Faculty Bibliography

PURPOSE/OBJECTIVE:The purpose of this study was to identify differences in imaging features between patients with confirmed right middle lobe (RML) torsion compared to those suspected yet without torsion. MATERIALS AND METHODS/METHODS:This retrospective study entailing a search of radiology reports from April 1, 2014, to April 15, 2021, resulted in 52 patients with suspected yet without lobar torsion and 4 with confirmed torsion, supplemented by 2 additional cases before the search period for a total of 6 confirmed cases. Four thoracic radiologists (1 an adjudicator) evaluated chest radiographs and computed tomography (CT) examinations, and Fisher exact and Mann-Whitney tests were used to identify any significant differences in imaging features (P<0.05). RESULTS:A reversed halo sign was more frequent for all readers (P=0.001) in confirmed RML torsion than patients without torsion (83.3% vs. 0% for 3 readers, one the adjudicator). The CT coronal bronchial angle between RML bronchus and bronchus intermedius was larger (P=0.035) in torsion (121.28 degrees) than nontorsion cases (98.26 degrees). Patients with torsion had a higher percentage of ground-glass opacity in the affected lobe (P=0.031). A convex fissure towards the adjacent lobe on CT (P=0.009) and increased lobe volume on CT (P=0.001) occurred more often in confirmed torsion. CONCLUSION/CONCLUSIONS:A reversed halo sign, larger CT coronal bronchial angle, greater proportion of ground-glass opacity, fissural convexity, and larger lobe volume on CT may aid in early recognition of the rare yet highly significant diagnosis of lobar torsion.

PURPOSE/OBJECTIVE:To assess deep learning denoised (DLD) computed tomography (CT) chest images at various low doses by both quantitative and qualitative perceptual image analysis. METHODS:Simulated noise was inserted into sinogram data from 32 chest CTs acquired at 100 mAs, generating anatomically registered images at 40, 20, 10, and 5 mAs. A DLD model was developed, with 23 scans selected for training, 5 for validation, and 4 for test.Quantitative analysis of perceptual image quality was assessed with Structural SIMilarity Index (SSIM) and Fréchet Inception Distance (FID). Four thoracic radiologists graded overall diagnostic image quality, image artifact, visibility of small structures, and lesion conspicuity. Noise-simulated and denoised image series were evaluated in comparison with one another, and in comparison with standard 100 mAs acquisition at the 4 mAs levels. Statistical tests were conducted at the 2-sided 5% significance level, with multiple comparison correction. RESULTS:At the same mAs levels, SSIM and FID between noise-simulated and reconstructed DLD images indicated that images were closer to a perfect match with increasing mAs (closer to 1 for SSIM, and 0 for FID).In comparing noise-simulated and DLD images to standard-dose 100-mAs images, DLD improved SSIM and FID. Deep learning denoising improved SSIM of 40-, 20-, 10-, and 5-mAs simulations in comparison with standard-dose 100-mAs images, with change in SSIM from 0.91 to 0.94, 0.87 to 0.93, 0.67 to 0.87, and 0.54 to 0.84, respectively. Deep learning denoising improved FID of 40-, 20-, 10-, and 5-mAs simulations in comparison with standard-dose 100-mAs images, with change in FID from 20 to 13, 46 to 21, 104 to 41, and 148 to 69, respectively.Qualitative image analysis showed no significant difference in lesion conspicuity between DLD images at any mAs in comparison with 100-mAs images. Deep learning denoising images at 10 and 5 mAs were rated lower for overall diagnostic image quality (P < 0.001), and at 5 mAs lower for overall image artifact and visibility of small structures (P = 0.002), in comparison with 100 mAs. CONCLUSIONS:Deep learning denoising resulted in quantitative improvements in image quality. Qualitative assessment demonstrated DLD images at or less than 10 mAs to be rated inferior to standard-dose images.

Background We observed a high number of patients with COVID-19 pneumonia who had barotrauma related to invasive mechanical ventilation at our institution. Purpose To determine if the rate of barotrauma in patients with COVID-19 infection was greater than other patients requiring invasive mechanical ventilation at our institution. Methods In this retrospective study, clinical and imaging data of patients seen between 03/01/2020 and 04/06/2020 who tested positive for COVID-19 and experienced barotrauma associated with invasive mechanical ventilation were compared to patients without COVID-19 infection during the same period. Historical comparison was made to barotrauma rates of patients with acute respiratory distress syndrome (ARDS) from 02/01/2016 to 02/01/2020 at our institution. Comparison of patient groups was performed using categorical or continuous statistical testing as appropriate with multivariable regression analysis. Patient survival was assessed using Kaplan-Meier curves analysis. Results 601 patients with COVID-19 infection underwent invasive mechanical ventilation (63 ± 15 years, 71% men). There were 89/601 (15%) patients with one or more barotrauma events, for a total of 145 barotrauma events (24% overall events) (95% CI 21-28%). During the same period, 196 patients without COVID-19 infection (64 ± 19 years, 52% male) with invasive mechanical ventilation had 1 barotrauma event (.5% 95% CI, 0-3%, p<.001 vs. the group with COVID-19 infection). Of 285 patients with ARDS over the prior 4 years on invasive mechanical ventilation (68 ± 17 years, 60% men), 28 patients (10%) had 31 barotrauma events, with overall barotrauma rate of 11% (95% CI 8-15%, p<.001 vs. the group with COVID-19 infection). Barotrauma is an independent risk factor for death in COVID-19 (OR=2.2, p=.03), and is associated with longer hospital length of stay (OR=.92, p<.001). Conclusion Patients with COVID-19 infection and invasive mechanical ventilation had a higher rate of barotrauma than patients with ARDS and patients without COVID-19 infection.

Computed tomography pulmonary angiography (CTPA) has become the primary imaging modality for evaluating the pulmonary arteries. Although pulmonary embolism is the primary indication for CTPA, various pulmonary vascular abnormalities can be detected in adults. Knowledge of these disease entities and understanding technical pitfalls that can occur when performing CTPA are essential to enable accurate diagnosis and allow timely management. This review will cover a spectrum of acquired abnormalities including pulmonary embolism due to thrombus and foreign bodies, primary and metastatic tumor involving the pulmonary arteries, pulmonary hypertension, as well as pulmonary artery aneurysms and stenoses. Additionally, methods to overcome technical pitfalls and interventional treatment options will be addressed.

To compare utilization of CT pulmonary angiogram (CTA) for diagnosis of pulmonary embolism (PE) in an emergency department (ED) with unstructured CT ordering to published rates of CT positivity in other EDs including those employing decision support and to identify pathways for improved utilization via collaboration with our pathology and ED colleagues. Two hundred seventeen patients over a 2.5-month time period who received a CTA for PE were reviewed with exclusion of pediatric patients and all sub-optimal, non-diagnostic, or equivocal scans; 21 were excluded leaving a sample of 196 patients. The rate of PE diagnosis and association of PE positivity with selected factors (D-dimer testing) was assessed. The percentage of cases positive for PE was 10.7 % (21/196) which is similar to the frequently published rate of 10 % in other emergency departments including settings that have studied the use of decision support. D-dimer testing was performed in 40.3 % of cases. In 29.6 % (58/196) of subjects, D-dimer was positive, 10.7 % (21/196) was negative, and 59.7 % (117/196) was not assessed. Prevalence of PE among D-dimer negative (0 %, 0/21) was lower versus positive D-dimer (12.1 %, 7/58) and unknown D-dimer patients (12.0 %, 14/117). D-dimer had 100 % (21/21) negative predictive value for the diagnosis of PE. While this suggests that D-dimer is useful to rule-out PE, due to the small number of patients with PE, the 95 % confidence intervals are wide and the post-test likelihood of PE could be as high as 14 %. The rate of CT positivity for PE in an ED with unstructured CT ordering is similar to that in other published series including as series in which decision support was used. While D-dimer had high negative predictive value, large studies are needed to confirm this high sensitivity and potentially increase its use in ruling out PE without CT and to reduce CT ordering particularly in patients with sufficiently low clinical pre-test probability of PE.

OBJECTIVE: The purpose of this study was to assess the impact of an automated program on improvement in lung nodule matching efficiency. MATERIALS AND METHODS: Four thoracic radiologists independently reviewed two serial chest CT examinations from each of 57 patients. Each radiologist performed timed manual lung nodule matching. After 6 weeks, all radiologists independently repeated the timed matching portion using an automated nodule matching program. The time required for manual and automated matching was compared. The impact of nodule size and number on matching efficiency was determined. RESULTS: An average of 325 (range, 244-413) noncalcified solid pulmonary nodules was identified. Nodule matching was significantly faster with the automated program irrespective of the interpreting radiologist (p < 0.0001 for each). The maximal time saved with automated matching was 11.4 minutes (mean, 2.3 +/- 2.0 minutes). Matching was faster in 56 of 57 cases (98.2%) for three readers and in 46 of 57 cases (80.7%) for one reader. There were no differences among readers with respect to the mean time saved per matched nodule (p > 0.5). The automated program achieved 90%, 90%, 79%, and 92% accuracy for the four readers. The improvement in efficiency for a given patient using the automated technique was proportional to the number of matched nodules (p < 0.0001) and inversely proportional to nodule size (p < 0.05). CONCLUSION: Use of the automated lung nodule matching program significantly improves diagnostic efficiency. The time saved is proportionate to the number of nodules identified and inversely proportional to nodule size. Adoption of such a program should expedite CT examination interpretation and improve report turnaround time.

BACKGROUND: This study correlated isolated, blunt liver or spleen injury with the presence, location, and amount of free fluid in the pediatric blunt trauma patient. METHODS: The hospital trauma registry was reviewed for the period 1/89 to 12/99 for pediatric patients (age < or = 17 years) who sustained blunt, isolated spleen or liver injury and had an abdominal CT scan. Patients with other intraabdominal injuries or inadequate scans were excluded. CT scans were reviewed by two radiologists and the isolated liver or spleen injury confirmed and graded. The presence, location, and amount of free fluid were evaluated in the RUQ, LUQ, and pelvis. Free fluid was quantified as 0 = no fluid, 1 = small amount, 2 = moderate, and 3 = large for each area. RESULTS: There were 134 pediatric patients with an isolated spleen (n = 66) or liver (n = 68) injury. Free fluid was noted in 101 patients (75%), more commonly with spleen (82%) than with liver (69%) injuries. As injury grade increased, so did frequency of patients with free fluid (grade 1 = 50% to grade 5 = 100%) and mean total volume (sum of fluid scores from each region) of free fluid (grade 1 = 0.75 to grade 5 = 6.5). The mean total volume of free fluid was greater for splenic injury (3.1) than for liver injury (1.7). The pelvis was the most common location for free fluid (liver 53%, spleen 71%) and had the greatest mean volume of free fluid (liver 0.9, spleen 1.5) of any single region. CONCLUSION: There is a direct correlation between the severity of the isolated injury and the likelihood and volume of associated free fluid. The pelvis was the most common location to detect free fluid and had the greatest estimated fluid volume.

MR imaging has many advantages over other modalities in the detection and staging of renal neoplasms, because of its intrinsic high soft tissue contrast, direct multiplanar imaging capabilities, and the availability of a non-nephrotoxic, renally excreted contrast agent. The ongoing refinement of breath-hold imaging sequences will probably broaden the use of MR techniques in imaging renal neoplasms.