Detectability of Hypoattenuating Liver Lesions with Deep Learning CT Reconstruction: A Phantom and Patient Study.

Background CT deep learning image reconstruction (DLIR) improves image quality by reducing noise compared with adaptive statistical iterative reconstruction-V (ASIR-V). However, objective assessment of low-contrast lesion detectability is lacking. Purpose To investigate low-contrast detectability of hypoattenuating liver lesions on CT scans reconstructed with DLIR compared with CT scans reconstructed with ASIR-V in a patient and a phantom study.

Multi-reader multiparametric DECT study evaluating different strengths of iterative and deep learning-based image reconstruction techniques.

Objectives: To perform a multi-reader comparison of multiparametric dual-energy computed tomography (DECT) images reconstructed with deep-learning image reconstruction (DLIR) and standard-of-care adaptive statistical iterative reconstruction-V (ASIR-V).

Methods: This retrospective study included 100 patients undergoing portal venous phase abdominal CT on a rapid kVp switching DECT scanner. Six reconstructed DECT sets (ASIR-V and DLIR, each at three strengths) were generated.

Material density dual-energy CT images: value added in early diagnosis of peritoneal carcinomatosis : Original research.

Objective: To assess the value of material density (MD) images generated from a rapid kilovoltage-switching dual-energy CT (rsDECT) in early detection of peritoneal carcinomatosis (PC).

Materials And Methods: Thirty patients (60 ± 13 years; 24 women) with PC detected on multiple abdominal DECT scans were included. Four separate DECTs with varying findings of PC from each patient were used for qualitative/quantitative analysis, resulting in a total of 120 DECT scans (n = 30 × 4).

Does CT overestimate extra-pancreatic perineural invasion in patients with pancreatic ductal adenocarcinoma following neoadjuvant chemoradiation therapy?

Objectives: To evaluate the diagnostic performance of CT in the assessment of extra-pancreatic perineural invasion (EPNI) in patients with pancreatic ductal adenocarcinoma (PDAC).

Methods: This retrospective study included 123 patients (66 men; median age, 66 years) with PDAC who underwent radical surgery and pancreatic protocol CT for assessing surgical resectability between September 2011 and March 2019. Among the 123 patients, 97 patients had received neoadjuvant chemoradiation therapy (CRT).

Intra-patient variability of iodine quantification across different dual-energy CT platforms: assessment of normalization techniques.

Objectives: To investigate intra-patient variability of iodine concentration (IC) between three different dual-energy CT (DECT) platforms and to test different normalization approaches.

Methods: Forty-four patients who underwent portal venous phase abdominal DECT on a dual-source (dsDECT), a rapid kVp switching (rsDECT), and a dual-layer detector platform (dlDECT) during cancer follow-up were retrospectively included. IC in the liver, pancreas, and kidneys and different normalized ICs (NIC:portal vein; NIC:abdominal aorta; NIC:overall iodine load) were compared between the three DECT scanners for each patient.

Diagnostic performance and feasibility of dual-layer detector dual-energy CT for characterization of urinary stones in patients of different sizes.

Background: Urinary stones are frequently encountered in urology and are typically identified using non-contrast CT scans. Dual-energy CT (DECT) is a valuable imaging technique that produces material-specific images and allows for precise assessment of stone composition by estimating the effective atomic number (Z), a capability not achievable with the conventional single-energy CT's attenuation measurement method.

Purpose: To investigate the diagnostic performance and image quality of dual-layer detector DECT (dlDECT) in characterizing urinary stones in patients of different sizes.

Can 1.25 mm thin-section images generated with Deep Learning Image Reconstruction technique replace standard-of-care 5 mm images in abdominal CT?

Background: CT image reconstruction has evolved from filtered back projection to hybrid- and model-based iterative reconstruction. Deep learning-based image reconstruction is a relatively new technique that uses deep convolutional neural networks to improve image quality.

Objective: To evaluate and compare 1.

Abdominal Imaging Findings on Computed Tomography as a Tool for COVID-19 Mortality Risk Assessment: Comparison With Chest Radiograph Severity Scores.

Objective: To quantify the association between computed tomography abdomen and pelvis with contrast (CTAP) findings and chest radiograph (CXR) severity score, and the incremental effect of incorporating CTAP findings into predictive models of COVID-19 mortality.

Methods: This retrospective study was performed at a large quaternary care medical center. All adult patients who presented to our institution between March and June 2020 with the diagnosis of COVID-19 and had a CXR up to 48 hours before a CTAP were included.

CT image quality evaluation in the age of deep learning: trade-off between functionality and fidelity.

Objective: To quantitatively compare DLIR and ASiR-V with realistic anatomical images.

Methods: CT scans of an anthropomorphic phantom were acquired using three routine protocols (brain, chest, and abdomen) at four dose levels, with images reconstructed at five levels of ASiR-V and three levels of DLIR. Noise power spectrum (NPS) was estimated using a difference image by subtracting two matching images from repeated scans.

Prediction of R Status in Resections for Pancreatic Cancer Using Simplified Radiological Criteria.

Objective: Predicting R status before surgery for pancreatic cancer (PDAC) patients with upfront surgery and neoadjuvant therapy.

Summary Background Data: Negative surgical margins (R0) are a key predictor of long-term outcomes in PDAC.

Methods: Patients undergoing pancreatic resection with curative intent for PDAC were identified.

Concordance of EUS and MRI/MRCP findings among high-risk individuals undergoing pancreatic cancer screening.

Background/objectives: Surveillance with endoscopic ultrasonography (EUS) and MRI/magnetic retrograde cholangiopancreatography (MRCP) is recommended for individuals at high risk for pancreatic cancer. We sought to characterize the findings of these surveillance exams and define the level of concordance between these two modalities.

Methods: 173 asymptomatic high-risk individuals (HRIs) meeting criteria for pancreatic cancer surveillance underwent EUS, MRI/MRCP, or both between 2008 and 2021.

Renal Lesion Characterization by Dual-Layer Dual-Energy CT: Comparison of Virtual and True Unenhanced Images.

Prior studies have provided mixed results for the ability to replace true unenhanced (TUE) images with virtual unenhanced (VUE) images when characterizing renal lesions by dual-energy CT (DECT). Detector-based dual-layer DECT (dlDECT) systems may optimize performance of VUE images for this purpose. The purpose of this article was to compare dual-phase dlDECT examinations evaluated using VUE and TUE images in differentiating cystic and solid renal masses.

Association of body composition parameters measured on CT with risk of hospitalization in patients with Covid-19.

Purpose: To assess prognostic value of body composition parameters measured at CT to predict risk of hospitalization in patients with COVID-19 infection.

Methods: 177 patients with SARS-CoV-2 infection and with abdominopelvic CT were included in this retrospective IRB approved two-institution study. Patients were stratified based on disease severity as outpatients (no hospital admission) and patients who were hospitalized (inpatients).

Attenuation values on virtual unenhanced images obtained with detector-based dual-energy computed tomography: observations on single- and split-bolus contrast protocols.

Purpose: To compare virtual unenhanced (VUE) attenuation values and their agreement with true unenhanced (TUE) images in patients who underwent dual-layer detector-based dual-energy computed tomography (dlDECT) with single- vs. split-bolus contrast media protocol.

Methods: In this HIPAA-compliant, IRB-approved retrospective analysis, a total of 105 patients who underwent nephrographic phase (NP) dlDECT between 07/2018 and 11/2019 were included: 55 patients received single bolus and 50 patients split-bolus examinations.

Arterial involvement and resectability scoring system to predict R0 resection in patients with pancreatic ductal adenocarcinoma treated with neoadjuvant chemoradiation therapy.

Objectives: To derive a CT-based scoring system incorporating arterial involvement and resectability status to predict R0 resection in patients with pancreatic ductal adenocarcinoma (PDAC) undergoing neoadjuvant chemoradiation therapy (CRT).

Methods: This retrospective study included 112 patients with PDAC who underwent dynamic contrast-enhanced CT before and after neoadjuvant CRT. A 5-point score was used to determine arterial involvement (A score; 1 = no involvement, 2 = haziness, 3 = abutment, 4 = encasement, 5 = deformity) and 4-point score evaluating resectability status (R score; 1 = resectable, 2 = borderline resectable [BR] with venous involvement, 3 = BR with arterial involvement, 4 = locally advanced [LA]).

Virtual Unenhanced Images: Qualitative and Quantitative Comparison Between Different Dual-Energy CT Scanners in a Patient and Phantom Study.

Materials And Methods: Forty-four patients with clinical contrast-enhanced abdominal examinations on each of the 3 DECT scanner types and a phantom scanned with the same protocols were included in this retrospective study. Qualitative and quantitative assessment was performed on VUE images. Quantitative evaluation included measurement of attenuation and image noise for various tissues and the phantom.

Multi-detector computed tomography (MDCT)-based severity score as a prognostic tool in patients with suspected immune checkpoint inhibitor therapy associated colitis.

Objective: This study aimed to assess MDCT as a diagnostic and prognostic tool in patients with suspected immune checkpoint inhibitor (ICI)-related colitis.

Materials And Methods: This retrospective cohort study included patients receiving ICIs at three hospitals between 2015 and 2019 who underwent both abdominopelvic MDCT and endoscopic biopsy to workup suspected ICI-related colitis. Two radiologists independently reviewed MDCT images for signs of colitis based on pre-defined features.

The absolute tumor-capsule contact length in the diagnosis of extraprostatic extension of prostate cancer.

Background: Extraprostatic extension (EPE) of prostate cancer is associated with a poor prognosis. The broad-based capsule-tumor interface has been recognized as one of the worrisome imaging features in multiparametric prostate MRI (mpMRI). However, there was significant heterogeneity among the measurement method used in prior studies.

Diagnostic utility of CT for suspected immune checkpoint inhibitor enterocolitis.

Background And Aims: Immune checkpoint inhibitor (ICI) enterocolitis is a common immune-related adverse event and can be fatal, especially when not diagnosed and treated promptly. The current gold standard for diagnosis is endoscopy with biopsy, but CT scan is a possible alternative. The primary objective of this study is to identify the diagnostic performance of CT in the evaluation of ICI enterocolitis.