First experience of evaluation of the impact of high-matrix size reconstruction in image quality in arterial CT runoff studies of the lower extremities.

OBJECTIVES: To determine whether image reconstruction with a higher matrix size improves image quality for lower extremity CTA studies. METHODS: Raw data from 50 consecutive lower extremity CTA studies acquired on two MDCT scanners (SOMATOM Flash, Force) in patients evaluated for peripheral arterial disease (PAD) were retrospectively collected and reconstructed with standard (512 × 512) and higher resolution (768 × 768, 1024 × 1024) matrix sizes. Five blinded readers reviewed representative transverse images in randomized order (150 total). Readers graded image quality (0 (worst)-100 (best)) for vascular wall definition, image noise, and confidence in stenosis grading. Ten patients' stenosis scores on CTA images were compared to invasive angiography. Scores were compared using mixed effects linear regression. RESULTS: Reconstructions with 1024 × 1024 matrix were ranked significantly better for wall definition (mean score 72, 95% CI = 61-84), noise (74, CI = 59-88), and confidence (70, CI = 59-80) compared to 512 × 512 (wall = 65, CI = 53 × 77; noise = 67, CI = 52 × 81; confidence = 62, CI = 52 × 73; p = 0.003, p = 0.01, and p = 0.004, respectively). Compared to 512 × 512, the 768 × 768 and 1024 × 1024 matrix improved image quality in the tibial arteries (wall = 51 vs 57 and 59, p < 0.05; noise = 65 vs 69 and 68, p = 0.06; confidence = 48 vs 57 and 55, p < 0.05) to a greater degree than the femoral-popliteal arteries (wall = 78 vs 78 and 85; noise = 81 vs 81 and 84; confidence = 76 vs 77 and 81, all p > 0.05), though for the 10 patients with angiography accuracy of stenosis grading was not significantly different. Inter-reader agreement was moderate (rho = 0.5). CONCLUSION: Higher matrix reconstructions of 768 × 768 and 1024 × 1024 improved image quality and may enable more confident assessment of PAD. CLINICAL RELEVANCE STATEMENT: Higher matrix reconstructions of the vessels in the lower extremities can improve perceived image quality and reader confidence in making diagnostic decisions based on CTA imaging. KEY POINTS: • Higher than standard matrix sizes improve perceived image quality of the arteries in the lower extremities. • Image noise is not perceived as increased even at a matrix size of 1024 × 1024 pixels. • Gains from higher matrix reconstructions are higher in smaller, more distal tibial and peroneal vessels than in femoropopliteal vessels.

Coronary Volume to Left Ventricular Mass Ratio in Patients With Hypertension.

The coronary vascular volume to left ventricular mass (V/M) ratio assessed by coronary computed tomography angiography (CCTA) is a promising new parameter to investigate the relation of coronary vasculature to the myocardium supplied. It is hypothesized that hypertension decreases the ratio between coronary volume and myocardial mass by way of myocardial hypertrophy, which could explain the detected abnormal myocardial perfusion reserve reported in patients with hypertension. Individuals enrolled in the multicenter ADVANCE (Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care) registry who underwent clinically indicated CCTA for analysis of suspected coronary artery disease with known hypertension status were included in current analysis. The V/M ratio was calculated from CCTA by segmenting the coronary artery luminal volume and left ventricular myocardial mass. In total, 2,378 subjects were included in this study, of whom 1,346 (56%) had hypertension. Left ventricular myocardial mass and coronary volume were higher in subjects with hypertension than normotensive patients (122.7 ± 32.8 g vs 120.0 ± 30.5 g, p = 0.039, and 3,105.0 ± 992.0 mm3 vs 2,965.6 ± 943.7 mm3, p <0.001, respectively). Subsequently, the V/M ratio was higher in patients with hypertension than those without (26.0 ± 7.6 mm3/g vs 25.3 ± 7.3 mm3/g, p = 0.024). After correcting for potential confounding factors, the coronary volume and ventricular mass remained higher in patients with hypertension (least square) mean difference estimate: 196.3 (95% confidence intervals [CI] 119.9 to 272.7) mm3, p <0.001, and 5.60 (95% CI 3.42 to 7.78) g, p <0.001, respectively), but the V/M ratio was not significantly different (least square mean difference estimate: 0.48 (95% CI -0.12 to 1.08) mm3/g, p = 0.116). In conclusion, our findings do not support the hypothesis that the abnormal perfusion reserve would be caused by reduced V/M ratio in patients with hypertension.

The effects of ambient lighting in chest radiology reading rooms.

Under typical dark chest radiography reading room conditions, a radiologist's pupils contract and dilate as their visual focus intermittently shifts between the high luminance monitor and the darker background wall, resulting in increased visual fatigue and degradation of diagnostic performance. A controlled increase of ambient lighting may minimize these visual adjustments and potentially improve comfort and accuracy. This study was designed to determine the effect of a controlled increase of ambient lighting on chest radiologist nodule detection performance. Four chest radiologists read 100 radiographs (50 normal and 50 containing a subtle nodule) under low (E=1 lx) and elevated (E=50 lx) ambient lighting levels on a DICOM-calibrated, medical-grade liquid crystal display. Radiologists were asked to identify nodule locations and rate their detection confidence. A receiver operating characteristic (ROC) analysis of radiologist results was performed and area under ROC curve (AUC) values calculated for each ambient lighting level. Additionally, radiologist selection times under both illuminance conditions were determined. Average AUC values did not significantly differ (p>0.05) between ambient lighting levels (estimated mean difference=-0.03; 95% CI, (-0.08, 0.03)). Average selection times decreased or remained constant with increased illuminance. The most considerable decreases occurred for false positive identification times (35.4±18.8 to 26.2±14.9 s) and true positive identification times (29.7±18.3 to 24.5±15.5 s). No performance differences were statistically significant. Study findings suggest that a controlled increase of ambient lighting within darkly lit chest radiology reading rooms, to a level more suitable for performance of common radiological tasks, does not appear to have a statistically significant effect on nodule detection performance.

Validation of lesion simulations in clinical CT data for anonymized chest and abdominal CT databases.

PURPOSE: To make available to the medical imaging community a computed tomography (CT) image database composed of hybrid datasets (patient CT images with digitally inserted anthropomorphic lesions) where lesion ground truth is known a priori. It is envisioned that such a dataset could be a resource for the assessment of CT image quality, machine learning, and imaging technologies [e.g., computer aided detection (CAD) and segmentation algorithms]. ACQUISITION AND VALIDATION METHODS: This HIPPA compliant, IRB waiver of approval study consisted of utilizing 120 chest and 100 abdominal clinically acquired adult CT exams. One image series per patient exam was utilized based on coverage of the anatomical region of interest (either the thorax or abdomen). All image series were de-identified. Simulated lesions were derived from a library of anatomically informed digital lesions (93 lung and 50 liver lesions) where six and four digital lesions with nominal diameters ranging from 4 to 20 mm were inserted into lung and liver image series, respectively. Locations for lesion insertion were randomly chosen. A previously validated lesion simulation and virtual insertion technique were utilized. The resulting hybrid images were reviewed by three experienced radiologists to assure similarity with routine clinical imaging in a diverse adult population. DATA FORMAT AND USAGE NOTES: The database is composed of four datasets that contain 100 patient cases each, for a total of 400 image series accompanied by Matlab.mat tables that provide descriptive information about the virtually inserted lesions (i.e., size, shape, opacity, and insertion location in physical (world) coordinates and voxel indices). All image and metadata are stored in DICOM format on the Quantitative Imaging Data Warehouse (https://qidw.rsna.org/#collection/57d463471cac0a4ec8ff8f46/folder/5b23dceb1cac0a4ec800a770?dialog=login), in two sets: (a) QIBA CT Hybrid Dataset I which contains Lung I and Liver I datasets, and (b) QIBA CT Hybrid Dataset II which contains Lung II and Liver II datasets. The QIDW is supported by the Radiological Society of North America (RSNA). Registration is required upon initial log in. POTENTIAL APPLICATIONS: By simulating lesion opacity (full solid, part solid and ground glass), size, and texture, the relationship between lesion morphology and segmentation or CAD algorithm performance can be investigated without the need for repetitive patient exams. This database can also serve as a reference standard for device and reader performance studies.