Faculty Bibliography

This dataset, Collab-CXR, provides a unique resource to study human-AI collaboration in chest X-ray interpretation. We present experimentally generated data from 227 professional radiologists who assessed 324 historical cases under varying information conditions: with and without AI assistance, and with and without clinical history. Using a custom-designed interface, we collected probabilistic assessments for 104 thoracic pathologies using a comprehensive hierarchical reporting structure. This dataset is the largest known comparison of human-AI collaborative performance to either AI or humans alone in radiology, offering assessments across an extensive range of pathologies with rich metadata on radiologist characteristics and decision-making processes. Multiple experimental designs enable both within-subject and between-subject analyses. Researchers can leverage this dataset to investigate how radiologists incorporate AI assistance, factors influencing collaborative effectiveness, and impacts on diagnostic accuracy, speed, and confidence across different cases and pathologies. By enabling rigorous study of human-AI integration in clinical workflows, this dataset can inform AI tool development, implementation strategies, and ultimately improve patient care through optimized collaboration in medical imaging.

Background Pulmonary mold infections are common complications of prolonged severe neutropenia in patients with leukemia. Mortality from these infections is high, but early detection and treatment have been shown to be effective in reducing this mortality. In this study, we investigate the use and effectiveness of baseline and serial bimonthly high-resolution computed tomographic (HRCT) scans of the chest in the early detection of mold pneumonias. Methods  Medical records of 63 patients with acute myeloid leukemia with prolonged (7 days) and profound neutropenia (absolute neutrophil count, 500 cells/mm3) at the H. Lee Moffitt Cancer Center and Research Institute between June 2005 and January 2010 were retrospectively selected and reviewed. These patients have undergone baseline and serial HRCT imaging of the chest and were found to have new nodules suggestive of a probable mold infection and are treated accordingly. Results Radiographic improvement was noted in 51 (81.0%) patients in an average of 27.2 days (SD, 16.7), and radiographic resolution was noted in 47 (74.6%) patients in an average of 58.5 days (SD, 33.79) after treatment. There was an overall mortality rate of 25.3%.Conclusions  Our findings suggest that baseline and serial chest HRCT is assistive in the early detection and treatment of mold pneumonias. A randomized controlled trial comparing outcome and cost effectiveness of fever-driven empirical antifungal therapy versus a baseline and bimonthly HRCT-driven preemptive antifungal treatment in patients with neutropenia was conducted to confirm results.

Establishing a clinical education track as part of a radiology residency is essential in shaping future radiology educators. Many obstacles will be encountered while starting, maintaining, and improving these educational pathways. Hurdles may include recruiting suitable residents for the track, recruiting and supporting faculty advisors, sustaining long-term resident engagement, counteracting educational exclusivity, and providing adequate time and financial support. Although every program and institution may face individualized "mountains" to overcome, they are not insurmountable. The goal of this review is to address different conflicts we have encountered while maintaining the clinical education tract at our institution and to provide tips for overcoming them.

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. Primary outcomes were the severity of lung disease before CTAP and mortality within 14 and 30 days. Logistic regression models were constructed to quantify the association between CXR score and CTAP findings. Penalized logistic regression models and random forests were constructed to identify key predictors (demographics, CTAP findings, and CXR score) of mortality. The discriminatory performance of these models, with and without CTAP findings, was summarized using area under the characteristic (AUC) curves. RESULTS:One hundred ninety-five patients (median age, 63 years; 119 men) were included. The odds of having CTAP findings was 3.89 times greater when a CXR score was classified as severe compared with mild (P = 0.002). When CTAP findings were included in the feature set, the AUCs for 14-day mortality were 0.67 (penalized logistic regression) and 0.71 (random forests). Similar values for 30-day mortality were 0.76 and 0.75. When CTAP findings were omitted, all AUC values were attenuated. CONCLUSIONS:The CTAP findings were associated with more severe CXR score and may serve as predictors of COVID-19 mortality.

INTRODUCTION/UNASSIGNED:Interventions and surgical procedures are common for nonmalignant lung lesions detected on lung cancer screening (LCS). Inadvertent surgical resection of benign nodules with a clinical suspicion of lung cancer can occur, can be associated with complications, and adds to the cost of screening. The objective of this study is to assess the characteristics of surgically resected benign nodules detected on LCS computed tomography which were presumed to be lung cancers. METHODS/UNASSIGNED:This retrospective study included 4798 patients who underwent LCS between June 2014 and January 2021. The benign lung nodules, surgically resected with a presumed cancer diagnosis, were identified from the LCS registry. Patient demographics, imaging characteristics, and pathologic diagnoses of benign nodules were analyzed. RESULTS/UNASSIGNED:Of the 4798 patients who underwent LCS, 148 (3.1%) underwent surgical resection of a lung nodule, and of those who had a resection, 19 of 148 (12.8%) had a benign diagnosis (median age = 64 y, range: 56-77 y; F = 12 of 19, 63.2%; M = seven of 19, 36.8%). The median nodule size was 10 mm (range: 6-31 mm). Most nodules were solid (15 of 19, 78.9%), located in the upper lobes (11 of 19; 57.9%), and were peripheral (17 of 19, 89.5%). Most nodules (13 of 17; 76.5%) had interval growth, and four of 17 (23.5%) had increased fluorodeoxyglucose uptake. Of the 19 patients, 17 (89.5%) underwent sublobar resection (16 wedge resection and one segmentectomy), whereas two central nodules (10.5%) had lobectomies. Pathologies identified included focal areas of fibrosis or scarring (n = 8), necrotizing granulomatous inflammation (n = 3), other nonspecific inflammatory focus (n = 3), benign tumors (n = 3), reactive lymphoid hyperplasia (n = 1), and organizing pneumonia (n = 1). CONCLUSIONS/UNASSIGNED:Surgical resections of benign nodules that were presumed malignant are infrequent and may be unavoidable given overlapping imaging features of benign and malignant nodules. Knowledge of benign pathologies that can mimic malignancy may help reduce the incidence of unnecessary surgeries.

The axilla contains several important structures which exist in a relatively confined anatomic space between the neck, chest wall, and upper extremity. While neoplastic lymphadenopathy may be among the most common axillary conditions, many other processes may be encountered. For example, expanded use of axillary vessels for access routes for endovascular procedures will increase the need for radiologists to access vessel anatomy, patency, and complications that may arise. Knowledge of axillary anatomy and pathology will allow the imager to systematically evaluate the axillae using various imaging modalities.

The first year of radiology residency presents many unique challenges, from transitioning into a completely new, specialized field to preparing for call. Implementation of a longitudinal lecture series dedicated towards the clinical demands of being a first-year radiology resident may improve their knowledge and comfort level, as well as benefit the entire program. In this article, we outline our experience with the development of a resident-led dedicated first-year radiology resident lecture series providing targeted, high-yield instruction on rotation logistics, basic physics and artifacts, examination protocolling, and common and "don't miss" pathology.