Ketogenesis protects against MASLD-MASH progression through mechanisms that extend beyond overall fat oxidation rate.

The progression of metabolic-dysfunction-associated steatotic liver disease (MASLD) to metabolic-dysfunction-associated steatohepatitis (MASH) involves complex alterations in both liver-autonomous and systemic metabolism that influence the liver's balance of fat accretion and disposal. Here, we quantify the relative contribution of hepatic oxidative pathways to liver injury in MASLD-MASH. Using NMR spectroscopy, UHPLC-MS, and GC-MS, we performed stable-isotope tracing and formal flux modeling to quantify hepatic oxidative fluxes in humans across the spectrum of MASLD-MASH, and in mouse models of impaired ketogenesis.

Improved quantitative parameter estimation for prostate T relaxometry using convolutional neural networks.

Objective: Quantitative parameter mapping conventionally relies on curve fitting techniques to estimate parameters from magnetic resonance image series. This study compares conventional curve fitting techniques to methods using neural networks (NN) for measuring T in the prostate.

Materials And Methods: Large physics-based synthetic datasets simulating T mapping acquisitions were generated for training NNs and for quantitative performance comparisons.

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.

Improved Quantitative Parameter Estimation for Prostate T2 Relaxometry using Convolutional Neural Networks.

This work seeks to evaluate multiple methods for quantitative parameter estimation from standard T mapping acquisitions in the prostate. The T estimation performance of methods based on neural networks (NN) was quantitatively compared to that of conventional curve fitting techniques. Large physics-based synthetic datasets simulating T mapping acquisitions were generated for training NNs and for quantitative performance comparisons.

Comparison of automatic liver volumetry performance using different types of magnetic resonance images.

Measurements of liver volume from MR images can be valuable for both clinical and research applications. Automated methods using convolutional neural networks have been used successfully for this using a variety of different MR image types as input. In this work, we sought to determine which types of magnetic resonance images give the best performance when used to train convolutional neural networks for liver segmentation and volumetry.

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

In diffusion-weighted MRI (DW-MRI), choice of b-value influences apparent diffusion coefficient (ADC) values by probing different aspects of the tissue microenvironment. As a secondary analysis of the multicenter ECOG-ACRIN A6698 trial, the purpose of this study was to investigate the impact of alternate b-value combinations on the performance and repeatability of tumor ADC as a predictive marker of breast cancer treatment response. The final analysis included 210 women who underwent standardized 4-b-value DW-MRI (b = 0/100/600/800 s/mm2) at multiple timepoints during neoadjuvant chemotherapy treatment and a subset (n = 71) who underwent test−retest scans.

Training Convolutional Networks for Prostate Segmentation With Limited Data.

Multi-zonal segmentation is a critical component of computer-aided diagnostic systems for detecting and staging prostate cancer. Previously, convolutional neural networks such as the U-Net have been used to produce fully automatic multi-zonal prostate segmentation on magnetic resonance images (MRIs) with performance comparable to human experts, but these often require large amounts of manually segmented training data to produce acceptable results. For institutions that have limited amounts of labeled MRI exams, it is not clear how much data is needed to train a segmentation model, and which training strategy should be used to maximize the value of the available data.

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

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response.

Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer.

In vivo magnetic resonance spectroscopy (MRS) can provide clinically valuable metabolic information from brain tumors that can be used for prognosis and monitoring response to treatment. Unfortunately, this technique has not been widely adopted in clinical practice or even clinical trials due to the difficulty in acquiring and analyzing the data. In this work we propose a computational approach to solve one of the most critical technical challenges: the problem of quickly and accurately positioning an MRS volume of interest (a voxel) inside a tumor using MR images for guidance.

Methodological consensus on clinical proton MRS of the brain: Review and recommendations.

Proton MRS ( H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor.

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

Background: Quantitative diffusion-weighted imaging (DWI) MRI is a promising technique for cancer characterization and treatment monitoring. Knowledge of the reproducibility of DWI metrics in breast tumors is necessary to apply DWI as a clinical biomarker.

Purpose: To evaluate the repeatability and reproducibility of breast tumor apparent diffusion coefficient (ADC) in a multi-institution clinical trial setting, using standardized DWI protocols and quality assurance (QA) procedures.

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

Purpose To determine if the change in tumor apparent diffusion coefficient (ADC) at diffusion-weighted (DW) MRI is predictive of pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer. Materials and Methods In this prospective multicenter study, 272 consecutive women with breast cancer were enrolled at 10 institutions (from August 2012 to January 2015) and were randomized to treatment with 12 weekly doses of paclitaxel (with or without an experimental agent), followed by 12 weeks of treatment with four cycles of anthracycline. Each woman underwent breast DW MRI before treatment, at early treatment (3 weeks), at midtreatment (12 weeks), and after treatment.

MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial.

Purpose: To estimate the accuracy of predicting response to neoadjuvant chemotherapy (NACT) in patients with locally advanced breast cancer using MR spectroscopy (MRS) measurements made very early in treatment.

Materials And Methods: This prospective Health Insurance Portability and Accountability Act (HIPAA)-compliant protocol was approved by the American College of Radiology and local-site institutional review boards. One hundred nineteen women with invasive breast cancer of ≥3 cm undergoing NACT were enrolled between September 2007 and April 2010.

Stress-induced activation of brown adipose tissue prevents obesity in conditions of low adaptive thermogenesis.

Background: Stress-associated conditions such as psychoemotional reactivity and depression have been paradoxically linked to either weight gain or weight loss. This bi-directional effect of stress is not understood at the functional level. Here we tested the hypothesis that pre-stress level of adaptive thermogenesis and brown adipose tissue (BAT) functions explain the vulnerability or resilience to stress-induced obesity.

Detection of Prostate Cancer: Quantitative Multiparametric MR Imaging Models Developed Using Registered Correlative Histopathology.

Purpose To develop multiparametric magnetic resonance (MR) imaging models to generate a quantitative, user-independent, voxel-wise composite biomarker score (CBS) for detection of prostate cancer by using coregistered correlative histopathologic results, and to compare performance of CBS-based detection with that of single quantitative MR imaging parameters. Materials and Methods Institutional review board approval and informed consent were obtained. Patients with a diagnosis of prostate cancer underwent multiparametric MR imaging before surgery for treatment.

Validation of marrow fat assessment using noninvasive imaging with histologic examination of human bone samples.

Purpose: The marrow composition throughout the body is heterogeneous and changes with age. Due to heterogeneity, invasive biopsies of the iliac crest do not truly represent the complete physiological status, impeding the clinical effectiveness of this method. Therefore, we aim to provide verification for an in vivo imaging technique using co-registered histologic examinations for assessment of marrow adiposity.

Measuring renal tissue relaxation times at 7 T.

As developments in RF coils and RF management strategies make performing ultra-high-field renal imaging feasible, understanding the relaxation times of the tissue becomes increasingly important for tissue characterization, sequence optimization and quantitative functional renal imaging, such as renal perfusion imaging using arterial spin labeling. By using a magnetization-prepared single-breath-hold fast spin echo imaging method, human renal T1 and T2 imaging studies were successfully performed at 7 T with 11 healthy volunteers (eight males, 45 ± 17 years, and three females, 29 ± 7 years, mean ± standard deviation, S.D.

Clinical proton MR spectroscopy in central nervous system disorders.

A large body of published work shows that proton (hydrogen 1 [(1)H]) magnetic resonance (MR) spectroscopy has evolved from a research tool into a clinical neuroimaging modality. Herein, the authors present a summary of brain disorders in which MR spectroscopy has an impact on patient management, together with a critical consideration of common data acquisition and processing procedures. The article documents the impact of (1)H MR spectroscopy in the clinical evaluation of disorders of the central nervous system.

Magnetic resonance spectroscopy of the breast: current status.

In vivo magnetic resonance spectroscopy (MRS) of the breast can be used to measure the level of choline-containing compounds, which is a biomarker of malignancy. In the diagnostic setting, MRS can provide high specificity for distinguishing benign from malignant lesions. MRS also can be used as an early response indicator in patients undergoing neoadjuvant chemotherapy.

Quantitative multiparametric MRI of ovarian cancer.

Purpose: To identify parameters associated with ovarian malignancy using multiparametric quantitative magnetic resonance imaging (MRI).

Materials And Methods: After Institutional Review Board (IRB) approval, women with ovarian masses underwent preoperative imaging with 3 T MRI. Dynamic contrast-enhanced (DCE)-MRI with pharmacokinetic modeling, quantitative T2 mapping, and diffusion-weighted imaging with quantitative mapping of the water diffusion parameters were performed.

Water-fat MRI for assessing changes in bone marrow composition due to radiation and chemotherapy in gynecologic cancer patients.

Purpose: To assess the feasibility of using fat-fraction imaging for measuring marrow composition changes over large regions in patients undergoing cancer therapy.

Materials And Methods: Thirteen women with gynecologic malignancies who were to receive radiation and/or chemotherapy were recruited for this study. Subjects were imaged on a 3T magnetic resonance (MR) scanner at baseline (after surgery but before radiation or chemotherapy), 6 months, and 12 months after treatment.

Quantitative mapping of total choline in healthy human breast using proton echo planar spectroscopic imaging (PEPSI) at 3 Tesla.

Purpose: To quantitatively measure tCho levels in healthy breasts using Proton-Echo-Planar-Spectroscopic-Imaging (PEPSI).

Materials And Methods: The two-dimensional mapping of tCho at 3 Tesla across an entire breast slice using PEPSI and a hybrid spectral quantification method based on LCModel fitting and integration of tCho using the fitted spectrum were developed. This method was validated in 19 healthy females and compared with single voxel spectroscopy (SVS) and with PRESS prelocalized conventional Magnetic Resonance Spectroscopic Imaging (MRSI) using identical voxel size (8 cc) and similar scan times (∼7 min).