Baseline CT-based Radiomic Features Aid Prediction of Nodal Positivity after Neoadjuvant Therapy in Pancreatic Cancer.

Purpose To study the association between CT-derived textural features of pancreatic cancer and patient outcome. Materials and Methods This retrospective study evaluated 54 patients (median age, 62 years [range, 40-88 years]; 32 men) with pancreatic cancer who underwent chemoradiation followed by surgical resection and lymph node dissection from May 2012 to June 2016. Three-dimensional segmentation of the pancreatic tumor was performed on baseline dual-energy CT images: 70-keV pancreatic parenchymal phase (PPP) images and iodine material density images. Then, 15 and 19 radiomic features were extracted from each phase, respectively. Logistic regression with elastic net regularization was used to select textural features associated with outcome, and receiver operating characteristic analysis evaluated feature performance. Survival curves were generated using the Kaplan-Meier method. Results The feature of integral total (∫ T), representing the mean intensity in Hounsfield units times the contour volume in milliliters of PPP imaging (hereafter, "∫ T (HU·mL) (PPP)"), is inversely associated with posttherapy pathologic lymph node (ypN) category. A threshold ∫ T (HU·mL) (PPP) less than 507.85 predicted ypN1-2 classification with 96% sensitivity, 34% specificity, and area under the curve of 0.61. Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased overall survival (median, 2.8 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (one event at 3.4 years) (P = .006). Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased progression-free survival (median, 1.5 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (median, 2.7 years) (P = .001). Conclusion A CT-based radiomic signature may help predict ypN category in patients with pancreatic cancer. Keywords: CT-Dual Energy, Abdomen/GI, Pancreas, Tumor Response, Outcomes Analysis © RSNA, 2022 Supplemental material is available for this article.

Quantification of Human Central Adipose Tissue Depots: An Anatomically Matched Comparison Between DXA and MRI.

Excess visceral adipose tissue (VAT) and VAT volume relative to subcutaneous adipose tissue (SAT) are associated with elevated health risks. This study compares fat measurements by dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI). In total, 21 control subjects (Control) and 16 individuals with metabolic syndrome (MetSyn) were scanned by DXA and MRI. The region measured by MRI was matched to the android region defined by DXA, and MRI reproducibility was also evaluated. In addition, liver fat fraction was quantified via MRI and whole-body fat by DXA. VAT measurements are interchangeable between DXA and MRI in the Control (R = 0.946), MetSyn (R = 0.968), and combined cohort (R = 0.983). VAT/SAT ratio did not differ in the Control group (P = .10), but VAT/SAT ratio measured by DXA was significantly higher in the MetSyn group (P < .01) and the combined (P = .03) cohort. Intraobserver (ICC = 0.998) and interobserver (ICC = 0.977) reproducibility of MRI VAT measurements was excellent. Liver fat fraction by MRI was higher (P = .001) in MetSyn (12.4% ± 7.6%) than in controls (2.6% ± 2.2%), as was whole-body fat percentage by DXA (P = .001) between the MetSyn (42.0% ± 8.1%) and Control groups (26.7% ± 6.9%). DXA and MRI VAT are interchangeable when measured over an anatomically matched region of the abdomen, while SAT and VAT/SAT ratio differ between the 2 modalities.

Free-breathing myocardial T2* mapping using GRE-EPI and automatic non-rigid motion correction.

BACKGROUND: Measurement of myocardial T2* is becoming widely used in the assessment of patients at risk for cardiac iron overload. The conventional breath-hold, ECG-triggered, segmented, multi-echo gradient echo (MGRE) sequence used for myocardial T2* quantification is very sensitive to respiratory motion and may not be feasible in patients who are unable to breath-hold. We propose a free-breathing myocardial T2* mapping approach that combines a single-shot gradient-echo echo-planar imaging (GRE-EPI) sequence for T2*-weighted image acquisition with automatic non-rigid motion correction (MOCO) of respiratory motion between single-shot images. METHODS: ECG-triggered T2*-weighted images at different echo times were acquired by a black-blood, single-shot GRE-EPI sequence during free-breathing. A single image at a single TE is acquired in each heartbeat. Automatic non-rigid MOCO was applied to correct for in-plane respiratory motion before pixel-wise T2* mapping. In a total of 117 patients referred for clinical cardiac magnetic resonance exams, the free-breathing MOCO GRE-EPI sequence was compared to the breath-hold segmented MGRE approach. Image quality was scored independently by 2 experienced observers blinded to the particular image acquisition strategy. T2* measurements in the interventricular septum and in the liver were compared for the two methods in all cases with adequate image quality. RESULTS: T2* maps were acquired in all 117 patients using the breath-hold MGRE and the free-breathing MOCO GRE-EPI approaches, including 8 patients with myocardial iron overload and 25 patients with hepatic iron overload. The mean image quality of the free-breathing MOCO GRE-EPI images was scored significantly higher than that of the breath-hold MGRE images by both reviewers. Out of the 117 studies, 21 breath-hold MGRE studies (17.9% of all the patients) were scored to be less than adequate or very poor by both reviewers, while only 2 free-breathing MOCO GRE-EPI studies were scored to be less than adequate image quality. In a comparative evaluation of the images with at least adequate quality, the intra-class correlation coefficients for myocardial and liver T2* were 0.868 and 0.986 respectively (p < 0.001), indicating that the T2* measured by breath-hold MGRE and free-breathing MOCO GRE-EPI were in close agreement. The coefficient of variation between the breath-hold and free-breathing approaches for myocardial and liver T2* were 9.88% and 9.38% respectively. Bland-Altman plots demonstrated good absolute agreement of T2* in the interventricular septum and the liver from the free-breathing and breath-hold approaches (mean differences -0.03 and 0.16 ms, respectively). CONCLUSION: The free-breathing approach described for T2* mapping using MOCO GRE-EPI enables accurate myocardial and liver T2* measurements and is insensitive to respiratory motion.