Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring.

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

Current and Future States of Natural Killer Cell-Based Immunotherapy in Hepatocellular Carcinoma.

Natural killer (NK) cells are innate lymphoid cells that exhibit high levels of cytotoxicity against NK-specific targets. NK cells also produce various cytokines, and interact with T cells, B cells, and dendritic cells to effectively serve as frontliners of the innate immune system. Produce various cytokines, and interact with T cells, B cells, and dendritic cells to effectively serve as frontliners of the innate immune system. Moreover, NK cells constitute the second most common immune cell in the liver. These properties have drawn significant attention towards leveraging NK cells in treating liver cancer, especially hepatocellular carcinoma (HCC), which accounts for 75% of all primary liver cancer and is the fourth leading cause of cancer-related death worldwide. Notable anti-cancer functions of NK cells against HCC include activating antibody-dependent cell cytotoxicity (ADCC), facilitating Gasdermin E-mediated pyroptosis of HCC cells, and initiating an antitumor response via the cGAS-STING signaling pathway. In this review, we describe how these mechanisms work in the context of HCC. We will then discuss the existing preclinical and clinical studies that leverage NK cell activity to create single and combined immunotherapies.

Understanding Spatial Correlation Between Multiparametric MRI Performance and Prostate Cancer.

BACKGROUND: Multiparametric MRI (mpMRI) has shown a substantial impact on prostate cancer (PCa) diagnosis. However, the understanding of the spatial correlation between mpMRI performance and PCa location is still limited. PURPOSE: To investigate the association between mpMRI performance and tumor spatial location within the prostate using a prostate sector map, described by Prostate Imaging Reporting and Data System (PI-RADS) v2.1. STUDY TYPE: Retrospective. SUBJECTS: One thousand one hundred forty-three men who underwent mpMRI before radical prostatectomy between 2010 and 2022. FIELD STRENGTH/SEQUENCE: 3.0 T. T2-weighted turbo spin-echo, a single-shot spin-echo EPI sequence for diffusion-weighted imaging, and a gradient echo sequence for dynamic contrast-enhanced MRI sequences. ASSESSMENT: Integrated relative cancer prevalence (rCP), detection rate (DR), and positive predictive value (PPV) maps corresponding to the prostate sector map for PCa lesions were created. The relationship between tumor location and its detection/missing by radiologists on mpMRI compared to WMHP as a reference standard was investigated. STATISTICAL TESTS: A weighted chi-square test was performed to examine the statistical differences for rCP, DR, and PPV of the aggregated sectors within the zone, anterior/posterior, left/right prostate, and different levels of the prostate with a statistically significant level of 0.05. RESULTS: A total of 1665 PCa lesions were identified in 1143 patients, and from those 1060 lesions were clinically significant (cs)PCa tumors (any Gleason score [GS] ≥7). Our sector-based analysis utilizing weighted chi-square tests suggested that the left posterior part of PZ had a high likelihood of missing csPCa lesions at a DR of 67.0%. Aggregated sector analysis indicated that the anterior or apex locations in PZ had the significantly lowest csPCa detection at 67.3% and 71.5%, respectively. DATA CONCLUSION: Spatial characteristics of the per-lesion-based mpMRI performance for diagnosis of PCa were studied. Our results demonstrated that there is a spatial correlation between mpMRI performance and locations of PCa on the prostate. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Investigating MRI-Associated Biological Aspects of Racial Disparities in Prostate Cancer for African American and White Men.

BACKGROUND: Understanding the characteristics of multiparametric MRI (mpMRI) in patients from different racial/ethnic backgrounds is important for reducing the observed gaps in clinical outcomes. PURPOSE: To investigate the diagnostic performance of mpMRI and quantitative MRI parameters of prostate cancer (PCa) in African American (AA) and matched White (W) men. STUDY TYPE: Retrospective. SUBJECTS: One hundred twenty-nine patients (43 AA, 86 W) with histologically proven PCa who underwent mpMRI before radical prostatectomy. FIELD STRENGTH/SEQUENCE: 3.0 T, T2-weighted turbo spin echo imaging, a single-shot spin-echo EPI sequence diffusion-weighted imaging, and a gradient echo sequence dynamic contrast-enhanced MRI with an ultrafast 3D spoiled gradient-echo sequence. ASSESSMENT: The diagnostic performance of mpMRI in AA and W men was assessed using detection rates (DRs) and positive predictive values (PPVs) in zones defined by the PI-RADS v2.1 prostate sector map. Quantitative MRI parameters, including Ktrans and ve of clinically significant (cs) PCa (Gleason score ≥ 7) tumors were compared between AA and W sub-cohorts after matching age, prostate-specific antigen (PSA), and prostate volume. STATISTICAL TESTS: Weighted Pearson's chi-square and Mann-Whitney U tests with a statistically significant level of 0.05 were used to examine differences in DR and PPV and to compare parameters between AA and matched W men, respectively. RESULTS: A total number of 264 PCa lesions were identified in the study cohort. The PPVs in the peripheral zone (PZ) and posterior prostate of mpMRI for csPCa lesions were significantly higher in AA men than in matched W men (87.8% vs. 68.1% in PZ, and 89.3% vs. 69.6% in posterior prostate). The Ktrans of index csPCa lesions in AA men was significantly higher than in W men (0.25 ± 0.12 vs. 0.20 ± 0.08 min-1; P < 0.01). DATA CONCLUSION: This study demonstrated race-related differences in the diagnostic performances and quantitative MRI measures of csPCa that were not reflected in age, PSA, and prostate volume. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Characterization of Microwave Generator Energy and Ablation Volumes following Transarterial Embolization in an In Vivo Porcine Liver Model.

PURPOSE: To characterize the relationship between ablation zone volume (AZV) and microwave ablation (MWA) energy in an in vivo porcine liver model following arterial embolization. MATERIALS AND METHODS: With Institutional Animal Care and Use Committee (IACUC) approval, 11 female swine underwent either right (n = 5) or left (n = 6) hepatic artery embolization under fluoroscopic guidance. Subsequently, ultrasound (US)-guided MWA was performed in each liver segment (left lateral, left medial, right medial, and right lateral) at either 30 W (n = 4 lobes), 60 W (n = 4), 65 W (n = 20), 90 W (n = 8), 120 W (n = 4), or 140 W (n = 4) continuously for 5 minutes. Postprocedural volumetric segmentation was performed on standardized multiphase T1 magnetic resonance (MR) imaging sequences. RESULTS: Mean AZVs in embolized lobes (15.8 mL ± SD 10.6) were significantly larger than those in nonembolized lobes (11.2 mL ± SD 6.5, P < .01). MWA energy demonstrated significant positive linear correlation with both embolized (R2 = 0.66, P < .01) and nonembolized (R2 = 0.64, P < .01) lobes. The slope of the linear models corresponded to a 0.95 mL/kJ (SD ± 0.16) and 0.54 mL/kJ (SD ± 0.09) increase in ablation volume per applied kilojoule of energy (E) in embolized and nonembolized lobes, respectively. In the multivariate model, embolization status significantly modified the relationship between E and AZV as described by the following interaction term: 0.42∗E∗(embolization status) (P = .031). CONCLUSIONS: Linear models demonstrated a near 1.8-fold increase in ratio of AZV per unit E, R(AZV:E), when applied to embolized lobes relative to nonembolized lobes. Absolute AZV differences between embolized and nonembolized lobes were greater at higher-power MWA.

Impact of PSMA PET on Prostate Cancer Management.

OPINION STATEMENT: PSMA-PET has been a practice-changing imaging biomarker for the management of men with PCa. Research suggests improved accuracy over conventional imaging and other PET radiotracers in many contexts. With multiple approved PSMA-targeting radiotracers, PSMA PET will become even more available in clinical practice. Its increased use requires an understanding of the prospective data available and caution when extrapolating from prior trial data that utilized other imaging modalities. Future trials leveraging PSMA PET for treatment optimization and management decision-making will ultimately drive its clinical utility.

High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising.

OBJECTIVE: To develop and evaluate a technique combining eddy current-nulled convex optimized diffusion encoding (ENCODE) with random matrix theory (RMT)-based denoising to accelerate and improve the apparent signal-to-noise ratio (aSNR) and apparent diffusion coefficient (ADC) mapping in high-resolution prostate diffusion-weighted MRI (DWI). MATERIALS AND METHODS: Eleven subjects with clinical suspicion of prostate cancer were scanned at 3T with high-resolution (HR) (in-plane: 1.0 × 1.0 mm2) ENCODE and standard-resolution (1.6 × 2.2 mm2) bipolar DWI sequences (both had 7 repetitions for averaging, acquisition time [TA] of 5 min 50 s). HR-ENCODE was retrospectively analyzed using three repetitions (accelerated effective TA of 2 min 30 s). The RMT-based denoising pipeline utilized complex DWI signals and Marchenko-Pastur distribution-based principal component analysis to remove additive Gaussian noise in images from multiple coils, b-values, diffusion encoding directions, and repetitions. HR-ENCODE with RMT-based denoising (HR-ENCODE-RMT) was compared with HR-ENCODE in terms of aSNR in prostate peripheral zone (PZ) and transition zone (TZ). Precision and accuracy of ADC were evaluated by the coefficient of variation (CoV) between repeated measurements and mean difference (MD) compared to the bipolar ADC reference, respectively. Differences were compared using two-sided Wilcoxon signed-rank tests (P < 0.05 considered significant). RESULTS: HR-ENCODE-RMT yielded 62% and 56% higher median aSNR than HR-ENCODE (b = 800 s/mm2) in PZ and TZ, respectively (P < 0.001). HR-ENCODE-RMT achieved 63% and 70% lower ADC-CoV than HR-ENCODE in PZ and TZ, respectively (P < 0.001). HR-ENCODE-RMT ADC and bipolar ADC had low MD of 22.7 × 10-6 mm2/s in PZ and low MD of 90.5 × 10-6 mm2/s in TZ. CONCLUSIONS: HR-ENCODE-RMT can shorten the acquisition time and improve the aSNR of high-resolution prostate DWI and achieve accurate and precise ADC measurements in the prostate.

What predicts durable symptom relief of uterine fibroids treated with MRI-guided focused ultrasound? A multicenter trial in 8 academic centers.

OBJECTIVE: To identify variables predictive of durable clinical success after MRI-guided focused ultrasound (MRgFUS) treatment of uterine fibroids. MATERIALS AND METHODS: In this prospective, multicenter trial, 99 women with symptomatic uterine fibroids were treated using MRgFUS. Pelvic MRI was obtained at baseline and treatment day. The Uterine Fibroid Symptom-Quality of Life questionnaire was used to calculate a symptom severity score (SSS) at baseline and 6, 12, 24, and 36 months following treatment. Clinical, imaging, and treatment variables were correlated with symptom reduction sustained through the 12- and 24-month time points using univariable and multivariable logistic regression analyses. A novel parameter, the ratio of non-perfused volume to total fibroid load (NPV/TFL), was developed to determine association with durable outcomes. RESULTS: Post-treatment, mean symptom severity decreased at the 6-, 12-, 24-, and 36-month follow-ups (p < 0.001, all time points). In univariable analysis, three variables predicted treatment success (defined by ≥ 30-point improvement in SSS) sustained at both the 12-month and 24-month time points: increasing ratio of NPV/TFL (p = 0.002), decreasing total fibroid load (p = 0.04), and the absence of T2-weighted Funaki type 2 fibroids (p = 0.02). In multivariable analysis, the NPV/TFL was the sole predictor of durable clinical success (p = 0.01). Patients with ratios below 30% had less improvement in SSS and lacked durable clinical response compared with those between 30-79 (p = 0.03) and ≥ 80% (p = 0.01). CONCLUSION: Increased non-perfused volume relative to total fibroid volume was significantly associated with durable reduction of symptoms of abnormal uterine bleeding and bulk bother. CLINICAL RELEVANCE STATEMENT: Patient selection for sustained clinical benefit should emphasize those with likelihood of achieving high ablation ratios, as determined by imaging (e.g., device access, Funaki type) and by considering the total fibroid load, not just the primary symptomatic fibroid. TRIAL REGISTRATION: Clinical trial ID: NCT01285960. KEY POINTS: • Patient selection/treatment approach associated with durable symptom relief in MRI-guided focused ultrasound ablation of uterine fibroids remains unclear. • The ablation ratio, non-perfused volume/total fibroid volume, was positively associated with sustained symptom relief in both bleeding and bulk bother at 1- and 2-year follow-ups. • Selecting patients with imaging features that favor a high ratio of ablation to total fibroid load (including non-targeted fibroids) is the main factor in predicting durability of symptom relief after uterine fibroid treatment.

MR imaging biomarkers in HCC: outcomes correlation in liver transplant listed patients.

PURPOSE: To determine hepatocellular carcinoma (HCC) magnetic resonance imaging (MRI) biomarkers that enable the prediction of delisting from tumor progression versus successful transplantation in patients listed for orthotopic liver transplantation (OLT). METHODS: With IRB approval and HIPPA compliance, patients with HCC awaiting OLT who were delisted due to HCC progression from 2006 to 2015 were identified. Patients with adequate MR images for review were subsequently matched with a cohort of patients successfully bridged to OLT in the same time period. Matching considered the tumor stage and the dominant treatment strategy adopted to bridge the patient to OLT. Potential MRI features were evaluated by univariable and multivariable analysis using a conditional logistic model. RESULTS: There were 53 patients included in each cohort. On uni-variable analysis, significant unfavorable MR imaging features included T2 hyperintensity (odds ratio [OR], 19.0), infiltrative border (OR, 7.50), lobulated shape (OR, 4.5), T1 hypointensity (OR, 3.0), heterogeneous arterial enhancement (OR, 7.0), and corona venous enhancement (OR, 4.0). A significant favorable MR imaging feature was the presence of intralesional fat (OR = .36). The best multivariable logistic prediction model derived from the above notable features included only T1 and T2 signal intensity, border definition, and absence of intra-lesional fat as significant variables, with an area under the receiver operating characteristic curve (AUC) of .86 in the prediction of delisting. CONCLUSION: Select MR imaging features of HCC at presentation before any treatment are significantly associated with the risk of tumor progression regardless of tumor stage and treatment strategy in patients awaiting liver transplantation.

Hepatocellular Adenoma Subtypes Based on 2017 Classification System: Exploratory Study of Gadoxetate Disodium-Enhanced MRI Features With Proposal of a Diagnostic Algorithm.

BACKGROUND. The classification of hepatocellular adenomas (HCAs) was updated in 2017 on the basis of genetic and molecular analysis. OBJECTIVE. The purpose of this article was to evaluate features on gadoxetate disodium-enhanced MRI of HCA subtypes on the basis of the 2017 classification and to propose a diagnostic algorithm for determining subtype using these features. METHODS. This retrospective study included 56 patients (49 women, seven men; mean age, 37 ± 13 [SD] years) with histologically confirmed HCA evaluated by gadoxetate disodium-enhanced MRI from January 2010 to January 2021. Subtypes were reclassified using 2017 criteria: hepatocyte nuclear factor-1α mutated HCA (HHCA), inflammatory HCA (IHCA), ß-catenin exon 3 activated HCA (ß-HCA), mixed inflammatory and ß-HCA (ß-IHCA), sonic hedgehog HCA (shHCA), and unclassified HCA (UHCA). Qualitative MRI features were assessed. Liver-to-lesion contrast enhancement ratios (LLCERs) were measured. Subtypes were compared, and a diagnostic algorithm was proposed. RESULTS. The analysis included 65 HCAs: 16 HHCAs, 31 IHCAs, six ß-HCA, four ß-IHCA, five shHCA, and three UHCAs. HHCAs showed homogeneous diffuse intralesional steatosis in 94%, whereas all other HCAs showed this finding in 0% (p < .001). IHCAs showed the "atoll" sign in 58%, whereas all other HCAs showed this finding in 12% (p < .001). IHCAs showed moderate T2 hyperintensity in 52%, whereas all other HCAs showed this finding in 12% (p < .001). The ß-HCAs and ß-IHCAs occurred in men in 63%, whereas all other HCAs occurred in men in 4% (p < .001). The ß-HCAs and ß-IHCAs had a mean size of 10.1 ± 6.8 cm, whereas all other HCAs had a mean size of 5.1 ± 2.9 cm (p = .03). The ß-HCAs and ß-IHCAs showed fluid components in 60%, whereas all other HCAs showed this finding in 5% (p < .001). Hepatobiliary phase iso- or hyperintensity was observed in 80% of ß-HCAs and ß-IHCAs versus 5% of all other HCAs (p < .001). Hepatobiliary phase LLCER was positive in nine HCAs (eight ß-HCAs and ß-IHCAs; one IHCA). The shHCA and UHCA did not show distinguishing features. The proposed diagnostic algorithm had accuracy of 98% for HHCAs, 83% for IHCAs, and 95% for ß-HCAs or ß-IHCAs. CONCLUSION. Findings on gadoxetate disodium-enhanced MRI, including hepatobiliary phase characteristics, were associated with HCA subtypes using the 2017 classification. CLINICAL IMPACT. The algorithm identified common HCA subtypes with high accuracy, including those with ß-catenin exon 3 mutations.

Hepatocellular Adenomas: Molecular Basis and Multimodality Imaging Update.

Hepatocellular adenomas (HCAs) are a family of liver tumors that are associated with variable prognoses. Since the initial description of these tumors, the classification of HCAs has expanded and now includes eight distinct genotypic subtypes based on molecular analysis findings. These genotypic subtypes have unique derangements in their cellular biologic makeup that determine their clinical course and may allow noninvasive identification of certain subtypes. Multiphasic MRI performed with hepatobiliary contrast agents remains the best method to noninvasively detect, characterize, and monitor HCAs. HCAs are generally hypointense during the hepatobiliary phase; the ß-catenin-mutated exon 3 subtype and up to a third of inflammatory HCAs are the exception to this characterization. It is important to understand the appearances of HCAs beyond their depictions at MRI, as these tumors are typically identified with other imaging modalities first. The two most feared related complications are bleeding and malignant transformation to hepatocellular carcinoma, although the risk of these complications depends on tumor size, subtype, and clinical factors. Elective surgical resection is recommended for HCAs that are persistently larger than 5 cm, adenomas of any size in men, and all ß-catenin-mutated exon 3 HCAs. Thermal ablation and transarterial embolization are potential alternatives to surgical resection. In the acute setting of a ruptured HCA, patients typically undergo transarterial embolization with or without delayed surgical resection. This update on HCAs includes a review of radiologic-pathologic correlations by subtype and imaging modality, related complications, and management recommendations. © RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

Translating AI to Clinical Practice: Overcoming Data Shift with Explainability.

To translate artificial intelligence (AI) algorithms into clinical practice requires generalizability of models to real-world data. One of the main obstacles to generalizability is data shift, a data distribution mismatch between model training and real environments. Explainable AI techniques offer tools to detect and mitigate the data shift problem and develop reliable AI for clinical practice. Most medical AI is trained with datasets gathered from limited environments, such as restricted disease populations and center-dependent acquisition conditions. The data shift that commonly exists in the limited training set often causes a significant performance decrease in the deployment environment. To develop a medical application, it is important to detect potential data shift and its impact on clinical translation. During AI training stages, from premodel analysis to in-model and post hoc explanations, explainability can play a key role in detecting model susceptibility to data shift, which is otherwise hidden because the test data have the same biased distribution as the training data. Performance-based model assessments cannot effectively distinguish the model overfitting to training data bias without enriched test sets from external environments. In the absence of such external data, explainability techniques can aid in translating AI to clinical practice as a tool to detect and mitigate potential failures due to data shift. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

MRI-guided focused ultrasound focal therapy for patients with intermediate-risk prostate cancer: a phase 2b, multicentre study.

BACKGROUND: Men with grade group 2 or 3 prostate cancer are often considered ineligible for active surveillance; some patients with grade group 2 prostate cancer who are managed with active surveillance will have early disease progression requiring radical therapy. This study aimed to investigate whether MRI-guided focused ultrasound focal therapy can safely reduce treatment burden for patients with localised grade group 2 or 3 intermediate-risk prostate cancer. METHODS: In this single-arm, multicentre, phase 2b study conducted at eight health-care centres in the USA, we recruited men aged 50 years and older with unilateral, MRI-visible, primary, intermediate-risk, previously untreated prostate adenocarcinoma (prostate-specific antigen ≤20 ng/mL, grade group 2 or 3; tumour classification ≤T2) confirmed on combined biopsy (combining MRI-targeted and systematic biopsies). MRI-guided focused ultrasound energy, sequentially titrated to temperatures sufficient for tissue ablation (about 60-70°C), was delivered to the index lesion and a planned margin of 5 mm or more of normal tissue, using real-time magnetic resonance thermometry for intraoperative monitoring. Co-primary outcomes were oncological outcomes (absence of grade group 2 and higher cancer in the treated area at 6-month and 24-month combined biopsy; when 24-month biopsy data were not available and grade group 2 or higher cancer had occurred in the treated area at 6 months, the 6-month biopsy results were included in the final analysis) and safety (adverse events up to 24 months) in all patients enrolled in the study. This study is registered with ClinicalTrials.gov, NCT01657942, and is no longer recruiting. FINDINGS: Between May 4, 2017, and Dec 21, 2018, we assessed 194 patients for eligibility and treated 101 patients with MRI-guided focused ultrasound. Median age was 63 years (IQR 58-67) and median concentration of prostate-specific antigen was 5·7 ng/mL (IQR 4·2-7·5). Most cancers were grade group 2 (79 [78%] of 101). At 24 months, 78 (88% [95% CI 79-94]) of 89 men had no evidence of grade group 2 or higher prostate cancer in the treated area. No grade 4 or grade 5 treatment-related adverse events were reported, and only one grade 3 adverse event (urinary tract infection) was reported. There were no treatment-related deaths. INTERPRETATION: 24-month biopsy outcomes show that MRI-guided focused ultrasound focal therapy is safe and effectively treats grade group 2 or 3 prostate cancer. These results support focal therapy for select patients and its use in comparative trials to determine if a tissue-preserving approach is effective in delaying or eliminating the need for radical whole-gland treatment in the long term. FUNDING: Insightec and the National Cancer Institute.

Integrative Machine Learning Prediction of Prostate Biopsy Results From Negative Multiparametric MRI.

BACKGROUND: Multiparametric MRI (mpMRI) is commonly recommended as a triage test prior to any prostate biopsy. However, there exists limited consensus on which patients with a negative prostate mpMRI could avoid prostate biopsy. PURPOSE: To identify which patient could safely avoid prostate biopsy when the prostate mpMRI is negative, via a radiomics-based machine learning approach. STUDY TYPE: Retrospective. SUBJECTS: Three hundred thirty patients with negative prostate 3T mpMRI between January 2016 and December 2018 were included. FIELD STRENGTH/SEQUENCE: A 3.0 T/T2-weighted turbo spin echo (TSE) imaging (T2 WI) and diffusion-weighted imaging (DWI). ASSESSMENT: The integrative machine learning (iML) model was trained to predict negative prostate biopsy results, utilizing both radiomics and clinical features. The final study cohort comprised 330 consecutive patients with negative mpMRI (PI-RADS < 3) who underwent systematic transrectal ultrasound-guided (TRUS) or MR-ultrasound fusion (MRUS) biopsy within 6 months. A secondary analysis of biopsy naïve subcohort (n = 227) was also conducted. STATISTICAL TESTS: The Mann-Whitney U test and Chi-Squared test were utilized to evaluate the significance of difference of clinical features between prostate biopsy positive and negative groups. The model performance was validated using leave-one-out cross-validation (LOOCV) and measured by AUC, sensitivity, specificity, and negative predictive value (NPV). RESULTS: Overall, 306/330 (NPV 92.7%) of the final study cohort patients had negative biopsies, and 207/227 (NPV 91.2%) of the biopsy naïve subcohort patients had negative biopsies. Our iML model achieved NPVs of 98.3% and 98.0% for the study cohort and subcohort, respectively, superior to prostate-specific antigen density (PSAD)-based risk assessment with NPVs of 94.9% and 93.9%, respectively. DATA CONCLUSION: The proposed iML model achieved high performance in predicting negative prostate biopsy results for patients with negative mpMRI. With improved NPVs, the proposed model can be used to stratify patients who in whom we might obviate biopsies, thus reducing the number of unnecessary biopsies. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

CT-monitored minimal ablative margin control in single-session microwave ablation of liver tumors: an effective strategy for local tumor control.

OBJECTIVES: To investigate the usefulness of minimal ablative margin (MAM) control by intra-procedural contrast-enhanced CT (CECT) in microwave ablation (MWA) of liver tumors. METHODS: A total of 334 consecutive liver tumors (240 hepatocellular carcinomas [HCCs] and 94 colorectal liver metastases [CRLMs]) in 172 patients treated with percutaneous MWA were retrospectively included. MAM of each tumor was assessed after expected ablation completion using intra-procedural CECT, allowing within-session additional ablation to any potentially insufficient margin. On immediate post-MWA MRI, complete ablation coverage of tumor and final MAM status were determined. The cumulative local tumor progression (LTP) rate was estimated by using the Kaplan-Meier method. To identify predictors of LTP, Cox regression analysis with a shared frailty model was performed. RESULTS: Intra-procedural CECT findings prompted additional ablation in 18.9% (63/334) of tumors. Final complete ablation coverage of tumor and sufficient MAM were determined by MRI to be achieved in 99.4% (332/334) and 77.5% (259/334), and their estimated 6-month, 1-year, and 2-year LTP rates were 3.2%, 7.5%, and 12.9%; and 1.0%, 2.1%, and 6.9%, respectively. Insufficient MAM on post-MWA MRI, perivascular tumor location, and tumor size (cm) were independent risk factors for LTP (hazard ratio = 14.4, 6.0, and 1.1, p < 0.001, p = 0.003, and p = 0.011, respectively), while subcapsular location and histology (HCC vs CRLM) were not. CONCLUSIONS: In MWA of liver tumors, intra-procedural CECT monitoring of minimal ablative margin facilitates identification of potentially suboptimal margins and guides immediate additional intra-session ablation to maximize rates of margin-sufficient ablations, the latter being a highly predictive marker for excellent long-term local tumor control. KEY POINTS: • In MWA of liver tumors, intra-procedural CECT can identify potentially suboptimal minimal ablative margin, leading to immediate additional ablation in a single treatment session. • Achieving a finally sufficient ablative margin through the MWA with intra-procedural CECT monitoring of minimal ablative margin results in excellent local tumor control.

Multiparametric MRI-based radiomics model to predict pelvic lymph node invasion for patients with prostate cancer.

OBJECTIVE: To identify which patient with prostate cancer (PCa) could safely avoid extended pelvic lymph node dissection (ePLND) by predicting lymph node invasion (LNI), via a radiomics-based machine learning approach. METHODS: An integrative radiomics model (IRM) was proposed to predict LNI, confirmed by the histopathologic examination, integrating radiomics features, extracted from prostatic index lesion regions on MRI images, and clinical features via SVM. The study cohort comprised 244 PCa patients with MRI and followed by radical prostatectomy (RP) and ePLND within 6 months between 2010 and 2019. The proposed IRM was trained in training/validation set and evaluated in an internal independent testing set. The model's performance was measured by area under the curve (AUC), sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). AUCs were compared via Delong test with 95% confidence interval (CI), and the rest measurements were compared via chi-squared test or Fisher's exact test. RESULTS: Overall, 17 (10.6%) and 14 (16.7%) patients with LNI were included in training/validation set and testing set, respectively. Shape and first-order radiomics features showed usefulness in building the IRM. The proposed IRM achieved an AUC of 0.915 (95% CI: 0.846-0.984) in the testing set, superior to pre-existing nomograms whose AUCs were from 0.698 to 0.724 (p < 0.05). CONCLUSION: The proposed IRM could be potentially feasible to predict the risk of having LNI for patients with PCa. With the improved predictability, it could be utilized to assess which patients with PCa could safely avoid ePLND, thus reduce the number of unnecessary ePLND. KEY POINTS: • The combination of MRI-based radiomics features with clinical information improved the prediction of lymph node invasion, compared with the model using only radiomics features or clinical features. • With improved prediction performance on predicting lymph node invasion, the number of extended pelvic lymph node dissection (ePLND) could be reduced by the proposed integrative radiomics model (IRM), compared with the existing nomograms.

Perioperative Skeletal Muscle Fluctuations in High-Acuity Liver Transplantation.

BACKGROUND: Frailty has been implicated as a negative predictor of Liver Transplant (LT) outcomes. However, an understanding of changes in patient muscle mass peri-LT, and their effect in high-acuity patients remains lacking. We examined the impact of perioperative muscle mass changes (ΔSMI) on high-acuity (MELD ≥35) LT recipients. MATERIALS AND METHODS: Skeletal muscle index (SMI) was calculated using CT imaging. Patients were divided into two groups, based on severity of peri-operative SMI decrease. LT recipients with chronic end-stage liver disease, MELD ≥35, and abdominal CT ≤30 days prior, and 30-90 days post LT were included. [1011 adult LT recipients reviewed, 2012-2018]. RESULTS: Of 1011 patients reviewed, 88 met inclusion criteria (median MELD 41.1). The median ΔSMI was -5.0 (-29.4 - +21.1 cm2/m2) (fig A). Patients were classified into two groups: ΔSMI<-5.0 (median ΔSMI: -0.4, n = 44) and ΔSMI>-5.0 (median ΔSMI: -9.2, n = 44). Recipients with ΔSMI<-5.0 had higher pre-LT SMI (35.4 versus 31.2 cm2/m2, P <0.001) and lower post-LT SMI (26.0 versus 30.8 cm2/m2, P <0.001). The ΔSMI<-5.0 group had higher early allograft dysfunction (40.9 versus 20.5%, P = 0.037), and inferior patient and graft survival (P = 0.015, 0.017, respectively). Multivariate analysis identified ΔSMI<-5.0 (HR: 2.938, P = 0.048), long cold-ischemia time (≥9h, HR: 7.332, P = 0.008), HCV (HR: 5.614, p = 0.001), and tracheostomy after LT (HR:9.218, P <0.001) as negative prognostic factors for patient survival . CONCLUSIONS: Progressive perioperative sarcopenic deterioration was associated with inferior patient and graft survival in high acuity LT. These findings may guide pre and post-operative patient care and rehabilitation efforts in this challenging patient population.

Sarcopenia in high acuity liver transplantation: Does it predict outcomes?

BACKGROUND: Sarcopenia has gained momentum as a potential risk-stratification tool in liver transplantation (LT). While LT recipients recently have more advanced end-stage liver disease, the impact of sarcopenia in high acuity recipients with a high model for end-stage liver disease (MELD) score remains unclear. METHODS: We retrospectively assessed sarcopenia by calculating skeletal muscle index (SMI) from cross-sectional area at third lumbar vertebra (cm2 ) and height (m2 ) in 296 patients with a CT ≤ 30 days prior to LT. Sex-specific SMI cut-offs were developed, and its impact was assessed in patients with MELD ≥ 35. RESULTS: In patients with MELD ≥ 35 (n = 217), men with a SMI < 30 cm2 /m2 had significantly higher rates of bacteremia (P = .021) and a longer hospital stay (P < .001). Women with a SMI < 34 cm2 /m2 had a longer hospital stay (P = .032). There were no relationships between SMI and survival in men and women with MELD ≥ 35. CONCLUSIONS: This series examined sarcopenia with a focus on high MELD patients. Although decreased SMI contributed to higher post-LT hospital stay, it did not impact patient survival, suggesting that while SMI alone may not aid in patient selection for LT, it certainly may guide perioperative care-planning in this challenging patient population.

Dictionary learning compressed sensing reconstruction: pilot validation of accelerated echo planar J-resolved spectroscopic imaging in prostate cancer.

OBJECTIVES: This study aimed at developing dictionary learning (DL) based compressed sensing (CS) reconstruction for randomly undersampled five-dimensional (5D) MR Spectroscopic Imaging (3D spatial + 2D spectral) data acquired in prostate cancer patients and healthy controls, and test its feasibility at 8x and 12x undersampling factors. MATERIALS AND METHODS: Prospectively undersampled 5D echo-planar J-resolved spectroscopic imaging (EP-JRESI) data were acquired in nine prostate cancer (PCa) patients and three healthy males. The 5D EP-JRESI data were reconstructed using DL and compared with gradient sparsity-based Total Variation (TV) and Perona-Malik (PM) methods. A hybrid reconstruction technique, Dictionary Learning-Total Variation (DLTV), was also designed to further improve the quality of reconstructed spectra. RESULTS: The CS reconstruction of prospectively undersampled (8x and 12x) 5D EP-JRESI data acquired in prostate cancer and healthy subjects were performed using DL, DLTV, TV and PM. It is evident that the hybrid DLTV method can unambiguously resolve 2D J-resolved peaks including myo-inositol, citrate, creatine, spermine and choline. CONCLUSION: Improved reconstruction of the accelerated 5D EP-JRESI data was observed using the hybrid DLTV. Accelerated acquisition of in vivo 5D data with as low as 8.33% samples (12x) corresponds to a total scan time of 14 min as opposed to a fully sampled scan that needs a total duration of 2.4 h (TR = 1.2 s, 32 [Formula: see text]×16 [Formula: see text]×8 [Formula: see text], 512 [Formula: see text] and 64 [Formula: see text]).

Predicting Pathological Tumor Size in Prostate Cancer Based on Multiparametric Prostate Magnetic Resonance Imaging and Preoperative Findings.

PURPOSE: Oncologic efficacy of focal therapies in prostate cancer depends heavily on accurate tumor size estimation. We aim to evaluate the agreement between radiologic tumor size and pathological tumor size, and identify predictors of pathological tumor size. MATERIALS AND METHODS: This single arm study cohort included all consecutive patients with biopsy proven prostate cancer and a corresponding PI-RADS®v2 3 or greater index tumor on multiparametric magnetic resonance imaging who subsequently underwent radical prostatectomy. Radiologic tumor size was defined as maximum tumor diameter on multiparametric magnetic resonance imaging and compared to whole mount histopathology tumor correlates. The difference between radiologic tumor size and pathological tumor size was assessed, and clinical, pathological and radiographic predictors of pathological tumor size were examined. RESULTS: A total of 461 consecutive lesions in 441 men were included for statistical analysis. Mean radiologic tumor size and pathological tumor size was 1.57 and 2.37 cm, respectively (p <0.001). Radiologic tumor size consistently underestimated pathological tumor size regardless of the preoperative covariates, and the degree of underestimation increased with smaller radiologic tumor size and lower PI-RADSv2 scores. Pathological tumor size was significantly larger for biopsy Gleason Grade Group (GG) 5 compared to GG1 (mean change 0.37 cm, p=0.014), PI-RADSv2 5 lesions compared to PI-RADSv2 4 (mean change 0.26, p=0.006) and higher prostate specific antigen density. The correlations between radiologic tumor size vs pathological tumor size according to biopsy GG and radiologic covariates were generally low with correlation coefficients ranging between 0.1 and 0.65. CONCLUSIONS: Multiparametric magnetic resonance imaging frequently underestimates pathological tumor size and the degree of underestimation increases with smaller radiologic tumor size and lower PI-RADSv2 scores. Therefore, a larger ablation margin may be required for smaller tumors and lesions with lower PI-RADSv2 scores. These variables must be considered when estimating treatment margins in focal therapy.