Back to Authors

Little, Brent P.

https://orcid.org/0000-0001-6657-8241

Mayo Clinic

Mayo Clinic

Citations 23

The Key Role of Radiologist Expertise in Collaborative Artificial Intelligence Workflows
Little, Brent P.

American Journal of Roentgenology | June 17, 2026 | Volume: No volume available | Issue: No issue available | Pages: 1-1

10.2214/ajr.26.35333 Get It

Imaging and Reporting of Post–COVID-19 Lung Abnormalities at CT: International Panel of Experts Provides Welcome Guidance
Little, Brent P.

American Journal of Roentgenology | October 15, 2025 | Volume: 225 | Issue: 6 | Pages: No page available

10.2214/ajr.25.33999 Get It

Correlation of Automated Adaptive Thresholding for Inspiratory Mosaic and Expiratory Air Trapping on Chest CT With Pulmonary Function Tests
Helgeson, Scott A. , Demirer, Mutlu , Gupta, Vikash , Erdal, Barbaros S. , Sonavane, Sushilkumar K. , Helgeson, Scott A , Little, Brent P. , White, Richard D.

Journal of Computer Assisted Tomography | September 16, 2025 | Volume: 50 | Issue: 2 | Pages: 286-293

10.1097/rct.0000000000001798 Get It

Objective: Pulmonary air trapping is critical for diagnosing and prognostication of various lung diseases. Expiratory CT imaging serves as an accessible method to assess air trapping, which correlates with small airway disease outcomes. Air trapping manifests as mosaic attenuation on inspiratory chest CT that is difficult for visual estimation. The primary aim of this study was to develop an automated tool to quantify mosaic attenuation on inspiratory CT and air trapping on paired expiratory CT. Secondary aims included comparing CT-derived parameters with PFT measurements and dyspnea scores. Methods: This retrospective analysis of noncontrast chest CTs from 2 academic hospitals was conducted between January 1, 2018, and December 31, 2019. Patients with paired inspiratory and expiratory CT chest scans and PFTs performed on the same day were included. A chest radiologist manually annotated lung parenchyma in a reference cohort. Several histogram-based metrics were computed from lung parenchymal CT values, with the maximum peak position showing the strongest correlation with manually determined thresholds. This threshold, derived from the histogram peak, was applied in the adaptive thresholding process to quantify mosaic attenuation and air trapping. Results: We analyzed 267 patients (65.5% female, median age 68). Most exhibited normal physiological patterns (44.0%). Patients with elevated residual volume (RV) by PFTs (28.1%) had significantly higher inspiratory CT mosaic attenuation (1629.6 vs. 1311.5 mL, P <0.01) and expiratory CT air trapping volumes (1413.7 vs. 886.2 mL, P <0.01). Correlation analyses demonstrated strong relationships between CT-derived mosaic attenuation and air trapping measures and RV. The correlation with PFT parameters was even stronger in subgroup analyses in patients with obstructive PFT patterns. These models had good predictive ability for an abnormal RV (AUC of 0.92, sensitivity of 72.4%, and specificity of 92.0%) and clinical utility based on good correlation with the mMRC dyspnea score ( r =0.71; 95% CI: 0.65-0.77). Conclusions: This automated adaptive thresholding on inspiratory and expiratory chest CT scans showed a high correlation of lung volume and air trapping parameters with PFTs, revealing that measures of lung function have a complex interplay with air trapping.
Generative AI Reporting of Chest Radiographs: Promise and Perspectives
Little, Brent P. , Little, Brent P

Radiology | March 25, 2025 | Volume: 314 | Issue: 3 | Pages: No page available

10.1148/radiol.250234 Get It

Mediastinal Lymph Node Staging in Non–Small Cell Lung Cancer: Challenges and Potential for Risk-Based Guidance
Little, Brent P.

American Journal of Roentgenology | March 12, 2025 | Volume: 224 | Issue: 5 | Pages: No page available

10.2214/ajr.25.32897 Get It

Quantitative Interstitial Abnormality Progression: Association with Acute Respiratory Events and Implications for Clinical Practice
Little, Brent P. , Little, Brent P

Radiology | April 30, 2024 | Volume: 311 | Issue: 1 | Pages: No page available

10.1148/radiol.240791 Get It

Searching for Screening
Zippi, Zachary , Grage, Rolf A. , Johnson, Elizabeth , Mergo, Patricia J. , Sonavane, Sushil, Stowell, Justin T. , Sonavane, Sushil K, Little, Brent P.

Journal of Thoracic Imaging | April 25, 2024 | Volume: 39 | Issue: 6 | Pages: 342-343

10.1097/rti.0000000000000785 Get It

RadioGraphics Update: The 10 Pillars of Lung Cancer Screening—Rationale and Logistics of a Lung Cancer Screening Program
Adams, Scott , Flores, Efrén J. , Sharma, Amita , Lennes, Inga T. , Shepard, Jo-Anne O. , Fintelmann, Florian J. , Adams, Scott J , Sharma, Amita , Shepard, Jo-Anne O , Fintelmann, Florian J , Flores, Efren J , Little, Brent P.

RadioGraphics | February 8, 2024 | Volume: 44 | Issue: 3 | Pages: No page available

10.1148/rg.230057 Get It

Editorial Comment: Artificial Intelligence for Detection of Endotracheal Tube Malposition—Augmented Rather Than Autonomous Radiology Interpretation
Little, Brent P.

American Journal of Roentgenology | October 4, 2023 | Volume: 222 | Issue: 1 | Pages: No page available

10.2214/ajr.23.30297 Get It

Breast Findings at Chest CT
Stowell, Justin T. , Grage, Rolf A. , Cortopassi, Isabel O. , Little, Brent P. , Maimone, Santo , Little, Brent P , Maimone, Santo

RadioGraphics | July 13, 2023 | Volume: 43 | Issue: 8 | Pages: No page available

10.1148/rg.220095 Get It