Objective Task-Based Evaluation of Quantitative Medical Imaging Methods: Emerging Frameworks and Future Directions.

Quantitative imaging (QI) holds significant potential across diverse clinical applications. For clinical translation of QI, rigorous evaluation on clinically relevant tasks is essential. This article outlines 4 emerging evaluation frameworks, including virtual imaging trials, evaluation with clinical data in the absence of ground truth, evaluation for joint detection and quantification tasks, and evaluation of QI methods that output multidimensional outputs.

ISIT-GEN: An in silico imaging trial to assess the inter-scanner generalizability of CTLESS for myocardial perfusion SPECT on defect-detection task.

A recently proposed scatter-window and deep learning-based attenuation compensation (AC) method for myocardial perfusion imaging (MPI) by single-photon emission computed tomography (SPECT), namely CTLESS, demonstrated promising performance on the clinical task of myocardial perfusion defect detection with retrospective data acquired on SPECT scanners from a single vendor. For clinical translation of CTLESS, it is important to assess the generalizability of CTLESS across different SPECT scanners. For this purpose, we conducted a virtual imaging trial, titled in silico imaging trial to assess generalizability (ISIT-GEN).

Sex differences in cardiac remodelling in ischaemic cardiomyopathy and functional mitral regurgitation: impact on prognosis.

Aims: Sex differences in prognosis of functional mitral regurgitation (FMR) associated with ischaemic cardiomyopathy (ICM) demonstrate the need to identify sex differences in cardiac remodelling. This study aimed to characterize sex differences in cardiac remodelling associated with FMR in the setting of ICM, sex interactions with cardiac remodelling and FMR severity, and predictors of all-cause mortality or heart transplantation using cardiac magnetic resonance (CMR) imaging.

Methods And Results: Consecutive patients with ICM referred to CMR between 2002 and 2017 were reviewed.

CTLESS: A scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT.

Attenuation compensation (AC), while being beneficial for visual-interpretation tasks in myocardial perfusion imaging (MPI) by single-photon emission computed tomography (SPECT), typically requires the availability of a separate X-ray CT component, leading to additional radiation dose, higher costs, and potentially inaccurate diagnosis in case of misalignment between SPECT and CT images. To address these issues, we developed a method for cardiac SPECT AC using deep learning and emission scatter-window photons without a separate transmission scan (CTLESS). In this method, an estimated attenuation map reconstructed from scatter-energy window projections is segmented into different regions using a multi-channel input multi-decoder network trained on CT scans.

Reproducibility of proton density fat fraction assessment of thigh muscle in a multi-site, multi-vendor cohort study at 10 years after anterior cruciate ligament reconstruction.

Background: Dixon-based magnetic resonance imaging (MRI) intramuscular proton density fat fraction (PDFF) is a potentially useful imaging biomarker of muscle quality. However, multi-vendor, multi-site reproducibility of intramuscular PDFF quantification, required for large clinical studies, can be strongly dependent on acquisition and processing. The purpose of this study was (I) to develop a 6-point Dixon MRI-based acquisition and processing technique for reproducible multi-vendor, multi-site quantification of thigh intramuscular PDFF; and (II) to evaluate the ability of the technique to detect differences in thigh muscle status between operated .

CTLESS: A scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT.

Attenuation compensation (AC), while being beneficial for visual-interpretation tasks in myocardial perfusion imaging (MPI) by SPECT, typically requires the availability of a separate X-ray CT component, leading to additional radiation dose, higher costs, and potentially inaccurate diagnosis due to SPECT/CT misalignment. To address these issues, we developed a method for cardiac SPECT AC using deep learning and emission scatter-window photons without a separate transmission scan (CTLESS). In this method, an estimated attenuation map reconstructed from scatter-energy window projections is segmented into different regions using a multi-channel input multi-decoder network trained on CT scans.

Reproducibility and Repeatability of US Shear-Wave and Transient Elastography in Nonalcoholic Fatty Liver Disease.

Background US shear-wave elastography (SWE) and vibration-controlled transient elastography (VCTE) enable assessment of liver stiffness, an indicator of fibrosis severity. However, limited reproducibility data restrict their use in clinical trials. Purpose To estimate SWE and VCTE measurement variability in nonalcoholic fatty liver disease (NAFLD) within and across systems to support clinical trial diagnostic enrichment and clinical interpretation of longitudinal liver stiffness.

Special Report on the Consensus QIBA Profile for Objective Analytical Validation of Non-calcified and High-risk Plaque and Other Biomarkers using Computed Tomography Angiography.

Rationale And Objectives: Evidence is building in support of the clinical utility of atherosclerotic plaque imaging by computed tomography angiography (CTA). There is increasing organized activity to embrace non-calcified plaque (NCP) as a formally defined biomarker for clinical trials, and high-risk plaque (HRP) for clinical care, as the most relevant measures for the field to advance and worthy of community efforts to validate. Yet the ability to assess the quantitative performance of any given specific solution to make these measurements or classifications is not available.

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study.

Background: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS 2.

F-fluciclovine PET/CT to distinguish radiation necrosis from tumor progression for brain metastases treated with radiosurgery: results of a prospective pilot study.

Purpose: Distinguishing radiation necrosis from tumor progression among patients with brain metastases previously treated with stereotactic radiosurgery represents a common diagnostic challenge. We performed a prospective pilot study to determine whether PET/CT with F-fluciclovine, a widely available amino acid PET radiotracer, repurposed intracranially, can accurately diagnose equivocal lesions.

Methods: Adults with brain metastases previously treated with radiosurgery presenting with a follow-up tumor-protocol MRI brain equivocal for radiation necrosis versus tumor progression underwent an F-fluciclovine PET/CT of the brain within 30 days.

Test-retest repeatability of ADC in prostate using the multi b-Value VERDICT acquisition.

Purpose: VERDICT (Vascular, Extracellular, Restricted Diffusion for Cytometry in Tumours) MRI is a multi b-value, variable diffusion time DWI sequence that allows generation of ADC maps from different b-value and diffusion time combinations. The aim was to assess precision of prostate ADC measurements from varying b-value combinations using VERDICT and determine which protocol provides the most repeatable ADC.

Materials And Methods: Forty-one men (median age: 67.

Comparing the Accuracy of Diagnostic Tests When Disease Is Characterized by an Ordinal Scale.

In diagnostic medicine, the true disease status of a patient is often represented on an ordinal scale-for example, cancer stage (0, I, II, III, or IV) or coronary artery disease severity measured using the Coronary Artery Disease Reporting and Data System (CAD-RADS) scale (none, minimal, mild, moderate, severe, or occluded). With advances in quantitation of diagnostic images and in artificial intelligence (AI), both supervised and unsupervised algorithms are being developed to help physicians correctly grade disease. Most of the diagnostic accuracy literature deals with binary disease status (disease present or absent); however, tests diagnosing ordinal-scaled diseases should not be reduced to a binary status just to simplify diagnostic accuracy testing.

Imaging Service Navigators: An Approach Toward More Efficient and Effective Communications.

Purpose: Many practices have implemented support services to assist radiologists with noninterpretive tasks; however, little research has been performed to assess the overall effect of these services. The purpose of this study was to evaluate the effect of a team of imaging service navigators (ISNs) incorporated into a practice on (1) number of communications, (2) time saved by radiologists, and (3) radiologist satisfaction with the service.

Methods: The numbers and types of reports dictated by radiologists were captured for 6-month periods before and after ISN implementation.

Multiparametric Data-driven Imaging Markers: Guidelines for Development, Application and Reporting of Model Outputs in Radiomics.

This paper is the fifth in a five-part series on statistical methodology for performance assessment of multi-parametric quantitative imaging biomarkers (mpQIBs) for radiomic analysis. Radiomics is the process of extracting visually imperceptible features from radiographic medical images using data-driven algorithms. We refer to the radiomic features as data-driven imaging markers (DIMs), which are quantitative measures discovered under a data-driven framework from images beyond visual recognition but evident as patterns of disease processes irrespective of whether or not ground truth exists for the true value of the DIM.

Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation.

Combinations of multiple quantitative imaging biomarkers (QIBs) are often able to predict the likelihood of an event of interest such as death or disease recurrence more effectively than single imaging measurements can alone. The development of such multiparametric quantitative imaging and evaluation of its fitness of use differs from the analogous processes for individual QIBs in several key aspects. A computational procedure to combine the QIB values into a model output must be specified.

A Framework for Evaluating the Technical Performance of Multiparameter Quantitative Imaging Biomarkers (mp-QIBs).

Multiparameter quantitative imaging incorporates anatomical, functional, and/or behavioral biomarkers to characterize tissue, detect disease, identify phenotypes, define longitudinal change, or predict outcome. Multiple imaging parameters are sometimes considered separately but ideally are evaluated collectively. Often, they are transformed as Likert interpretations, ignoring the correlations of quantitative properties that may result in better reproducibility or outcome prediction.

Meniscal Treatment as a Predictor of Worse Articular Cartilage Damage on MRI at 2 Years After ACL Reconstruction: The MOON Nested Cohort.

Background: Patients undergoing anterior cruciate ligament reconstruction (ACLR) are at an increased risk for posttraumatic osteoarthritis (PTOA). While we have previously shown that meniscal treatment with ACLR predicts more radiographic PTOA at 2 to 3 years postoperatively, there are a limited number of similar studies that have assessed cartilage directly with magnetic resonance imaging (MRI).

Hypothesis: Meniscal repair or partial meniscectomy at the time of ACLR independently predicts more articular cartilage damage on 2- to 3-year postoperative MRI compared with a healthy meniscus or a stable untreated tear.

Statistical practice and transparent reporting in the neurosciences: Preclinical motor behavioral experiments.

Longitudinal and behavioral preclinical animal studies generate complex data, which may not be well matched to statistical approaches common in this literature. Analyses that do not adequately account for complexity may result in overly optimistic study conclusions, with consequences for reproducibility and translational decision-making. Recent work interrogating methodological shortcomings in animal research has not yet comprehensively investigated statistical shortcomings in the analysis of complex longitudinal and behavioral data.

Sex-based differences in left ventricular remodeling in patients with chronic aortic regurgitation: a multi-modality study.

Background: Significant aortic regurgitation (AR) leads to left ventricular (LV) remodeling; however, little data exist regarding sex-based differences in LV remodeling in this setting. We sought to compare LV remodeling and AR severity, assessed by echocardiography and cardiovascular magnetic resonance (CMR), to discern sex-based differences.

Methods: Patients with ≥ moderate chronic AR by echocardiography who underwent CMR within 90 days between December 2005 and October 2015 were included.

Multireader Diagnostic Accuracy Imaging Studies: Fundamentals of Design and Analysis.

The design and analysis of multireader multicase (MRMC) studies are quite challenging. These studies differ from most medical studies because they need a reference standard and sampling from two populations (ie, reader and patient populations). They are quite expensive to conduct, requiring a good deal of readers' time for image interpretation.