. Results Among the 1451 participants with lung cancer in group A, 163 participants (median age, 68 years [IQR, 61.5-75.0 years]; 92 male participants) had 164 malignant M/DP-NCNs 3.0-30.0 mm in average diameter. None of the 164 malignant M/DP-NCNs had smooth margins and triangular or LOS shapes (upper limit of 95% CI of proportion, 0.02). Among the 345 consecutive screening participants in group B, 146 participants (median age, 65 years [IQR, 59-71 years]; 81 female participants) had 240 M/DP-NCNs with average diameter 3.0-30.0 mm. None of the M/DP-NCNs with smooth margins and triangular or LOS shapes were malignant after a median follow-up of 57.8 months (IQR, 46.3-68.1 months). Conclusion For solid M/DP-NCNs with smooth margins and triangular or LOS shapes at low-dose CT, the risk of lung cancer is extremely low, which supports the recommendation of Lung Imaging Reporting and Data System version 2022 for annual follow-up instead of immediate workup. © RSNA, 2024 See also the editorial by Goodman and Baruah in this issue.

Quantification of Emphysema Progression at CT Using Simultaneous Volume, Noise, and Bias Lung Density Correction

Background CT attenuation is affected by lung volume, dosage, and scanner bias, leading to inaccurate emphysema progression measurements in multicenter studies. Purpose To develop and validate a method that simultaneously corrects volume, noise, and interscanner bias for lung density change estimation in emphysema progression at CT in a longitudinal multicenter study. Materials and Methods In this secondary analysis of the prospective Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, lung function data were obtained from participants who completed baseline and 5-year follow-up visits from January 2008 to August 2017. CT emphysema progression was measured with volume-adjusted lung density (VALD) and compared with the joint volume-noise-bias-adjusted lung density (VNB-ALD). Reproducibility was studied under change of dosage protocol and scanner model with repeated acquisitions. Emphysema progression was visually scored in 102 randomly selected participants. A stratified analysis of clinical characteristics was performed that considered groups based on their combined lung density change measured by VALD and VNB-ALD. Results A total of 4954 COPDGene participants (mean age, 60 years ± 9 [SD]; 2511 male, 2443 female) were analyzed (1329 with repeated reduced-dose acquisition in the follow-up visit). Mean repeatability coefficients were 30 g/L ± 0.46 for VALD and 14 g/L ± 0.34 for VNB-ALD. VALD measurements showed no evidence of differences between nonprogressors and progressors (mean, -5.5 g/L ± 9.5 vs -8.6 g/L ± 9.6; P = .11), while VNB-ALD agreed with visual readings and showed a difference (mean, -0.67 g/L ± 4.8 vs -4.2 g/L ± 5.5; P < .001). Analysis of progression showed that VNB-ALD progressors had a greater decline in forced expiratory volume in 1 second (-42 mL per year vs -32 mL per year; Tukey-adjusted P = .002). Conclusion Simultaneously correcting volume, noise, and interscanner bias for lung density change estimation in emphysema progression at CT improved repeatability analyses and agreed with visual readings. It distinguished between progressors and nonprogressors and was associated with a greater decline in lung function metrics. Clinical trial registration no. NCT00608764 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Goo in this issue.

Style Transfer-assisted Deep Learning Method for Kidney Segmentation at Multiphase MRI

Purpose

To develop and validate a semisupervised style transfer-assisted deep learning method for automated segmentation of the kidneys using multiphase contrast-enhanced (MCE) MRI acquisitions.

Materials and Methods

This retrospective, Health Insurance Portability and Accountability Act-compliant, institutional review board-approved study included 125 patients (mean age, 57.3 years; 67 male, 58 female) with renal masses. Cohort 1 consisted of 102 coronal T2-weighted MRI acquisitions and 27 MCE MRI acquisitions during the corticomedullary phase. Cohort 2 comprised 92 MCE MRI acquisitions (23 acquisitions during four phases each, including precontrast, corticomedullary, early nephrographic, and nephrographic phases). The kidneys were manually segmented on T2-weighted images. A cycle-consistent generative adversarial network (CycleGAN) was trained to generate anatomically coregistered synthetic corticomedullary style images using T2-weighted images as input. Synthetic images for precontrast, early nephrographic, and nephrographic phases were then generated using the synthetic corticomedullary images as input. Mask region-based convolutional neural networks were trained on the four synthetic phase series for kidney segmentation using T2-weighted masks. Segmentation performance was evaluated in a different cohort of 20 originally acquired MCE MRI examinations by using Dice and Jaccard scores.

Results

The CycleGAN network successfully generated anatomically coregistered synthetic MCE MRI-like datasets from T2-weighted acquisitions. The proposed deep learning approach for kidney segmentation achieved high mean Dice scores in all four phases of the original MCE MRI acquisitions (0.91 for precontrast, 0.92 for corticomedullary, 0.91 for early nephrographic, and 0.93 for nephrographic).

Conclusion

The proposed deep learning approach achieved high performance in kidney segmentation on different MCE MRI acquisitions.Keywords: Kidney Segmentation, Generative Adversarial Network, CycleGAN, Convolutional Neural Network, Transfer Learning Supplemental material is available for this article. Published under a CC BY 4.0 license.

Social Determinants of Health in Imaging-based Cancer Screening: A Case-based Primer with Strategies for Care Improvement

Health disparities, preventable differences in the burden of disease and disease outcomes often experienced by socially disadvantaged populations, can be found in nearly all areas of radiology, including emergency radiology, neuroradiology, nuclear medicine, image-guided interventions, and imaging-based cancer screening. Disparities in imaging-based cancer screening are especially noteworthy given the far-reaching population health impact. The social determinants of health (SDoH) play an important role in disparities in cancer screening and outcomes. Through improved understanding of how SDoH can drive differences in health outcomes in radiology, radiologists can effectively provide patient-centered, high-quality, and equitable care. Radiologists and radiology practices can become active partners in efforts to assist patients along their imaging journey and overcome existing barriers to equitable cancer screening care for traditionally marginalized populations. As radiology exists at the intersection of diagnostic imaging, image-guided diagnostic intervention, and image-guided treatment, radiologists are uniquely positioned to design these strategies. Cost-effective and socially conscious strategies that address barriers to equitable care can improve both public health and equitable health outcomes. Potential strategies include championing supportive health policy, reducing out-of-pocket costs, increasing price transparency, improving education and outreach efforts, ensuring that appropriate language translation services are available, providing individualized assistance with appointment scheduling, and offering transportation assistance and childcare. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

A Super-Resolution Diffusion Model for Recovering Bone Microstructure from CT Images

Purpose

To use a diffusion-based deep learning model to recover bone microstructure from low-resolution images of the proximal femur, a common site of traumatic osteoporotic fractures.

Materials and Methods

Training and testing data in this retrospective study consisted of high-resolution cadaveric micro-CT scans (n = 26), which served as ground truth. The images were downsampled prior to use for model training. The model was used to increase spatial resolution in these low-resolution images threefold, from 0.72 mm to 0.24 mm, sufficient to visualize bone microstructure. Model performance was validated using microstructural metrics and finite element simulation-derived stiffness of trabecular regions. Performance was also evaluated across a handful of image quality assessment metrics. Correlations between model performance and ground truth were assessed using intraclass correlation coefficients (ICCs) and Pearson correlation coefficients.

Results

Compared with popular deep learning baselines, the proposed model exhibited greater accuracy (mean ICC of proposed model, 0.92 vs ICC of next best method, 0.83) and lower bias (mean difference in means, 3.80% vs 10.00%, respectively) across the physiologic metrics. Two gradient-based image quality metrics strongly correlated with accuracy across structural and mechanical criteria (r > 0.89).

Conclusion

The proposed method may enable accurate measurements of bone structure and strength with a radiation dose on par with current clinical imaging protocols, improving the viability of clinical CT for assessing bone health.Keywords: CT, Image Postprocessing, Skeletal-Appendicular, Long Bones, Radiation Effects, Quantification, Prognosis, Semisupervised Learning Online supplemental material is available for this article. © RSNA, 2023.

Quantification of Low-Attenuation Plaque Burden from Coronary CT Angiography: A Head-to-Head Comparison with Near-Infrared Spectroscopy Intravascular US

Purpose

To determine the association between low-attenuation plaque (LAP) burden at coronary CT angiography (CCTA) and plaque morphology determined with near-infrared spectroscopy intravascular US (NIRS-IVUS) and to compare the discriminative ability for NIRS-IVUS-verified high-risk plaques (HRPs) between LAP burden and visual assessment of LAP.

Materials and Methods

This Health Insurance Portability and Accountability Act-compliant retrospective study included consecutive patients who underwent CCTA before NIRS-IVUS between October 2019 and October 2022 at two facilities. LAPs were visually identified as having a central focal area of less than 30 HU using the pixel lens technique. LAP burden was calculated as the volume of voxels with less than 30 HU divided by vessel volume. HRPs were defined as plaques with one of the following NIRS-IVUS-derived high-risk features: maximum 4-mm lipid core burden index greater than 400 (lipid-rich plaque), an echolucent zone (intraplaque hemorrhage), or echo attenuation (cholesterol clefts). Multivariable analysis was performed to evaluate NIRS-IVUS-derived parameters associated with LAP burden. The discriminative ability for NIRS-IVUS-verified HRPs was compared using receiver operating characteristic analysis.

Results

In total, 273 plaques in 141 patients (median age, 72 years; IQR, 63-78 years; 106 males) were analyzed. All the NIRS-IVUS-derived high-risk features were independently linked to LAP burden (P < .01 for all). LAP burden increased with the number of high-risk features (P < .001) and had better discriminative ability for HRPs than plaque attenuation by visual assessment (area under the receiver operating characteristic curve, 0.93 vs 0.89; P = .02).

Conclusion

Quantification of LAP burden improved HRP assessment compared with visual assessment. LAP burden was associated with the accumulation of HRP morphology.Keywords: Coronary CT Angiography, Intraplaque Hemorrhage, Lipid-Rich Plaque, Low Attenuation Plaque, Near-Infrared Spectroscopy Intravascular Ultrasound Supplemental material is available for this article. See also the commentary by Ferencik in this issue.© RSNA, 2023.

Repeatability of MRI Biomarkers in Nonalcoholic Fatty Liver Disease: The NIMBLE Consortium

Background There is a need for reliable noninvasive methods for diagnosing and monitoring nonalcoholic fatty liver disease (NAFLD). Thus, the multidisciplinary Non-invasive Biomarkers of Metabolic Liver disease (NIMBLE) consortium was formed to identify and advance the regulatory qualification of NAFLD imaging biomarkers. Purpose To determine the different-day same-scanner repeatability coefficient of liver MRI biomarkers in patients with NAFLD at risk for steatohepatitis. Materials and Methods NIMBLE 1.2 is a prospective, observational, single-center short-term cross-sectional study (October 2021 to June 2022) in adults with NAFLD across a spectrum of low, intermediate, and high likelihood of advanced fibrosis as determined according to the fibrosis based on four factors (FIB-4) index. Participants underwent up to seven MRI examinations across two visits less than or equal to 7 days apart. Standardized imaging protocols were implemented with six MRI scanners from three vendors at both 1.5 T and 3 T, with central analysis of the data performed by an independent reading center (University of California, San Diego). Trained analysts, who were blinded to clinical data, measured the MRI proton density fat fraction (PDFF), liver stiffness at MR elastography (MRE), and visceral adipose tissue (VAT) for each participant. Point estimates and CIs were calculated using χ2 distribution and statistical modeling for pooled repeatability measures. Results A total of 17 participants (mean age, 58 years ± 8.5 [SD]; 10 female) were included, of which seven (41.2%), six (35.3%), and four (23.5%) participants had a low, intermediate, or high likelihood of advanced fibrosis, respectively. The different-day same-scanner mean measurements were 13%-14% for PDFF, 6.6 L for VAT, and 3.15 kPa for two-dimensional MRE stiffness. The different-day same-scanner repeatability coefficients were 0.22 L (95% CI: 0.17, 0.29) for VAT, 0.75 kPa (95% CI: 0.6, 0.99) for MRE stiffness, 1.19% (95% CI: 0.96, 1.61) for MRI PDFF using magnitude reconstruction, 1.56% (95% CI: 1.26, 2.07) for MRI PDFF using complex reconstruction, and 19.7% (95% CI: 15.8, 26.2) for three-dimensional MRE shear modulus. Conclusion This preliminary study suggests that thresholds of 1.2%-1.6%, 0.22 L, and 0.75 kPa for MRI PDFF, VAT, and MRE, respectively, should be used to discern measurement error from real change in patients with NAFLD. ClinicalTrials.gov registration no. NCT05081427 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kozaka and Matsui in this issue.

Brain Growth Charts for Quantitative Analysis of Pediatric Clinical Brain MRI Scans with Limited Imaging Pathology

Background Clinically acquired brain MRI scans represent a valuable but underused resource for investigating neurodevelopment due to their technical heterogeneity and lack of appropriate controls. These barriers have curtailed retrospective studies of clinical brain MRI scans compared with more costly prospectively acquired research-quality brain MRI scans. Purpose To provide a benchmark for neuroanatomic variability in clinically acquired brain MRI scans with limited imaging pathology (SLIPs) and to evaluate if growth charts from curated clinical MRI scans differed from research-quality MRI scans or were influenced by clinical indication for the scan. Materials and Methods In this secondary analysis of preexisting data, clinical brain MRI SLIPs from an urban pediatric health care system (individuals aged ≤22 years) were scanned across nine 3.0-T MRI scanners. The curation process included manual review of signed radiology reports and automated and manual quality review of images without gross pathology. Global and regional volumetric imaging phenotypes were measured using two image segmentation pipelines, and clinical brain growth charts were quantitatively compared with charts derived from a large set of research controls in the same age range by means of Pearson correlation and age at peak volume. Results The curated clinical data set included 532 patients (277 male; median age, 10 years [IQR, 5-14 years]; age range, 28 days after birth to 22 years) scanned between 2005 and 2020. Clinical brain growth charts were highly correlated with growth charts derived from research data sets (22 studies, 8346 individuals [4947 male]; age range, 152 days after birth to 22 years) in terms of normative developmental trajectories predicted by the models (median r = 0.979). Conclusion The clinical indication of the scans did not significantly bias the output of clinical brain charts. Brain growth charts derived from clinical controls with limited imaging pathology were highly correlated with brain charts from research controls, suggesting the potential of curated clinical MRI scans to supplement research data sets. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Ertl-Wagner and Pai in this issue.

Contrast-enhanced US Evaluation of Hepatocellular Carcinoma Response to Chemoembolization: A Prospective Multicenter Trial

Background Contrast-enhanced (CE) US has been studied for use in the detection of residual viable hepatocellular carcinoma (HCC) after locoregional therapy, but multicenter data are lacking. Purpose To compare two-dimensional (2D) and three-dimensional (3D) CE US diagnostic performance with that of CE MRI or CT, the current clinical standard, in the detection of residual viable HCC after transarterial chemoembolization (TACE) in a prospective multicenter trial. Materials and Methods Participants aged at least 21 years with US-visible HCC scheduled for TACE were consecutively enrolled at one of three participating academic medical centers from May 2016 to March 2022. Each underwent baseline 2D and 3D CE US before TACE, 2D and 3D CE US 1-2 weeks and/or 4-6 weeks after TACE, and CE MRI or CT 4-6 weeks after TACE. CE US and CE MRI or CT were evaluated by three fellowship-trained radiologists for the presence or absence of viable tumors and were compared with reference standards of pathology (18%), angiography on re-treatment after identification of residual disease at 1-2-month follow-up imaging (31%), 4-8-month CE MRI or CT (42%), or short-term (approximately 1-2 months) CE MRI or CT if clinically decompensated and estimated viability was greater than 50% at imaging (9%). Diagnostic performance criteria, including sensitivity and specificity, were obtained for each modality and time point with generalized estimating equation analysis. Results A total of 132 participants were included (mean age, 64 years ± 7 [SD], 87 male). Sensitivity of 2D CE US 4-6 weeks after TACE was 91% (95% CI: 84, 95), which was higher than that of CE MRI or CT (68%; 95% CI: 58, 76; P < .001). Sensitivity of 3D CE US 4-6 weeks after TACE was 89% (95% CI: 81, 94), which was higher than that of CE MRI or CT (P < .001), with no evidence of a difference from 2D CE US (P = .22). CE MRI or CT had 85% (95% CI: 76, 91) specificity, higher than that of 4-6-week 2D and 3D CE US (70% [95% CI: 56, 80] and 67% [95% CI: 53, 78], respectively; P = .046 and P = .023, respectively). No evidence of differences in any diagnostic criteria were observed between 1-2-week and 4-6-week 2D CE US (P > .21). Conclusion The 2D and 3D CE US examinations 4-6 weeks after TACE revealed higher sensitivity in the detection of residual HCC than CE MRI or CT, albeit with lower specificity. Importantly, CE US performance was independent of follow-up time. Clinical trial registration no. NCT02764801 © RSNA, 2023 Supplemental material is available for this article.

Triple-Negative Breast Cancer: Histopathologic Features, Genomics, and Treatment

Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive group of tumors that are defined by the absence of estrogen and progesterone receptors and lack of ERBB2 (formerly HER2 or HER2/neu) overexpression. TNBC accounts for 8%-13% of breast cancers. In addition, it accounts for a higher proportion of breast cancers in younger women compared with those in older women, and it disproportionately affects non-Hispanic Black women. TNBC has high metastatic potential, and the risk of recurrence is highest during the 5 years after it is diagnosed. TNBC exhibits benign morphologic imaging features more frequently than do other breast cancer subtypes. Mammography can be suboptimal for early detection of TNBC owing to factors that include the fast growth of this cancer, increased mammographic density in young women, and lack of the typical features of malignancy at imaging. US is superior to mammography for TNBC detection, but benign-appearing features can lead to misdiagnosis. Breast MRI is the most sensitive modality for TNBC detection. Most cases of TNBC are treated with neoadjuvant chemotherapy, followed by surgery and radiation. MRI is the modality of choice for evaluating the response to neoadjuvant chemotherapy. Survival rates for individuals with TNBC are lower than those for persons with hormone receptor-positive and human epidermal growth factor receptor 2-positive cancers. The 5-year survival rates for patients with localized, regional, and distant disease at diagnosis are 91.3%, 65.8%, and 12.0%, respectively. The early success of immunotherapy has raised hope regarding the development of personalized strategies to treat TNBC. Imaging and tumor biomarkers are likely to play a crucial role in the prediction of TNBC treatment response and TNBC patient survival in the future. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum

Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniques can detect complex patterns in MRI data and have potential for noninvasive characterization of ATN status. Purpose To use deep learning to predict PET-determined ATN biomarker status using MRI and readily available diagnostic data. Materials and Methods MRI and PET data were retrospectively collected from the Alzheimer's Disease Imaging Initiative. PET scans were paired with MRI scans acquired within 30 days, from August 2005 to September 2020. Pairs were randomly split into subsets as follows: 70% for training, 10% for validation, and 20% for final testing. A bimodal Gaussian mixture model was used to threshold PET scans into positive and negative labels. MRI data were fed into a convolutional neural network to generate imaging features. These features were combined in a logistic regression model with patient demographics, APOE gene status, cognitive scores, hippocampal volumes, and clinical diagnoses to classify each ATN biomarker component as positive or negative. Area under the receiver operating characteristic curve (AUC) analysis was used for model evaluation. Feature importance was derived from model coefficients and gradients. Results There were 2099 amyloid (mean patient age, 75 years ± 10 [SD]; 1110 male), 557 tau (mean patient age, 75 years ± 7; 280 male), and 2768 FDG PET (mean patient age, 75 years ± 7; 1645 male) and MRI pairs. Model AUCs for the test set were as follows: amyloid, 0.79 (95% CI: 0.74, 0.83); tau, 0.73 (95% CI: 0.58, 0.86); and neurodegeneration, 0.86 (95% CI: 0.83, 0.89). Within the networks, high gradients were present in key temporal, parietal, frontal, and occipital cortical regions. Model coefficients for cognitive scores, hippocampal volumes, and APOE status were highest. Conclusion A deep learning algorithm predicted each component of PET-determined ATN status with acceptable to excellent efficacy using MRI and other available diagnostic data. © RSNA, 2023 Supplemental material is available for this article.

Functional MRI in Neuro-Oncology: State of the Art and Future Directions

Since its discovery in the early 1990s, functional MRI (fMRI) has been used to study human brain function. One well-established application of fMRI in the clinical setting is the neurosurgical planning of patients with brain tumors near eloquent cortical areas. Clinical fMRI aims to preoperatively identify eloquent cortices that serve essential functions in daily life, such as hand movement and language. The primary goal of neurosurgery is to maximize tumor resection while sparing eloquent cortices adjacent to the tumor. When a lesion presents in the vicinity of an eloquent cortex, surgeons may use fMRI to plan their best surgical approach by determining the proximity of the lesion to regions of activation, providing guidance for awake brain surgery and intraoperative brain mapping. The acquisition of fMRI requires patient preparation prior to imaging, determination of functional paradigms, monitoring of patient performance, and both processing and analysis of images. Interpretation of fMRI maps requires a strong understanding of functional neuroanatomy and familiarity with the technical limitations frequently present in brain tumor imaging, including neurovascular uncoupling, patient compliance, and data analysis. This review discusses clinical fMRI in neuro-oncology, relevant ongoing research topics, and prospective future developments in this exciting discipline.

Local Staging of Prostate Cancer at MRI: What the Urologist and Radiation Oncologist Want to Know

This slide presentation provides an overview of prostate cancer risk stratification and management, reviews key anatomic and imaging principles pertaining to local staging of prostate cancer, and highlights inflection points where MRI findings regarding local staging may modify clinical management.

The RSNA Cervical Spine Fracture CT Dataset

This dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/.

Comparative Performance of Contrast-enhanced Mammography, Abbreviated Breast MRI, and Standard Breast MRI for Breast Cancer Screening

Background Contrast-enhanced mammography (CEM) and abbreviated breast MRI (ABMRI) are emerging alternatives to standard MRI for supplemental breast cancer screening. Purpose To compare the diagnostic performance of CEM, ABMRI, and standard MRI. Materials and Methods This single-institution, prospective, blinded reader study included female participants referred for breast MRI from January 2018 to June 2021. CEM was performed within 14 days of standard MRI; ABMRI was produced from standard MRI images. Two readers independently interpreted each CEM and ABMRI after a washout period. Examination-level performance metrics calculated were recall rate, cancer detection, and false-positive biopsy recommendation rates per 1000 examinations and sensitivity, specificity, and positive predictive value of biopsy recommendation. Bootstrap and permutation tests were used to calculate 95% CIs and compare modalities. Results Evaluated were 492 paired CEM and ABMRI interpretations from 246 participants (median age, 51 years; IQR, 43-61 years). On 49 MRI scans with lesions recommended for biopsy, nine lesions showed malignant pathology. No differences in ABMRI and standard MRI performance were identified. Compared with standard MRI, CEM demonstrated significantly lower recall rate (14.0% vs 22.8%; difference, -8.7%; 95% CI: -14.0, -3.5), lower false-positive biopsy recommendation rate per 1000 examinations (65.0 vs 162.6; difference, -97.6; 95% CI: -146.3, -50.8), and higher specificity (87.8% vs 80.2%; difference, 7.6%; 95% CI: 2.3, 13.1). Compared with standard MRI, CEM had significantly lower cancer detection rate (22.4 vs 36.6; difference, -14.2; 95% CI: -28.5, -2.0) and sensitivity (61.1% vs 100%; difference, -38.9%; 95% CI: -66.7, -12.5). The performance differences between CEM and ABMRI were similar to those observed between CEM and standard MRI. Conclusion ABMRI had comparable performance to standard MRI and may support more efficient MRI screening. CEM had lower recall and higher specificity compared with standard MRI or ABMRI, offset by lower cancer detection rate and sensitivity compared with standard MRI. These trade-offs warrant further consideration of patient population characteristics before widespread screening with CEM. Clinical trial registration no. NCT03517813 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Chang in this issue.

Mapping the Spatial Extent of Hypoperfusion in Chronic Thromboembolic Pulmonary Hypertension Using Multienergy CT

Purpose

To assess if a novel automated method to spatially delineate and quantify the extent of hypoperfusion on multienergy CT angiograms can aid the evaluation of chronic thromboembolic pulmonary hypertension (CTEPH) disease severity.

Materials and Methods

Multienergy CT angiograms obtained between January 2018 and December 2020 in 51 patients with CTEPH (mean age, 47 years ± 17 [SD]; 27 women) were retrospectively compared with those in 110 controls with no imaging findings suggestive of pulmonary vascular abnormalities (mean age, 51 years ± 16; 81 women). Parenchymal iodine values were automatically isolated using deep learning lobar lung segmentations. Low iodine concentration was used to delineate areas of hypoperfusion and calculate hypoperfused lung volume (HLV). Receiver operating characteristic curves, correlations with preoperative and postoperative changes in invasive hemodynamics, and comparison with visual assessment of lobar hypoperfusion by two expert readers were evaluated.

Results

Global HLV correctly separated patients with CTEPH from controls (area under the receiver operating characteristic curve = 0.84; 10% HLV cutoff: 90% sensitivity, 72% accuracy, and 64% specificity) and correlated moderately with hemodynamic severity at time of imaging (pulmonary vascular resistance [PVR], ρ = 0.67; P < .001) and change after surgical treatment (∆PVR, ρ = -0.61; P < .001). In patients surgically classified as having segmental disease, global HLV correlated with preoperative PVR (ρ = 0.81) and postoperative ∆PVR (ρ = -0.70). Lobar HLV correlated moderately with expert reader lobar assessment (ρHLV = 0.71 for reader 1; ρHLV = 0.67 for reader 2).

Conclusion

Automated quantification of hypoperfused areas in patients with CTEPH can be performed from clinical multienergy CT examinations and may aid clinical evaluation, particularly in patients with segmental-level disease.Keywords: CT-Spectral Imaging (Multienergy), Pulmonary, Pulmonary Arteries, Embolism/Thrombosis, Chronic Thromboembolic Pulmonary Hypertension, Multienergy CT, Hypoperfusion© RSNA, 2023.

Conquering the Cobb Angle: A Deep Learning Algorithm for Automated, Hardware-Invariant Measurement of Cobb Angle on Radiographs in Patients with Scoliosis

Scoliosis is a disease estimated to affect more than 8% of adults in the United States. It is diagnosed with use of radiography by means of manual measurement of the angle between maximally tilted vertebrae on a radiograph (ie, the Cobb angle). However, these measurements are time-consuming, limiting their use in scoliosis surgical planning and postoperative monitoring. In this retrospective study, a pipeline (using the SpineTK architecture) was developed that was trained, validated, and tested on 1310 anterior-posterior images obtained with a low-dose stereoradiographic scanning system and radiographs obtained in patients with suspected scoliosis to automatically measure Cobb angles. The images were obtained at six centers (2005-2020). The algorithm measured Cobb angles on hold-out internal (n = 460) and external (n = 161) test sets with less than 2° error (intraclass correlation coefficient, 0.96) compared with ground truth measurements by two experienced radiologists. Measurements, produced in less than 0.5 second, did not differ significantly (P = .05 cutoff) from ground truth measurements, regardless of the presence or absence of surgical hardware (P = .80), age (P = .58), sex (P = .83), body mass index (P = .63), scoliosis severity (P = .44), or image type (low-dose stereoradiographic image vs radiograph; P = .51) in the patient. These findings suggest that the algorithm is highly robust across different clinical characteristics. Given its automated, rapid, and accurate measurements, this network may be used for monitoring scoliosis progression in patients. Keywords: Cobb Angle, Convolutional Neural Network, Deep Learning Algorithms, Pediatrics, Machine Learning Algorithms, Scoliosis, Spine Supplemental material is available for this article. © RSNA, 2023.

Effect of Longitudinal Variation in Tumor Volume Estimation for MRI-guided Personalization of Breast Cancer Neoadjuvant Treatment

Purpose To investigate the impact of longitudinal variation in functional tumor volume (FTV) underestimation and overestimation in predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC). Materials and Methods Women with breast cancer who were enrolled in the prospective I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2) from May 2010 to November 2016 were eligible for this retrospective analysis. Participants underwent four MRI examinations during NAC treatment. FTV was calculated based on automated segmentation. Baseline FTV before treatment (FTV0) and the percentage of FTV change at early treatment and inter-regimen time points relative to baseline (∆FTV1 and ∆FTV2, respectively) were classified into high-standard or standard groups based on visual assessment of FTV under- and overestimation. Logistic regression models predicting pCR using single predictors (FTV0, ∆FTV1, and ∆FTV2) and multiple predictors (all three) were developed using bootstrap resampling with out-of-sample data evaluation with the area under the receiver operating characteristic curve (AUC) independently in each group. Results This study included 432 women (mean age, 49.0 years ± 10.6 [SD]). In the FTV0 model, the high-standard and standard groups showed similar AUCs (0.61 vs 0.62). The high-standard group had a higher estimated AUC compared with the standard group in the ∆FTV1 (0.74 vs 0.63), ∆FTV2 (0.79 vs 0.62), and multiple predictor models (0.85 vs 0.64), with a statistically significant difference for the latter two models (P = .03 and P = .01, respectively). Conclusion The findings in this study suggest that longitudinal variation in FTV estimation needs to be considered when using early FTV change as an MRI-based criterion for breast cancer treatment personalization. Keywords: Breast, Cancer, Dynamic Contrast-enhanced, MRI, Tumor Response ClinicalTrials.gov registration no. NCT01042379 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Ram in this issue.

A Radiomics Model Based on Synthetic MRI Acquisition for Predicting Neoadjuvant Systemic Treatment Response in Triple-Negative Breast Cancer

Purpose To determine if a radiomics model based on quantitative maps acquired with synthetic MRI (SyMRI) is useful for predicting neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). Materials and Methods In this prospective study, 181 women diagnosed with stage I-III TNBC were scanned with a SyMRI sequence at baseline and at midtreatment (after four cycles of NAST), producing T1, T2, and proton density (PD) maps. Histopathologic analysis at surgery was used to determine pathologic complete response (pCR) or non-pCR status. From three-dimensional tumor contours drawn on the three maps, 310 histogram and textural features were extracted, resulting in 930 features per scan. Radiomic features were compared between pCR and non-pCR groups by using Wilcoxon rank sum test. To build a multivariable predictive model, logistic regression with elastic net regularization and cross-validation was performed for texture feature selection using 119 participants (median age, 52 years [range, 26-77 years]). An independent testing cohort of 62 participants (median age, 48 years [range, 23-74 years]) was used to evaluate and compare the models by area under the receiver operating characteristic curve (AUC). Results Univariable analysis identified 15 T1, 10 T2, and 12 PD radiomic features at midtreatment that predicted pCR with an AUC greater than 0.70 in both the training and testing cohorts. Multivariable radiomics models of maps acquired at midtreatment demonstrated superior performance over those acquired at baseline, achieving AUCs as high as 0.78 and 0.72 in the training and testing cohorts, respectively. Conclusion SyMRI-based radiomic features acquired at midtreatment are potentially useful for identifying early NAST responders in TNBC. Keywords: MR Imaging, Breast, Outcomes Analysis ClinicalTrials.gov registration no. NCT02276443 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Houser and Rapelyea in this issue.

PET/MRI and Bioluminescent Imaging Identify Hypoxia as a Cause of Programmed Cell Death Ligand 1 Image Heterogeneity

Purpose To examine the association between hypoxia and programmed cell death ligand 1 (PD-L1) expression using bioluminescence imaging (BLI) and PET/MRI in a syngeneic mouse model of triple-negative breast cancer (TNBC). Materials and Methods PET/MRI and optical imaging were used to determine the role of hypoxia in altering PD-L1 expression using a syngeneic TNBC model engineered to express luciferase under hypoxia. Results Imaging showed a close spatial association between areas of hypoxia and increased PD-L1 expression in the syngeneic murine (4T1) tumor model. Mouse and human TNBC cells exposed to hypoxia exhibited a significant increase in PD-L1 expression, consistent with the in vivo imaging data. The role of hypoxia in increasing PD-L1 expression was further confirmed by using The Cancer Genome Atlas analyses of different human TNBCs. Conclusion These results have identified the potential role of hypoxia in contributing to PD-L1 heterogeneity in tumors by increasing cancer cell PD-L1 expression. Keywords: Hypoxia, PD-L1, Triple-Negative Breast Cancer, PET/MRI, Bioluminescence Imaging Supplemental material is available for this article. © RSNA, 2023.

MRI Features for Identifying MYCN-amplified RB1 Wild-type Retinoblastoma

Background MYCN-amplified RB1 wild-type (MYCNARB1+/+) retinoblastoma is a rare but clinically important subtype of retinoblastoma due to its aggressive character and relative resistance to typical therapeutic approaches. Because biopsy is not indicated in retinoblastoma, specific MRI features might be valuable to identify children with this genetic subtype. Purpose To define the MRI phenotype of MYCNARB1+/+ retinoblastoma and evaluate the ability of qualitative MRI features to help identify this specific genetic subtype. Materials and Methods In this retrospective, multicenter, case-control study, MRI scans in children with MYCNARB1+/+ retinoblastoma and age-matched children with RB1-/- subtype retinoblastoma were included (case-control ratio, 1:4; scans acquired from June 2001 to February 2021; scans collected from May 2018 to October 2021). Patients with histopathologically confirmed unilateral retinoblastoma, genetic testing (RB1/MYCN status), and MRI scans were included. Associations between radiologist-scored imaging features and diagnosis were assessed with the Fisher exact test or Fisher-Freeman-Halton test, and Bonferroni-corrected P values were calculated. Results A total of 110 patients from 10 retinoblastoma referral centers were included: 22 children with MYCNARB1+/+ retinoblastoma and 88 control children with RB1-/- retinoblastoma. Children in the MYCNARB1+/+ group had a median age of 7.0 months (IQR, 5.0-9.0 months) (13 boys), while children in the RB1-/- group had a median age of 9.0 months (IQR, 4.6-13.4 months) (46 boys). MYCNARB1+/+ retinoblastomas were typically peripherally located (in 10 of 17 children; specificity, 97%; P < .001) and exhibited plaque or pleomorphic shape (in 20 of 22 children; specificity, 51%; P = .011) with irregular margins (in 16 of 22 children; specificity, 70%; P = .008) and extensive retina folding with vitreous enclosure (specificity, 94%; P < .001). MYCNARB1+/+ retinoblastomas showed peritumoral hemorrhage (in 17 of 21 children; specificity, 88%; P < .001), subretinal hemorrhage with a fluid-fluid level (in eight of 22 children; specificity, 95%; P = .005), and strong anterior chamber enhancement (in 13 of 21 children; specificity, 80%; P = .008). Conclusion MYCNARB1+/+ retinoblastomas show distinct MRI features that could enable early identification of these tumors. This may improve patient selection for tailored treatment in the future. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Rollins in this issue.

Lung Volume Dependence and Repeatability of Hyperpolarized 129Xe MRI Gas Uptake Metrics in Healthy Volunteers and Participants with COPD

Purpose

To assess the effect of lung volume on measured values and repeatability of xenon 129 (¹²⁹Xe) gas uptake metrics in healthy volunteers and participants with chronic obstructive pulmonary disease (COPD).

Materials and Methods

This Health Insurance Portability and Accountability Act-compliant prospective study included data (March 2014-December 2015) from 49 participants (19 with COPD [mean age, 67 years ± 9 (SD)]; nine women]; 25 older healthy volunteers [mean age, 59 years ± 10; 20 women]; and five young healthy women [mean age, 23 years ± 3]). Thirty-two participants underwent repeated ¹²⁹Xe and same-breath-hold proton MRI at residual volume plus one-third forced vital capacity (RV+FVC/3), with 29 also undergoing one examination at total lung capacity (TLC). The remaining 17 participants underwent imaging at TLC, RV+FVC/3, and residual volume (RV). Signal ratios between membrane, red blood cell (RBC), and gas-phase compartments were calculated using hierarchical iterative decomposition of water and fat with echo asymmetry and least-squares estimation (ie, IDEAL). Repeatability was assessed using coefficient of variation and intraclass correlation coefficient, and volume relationships were assessed using Spearman correlation and Wilcoxon rank sum tests.

Results

Gas uptake metrics were repeatable at RV+FVC/3 (intraclass correlation coefficient = 0.88 for membrane/gas; 0.71 for RBC/gas, and 0.88 for RBC/membrane). Relative ratio changes were highly correlated with relative volume changes for membrane/gas (r = -0.97) and RBC/gas (r = -0.93). Membrane/gas and RBC/gas measured at RV+FVC/3 were significantly lower in the COPD group than the corresponding healthy group (P ≤ .001). However, these differences lessened upon correction for individual volume differences (P = .23 for membrane/gas; P = .09 for RBC/gas).

Conclusion

Dissolved-phase ¹²⁹Xe MRI-derived gas uptake metrics were repeatable but highly dependent on lung volume during measurement.Keywords: Blood-Air Barrier, MRI, Chronic Obstructive Pulmonary Disease, Pulmonary Gas Exchange, Xenon Supplemental material is available for this article © RSNA, 2023.

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, P = .002), but not for historic cohort studies (0.89 vs 0.96, P = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, P < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Scaranelo in this issue.

StrainNet: Improved Myocardial Strain Analysis of Cine MRI by Deep Learning from DENSE

Purpose

To develop a three-dimensional (two dimensions + time) convolutional neural network trained with displacement encoding with stimulated echoes (DENSE) data for displacement and strain analysis of cine MRI.

Materials and Methods

In this retrospective multicenter study, a deep learning model (StrainNet) was developed to predict intramyocardial displacement from contour motion. Patients with various heart diseases and healthy controls underwent cardiac MRI examinations with DENSE between August 2008 and January 2022. Network training inputs were a time series of myocardial contours from DENSE magnitude images, and ground truth data were DENSE displacement measurements. Model performance was evaluated using pixelwise end-point error (EPE). For testing, StrainNet was applied to contour motion from cine MRI. Global and segmental circumferential strain (Ecc) derived from commercial feature tracking (FT), StrainNet, and DENSE (reference) were compared using intraclass correlation coefficients (ICCs), Pearson correlations, Bland-Altman analyses, paired t tests, and linear mixed-effects models.

Results

The study included 161 patients (110 men; mean age, 61 years ± 14 [SD]), 99 healthy adults (44 men; mean age, 35 years ± 15), and 45 healthy children and adolescents (21 males; mean age, 12 years ± 3). StrainNet showed good agreement with DENSE for intramyocardial displacement, with an average EPE of 0.75 mm ± 0.35. The ICCs between StrainNet and DENSE and FT and DENSE were 0.87 and 0.72, respectively, for global Ecc and 0.75 and 0.48, respectively, for segmental Ecc. Bland-Altman analysis showed that StrainNet had better agreement than FT with DENSE for global and segmental Ecc.

Conclusion

StrainNet outperformed FT for global and segmental Ecc analysis of cine MRI.Keywords: Image Postprocessing, MR Imaging, Cardiac, Heart, Pediatrics, Technical Aspects, Technology Assessment, Strain, Deep Learning, DENSE Supplemental material is available for this article. © RSNA, 2023.

Normative Cerebral Hemodynamics in Middle-aged and Older Adults Using 4D Flow MRI: Initial Analysis of Vascular Aging

Background Characterizing cerebrovascular hemodynamics in older adults is important for identifying disease and understanding normal neurovascular aging. Four-dimensional (4D) flow MRI allows for a comprehensive assessment of cerebral hemodynamics in a single acquisition. Purpose To establish reference intracranial blood flow and pulsatility index values in a large cross-sectional sample of middle-aged (45-65 years) and older (>65 years) adults and characterize the effect of age and sex on blood flow and pulsatility. Materials and Methods In this retrospective study, patients aged 45-93 years (cognitively unimpaired) underwent cranial 4D flow MRI between March 2010 and March 2020. Blood flow rates and pulsatility indexes from 13 major arteries and four venous sinuses and total cerebral blood flow were collected. Intraobserver and interobserver reproducibility of flow and pulsatility measures was assessed in 30 patients. Descriptive statistics (mean ± SD) of blood flow and pulsatility were tabulated for the entire group and by age and sex. Multiple linear regression and linear mixed-effects models were used to assess the effect of age and sex on total cerebral blood flow and vessel-specific flow and pulsatility, respectively. Results There were 759 patients (mean age, 65 years ± 8 [SD]; 506 female patients) analyzed. For intra- and interobserver reproducibility, median intraclass correlation coefficients were greater than 0.90 for flow and pulsatility measures across all vessels. Regression coefficients β ± standard error from multiple linear regression showed a 4 mL/min decrease in total cerebral blood flow each year (age β = -3.94 mL/min per year ± 0.44; P < .001). Mixed effects showed a 1 mL/min average annual decrease in blood flow (age β = -0.95 mL/min per year ± 0.16; P < .001) and 0.01 arbitrary unit (au) average annual increase in pulsatility over all vessels (age β = 0.011 au per year ± 0.001; P < .001). No evidence of sex differences was observed for flow (β = -1.60 mL/min per male patient ± 1.77; P = .37), but pulsatility was higher in female patients (sex β = -0.018 au per male patient ± 0.008; P = .02). Conclusion Normal reference values for blood flow and pulsatility obtained using four-dimensional flow MRI showed correlations with age. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Steinman in this issue.

Quantitative CT Evaluation of Emphysema Progression over 10 Years in the COPDGene Study

Background Long-term studies of chronic obstructive pulmonary disease (COPD) can evaluate emphysema progression. Adjustment for differences in equipment and scanning protocols of individual CT examinations have not been studied extensively. Purpose To evaluate emphysema progression in current and former smokers in the COPDGene cohort over three imaging points obtained at 5-year intervals accounting for individual CT parameters. Materials and Methods Current and former cigarette smokers enrolled between 2008 and 2011 from the COPDGene study were prospectively followed for 10 years between 2008 and 2020. Extent of emphysema as adjusted lung density (ALD) from quantitative CT was measured at baseline and at 5- and 10-year follow-up. Linear mixed models adjusted for CT technical characteristics were constructed to evaluate emphysema progression. Mean annual changes in ALD over consecutive 5-year study periods were estimated by smoking status and baseline emphysema. Results Of 8431 participants at baseline (mean age, 60 years ± 9 [SD]; 3905 female participants), 4913 were at 5-year follow-up and 1544 participants were at 10-year follow-up. There were 4134 (49%) participants who were current smokers, and 4449 (53%) participants had more than trace emphysema at baseline. Current smokers with more than trace emphysema showed the largest decline in ALD, with mean annual decreases of 1.4 g/L (95% CI: 1.2, 1.5) in the first 5 years and 0.9 g/L (95% CI: 0.7, 1.2) in the second 5 years. Accounting for CT noise, field of view, and scanner model improved model fit for estimation of emphysema progression (P < .001 by likelihood ratio test). Conclusion Evaluation at CT of emphysema progression in the COPDGene study showed that, during the span of 10 years, participants with pre-existing emphysema who continued smoking had the largest decline in ALD. Adjusting for CT equipment and protocol factors improved these longitudinal estimates. Clinical trial registration no. NCT00608764 © RSNA, 2023 Supplemental material is available for this article. See the editorial by Parraga and Kirby in this issue.

Differences in Molecular Subtype Reference Standards Impact AI-based Breast Cancer Classification with Dynamic Contrast-enhanced MRI

Background Breast cancer tumors can be identified as different luminal molecular subtypes depending on either immunohistochemical (IHC) staining or St Gallen criteria that includes Ki-67. Purpose To characterize molecular subtypes and understand the impact of disagreement among IHC and St Gallen molecular subtype reference standards on artificial intelligence classification of luminal A and luminal B tumors with use of radiomic features extracted from dynamic contrast-enhanced (DCE) MRI scans. Materials and Methods In this retrospective study, 28 radiomic features previously extracted from DCE-MRI scans of breast tumors imaged between February 2015 and October 2017 were examined in the following groups: (a) tumors classified as luminal A by both reference standards ("agreement"), (b) tumors classified as luminal A by IHC and luminal B by St Gallen ("disagreement"), and (c) tumors classified as luminal B by both ("agreement"). Luminal A or luminal B tumor classification with use of radiomic features was conducted with use of three sets: (a) IHC molecular subtyping, (b) St Gallen molecular subtyping, and (c) agreement tumors. The Kruskal-Wallis test was followed by the Mann-Whitney U test to determine pair-wise differences of radiomic features among agreement and disagreement tumors. Fivefold cross-validation with use of stepwise feature selection and linear discriminant analysis classified tumors in each set, with performance measured with use of area under the receiver operating characteristic curve (AUC). Results A total of 877 breast cancer tumors from 872 women (mean age, 48 years [range, 19-75 years]) were analyzed. Six features (sphericity, irregularity, surface area to volume ratio, variance of radial gradient histogram, sum average, volume of most enhancing voxels) were different (P ≤ .001) among agreement and disagreement tumors. AUC (median, 0.74 [95% CI: 0.68, 0.80]) was higher than when using tumors subtyped by either reference standard (IHC, 0.66 [0.60, 0.71], P = .003; St Gallen, 0.62 [0.58, 0.67], P = .001). Conclusion Differences in reference standards can hinder artificial intelligence classification performance of luminal molecular subtypes with dynamic contrast-enhanced MRI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bae in this issue.

Multicenter Validation of Abbreviated MRI for Detecting Early-Stage Hepatocellular Carcinoma

Background Abbreviated MRI is a proposed paradigm shift for hepatocellular carcinoma (HCC) surveillance, but data on its performance are lacking for histopathologically confirmed early-stage HCC. Purpose To evaluate the sensitivity and specificity of dynamic contrast-enhanced abbreviated MRI for early-stage HCC detection, using surgical pathologic findings as the reference standard. Materials and Methods This retrospective study was conducted at three U.S. liver transplant centers in patients with cirrhosis who underwent liver resection or transplant between January 2009 and December 2019 and standard "full" liver MRI with and without contrast enhancement within 3 months before surgery. Patients who had HCC-directed treatment before surgery were excluded. Dynamic abbreviated MRI examinations were simulated from the presurgical full MRI by selecting the coronal T2-weighted and axial three-dimensional fat-suppressed T1-weighted dynamic contrast-enhanced sequences at precontrast, late arterial, portal venous, and delayed phases. Two abdominal radiologists at each center independently interpreted the simulated abbreviated examinations with use of the Liver Imaging Reporting and Data System version 2018. Patients with any high-risk liver observations (>LR-3) were classified as positive; otherwise, they were classified as negative. With liver pathologic findings as the reference standard for the presence versus absence of early-stage HCC, the sensitivity, specificity, and their 95% CIs were calculated. Logistic regression was used to identify factors associated with correct classification. Results A total of 161 patients with early-stage HCC (median age, 62 years [IQR, 58-67 years]; 123 men) and 138 patients without HCC (median age, 55 years [IQR, 47-63 years]; 85 men) were confirmed with surgical pathologic findings. The sensitivity and specificity of abbreviated MRI were 88.2% (142 of 161 patients) (95% CI: 83.5, 92.5) and 89.1% (123 of 138 patients) (95% CI: 84.4, 93.8), respectively. Sensitivity was lower for Child-Pugh class B or C versus Child-Pugh class A cirrhosis (64.1% vs 94.2%; P < .001). Conclusion With surgical pathologic findings as the reference standard, dynamic abbreviated MRI had high sensitivity and specificity for early-stage hepatocellular carcinoma detection in patients with compensated cirrhosis but lower sensitivity in those with decompensated cirrhosis. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kim in this issue.

MRI Quantification of Cortical Bone Porosity, Mineralization, and Morphologic Structure in Postmenopausal Osteoporosis

Background Preclinical studies have suggested that solid-state MRI markers of cortical bone porosity, morphologic structure, mineralization, and osteoid density are useful measures of bone health. Purpose To explore whether MRI markers of cortical bone porosity, morphologic structure, mineralization, and osteoid density are affected in postmenopausal osteoporosis (OP) and to examine associations between MRI markers and bone mineral density (BMD) in postmenopausal women. Materials and Methods In this single-center study, postmenopausal women were prospectively recruited from January 2019 to October 2020 into two groups: participants with OP who had not undergone treatment, defined as having any dual-energy x-ray absorptiometry (DXA) T-score of -2.5 or less, and age-matched control participants without OP (hereafter, non-OP). Participants underwent MRI in the midtibia, along with DXA in the hip and spine, and peripheral quantitative CT in the midtibia. Specifically, MRI measures of cortical bone porosity (pore water and total water), osteoid density (bound water [BW]), morphologic structure (cortical bone thickness), and mineralization (phosphorous [P] density [31P] and 31P-to-BW concentration ratio) were quantified at 3.0 T. MRI measures were compared between OP and non-OP groups and correlations with BMD were assessed. Results Fifteen participants with OP (mean age, 63 years ± 5 [SD]) and 19 participants without OP (mean age, 65 years ± 6) were evaluated. The OP group had elevated pore water (11.6 mol/L vs 9.5 mol/L; P = .007) and total water densities (21.2 mol/L vs 19.7 mol/L; P = .03), and had lower cortical bone thickness (4.8 mm vs 5.6 mm; P < .001) and 31P density (6.4 mol/L vs 7.5 mol/L; P = .01) than the non-OP group, respectively, although there was no evidence of a difference in BW or 31P-to-BW concentration ratio. Pore and total water densities were inversely associated with DXA and peripheral quantitative CT BMD (P < .001), whereas cortical bone thickness and 31P density were positively associated with DXA and peripheral quantitative CT BMD (P = .01). BW, 31P density, and 31P-to-BW concentration ratio were positively associated with DXA (P < .05), but not with peripheral quantitative CT. Conclusion Solid-state MRI of cortical bone was able to help detect potential impairments in parameters reflecting porosity, morphologic structure, and mineralization in postmenopausal osteoporosis. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bae in this issue.

Watch-and-Wait Approach to Rectal Cancer: The Role of Imaging

The diagnosis and treatment of rectal cancer have evolved dramatically over the past several decades. At the same time, its incidence has increased in younger populations. This review will inform the reader of advances in both diagnosis and treatment. These advances have led to the watch-and-wait approach, otherwise known as nonsurgical management. This review briefly outlines changes in medical and surgical treatment, advances in MRI technology and interpretation, and landmark studies or trials that have led to this exciting juncture. Herein, the authors delve into current state-of-the-art methods to assess response to treatment with MRI and endoscopy. Currently, these methods for avoiding surgery can be used to detect a complete clinical response in as many as 50% of patients with rectal cancer. Finally, the limitations of imaging and endoscopy and future challenges will be discussed.