Publications by authors named "Dylan Zhang"
Background And Purpose: To develop and evaluate an automated, AI-based, volumetric brain tumor MRI response assessment algorithm on a large cohort of patients treated at a high-volume brain tumor center.
Materials And Methods: We retrospectively analyzed data from 634 patients treated for glioblastoma at a single brain tumor center over a 5-year period (2017-2021). The mean age was 56 +/-13 years.
Article Synopsis
- PI-RADS 4 lesions are associated with a high likelihood of significant prostate cancer, but targeted biopsies reveal diverse histological results, highlighting the need for improved diagnostic accuracy.
- A study analyzed 248 patients with PI-RADS 4 lesions, using a Quality Improvement protocol to assess discordant biopsy results; post-review, the Positive Predictive Values increased, indicating better diagnostic outcomes.
- The results emphasized the usefulness of subcategorizing lesions based on ADC values, which led to improved Cancer Detection Rates for lesions with higher suspicion, suggesting a more tailored approach to patient management.
Introduction: Biomarkers are needed to identify patients with metastatic renal cell carcinoma (mRCC) most likely to benefit from immune checkpoint inhibitors. We examined associations between radiographically assessed body composition (BC) variables and body mass index (BMI) with clinical outcomes for patients with mRCC receiving first-line ipilimumab + nivolumab (ipi/nivo).
Patients And Methods: We retrospectively reviewed all patients with mRCC treated with first-line ipi/nivo at one institution before June 1, 2021 with an analyzable baseline computed tomography (CT) scan.
Rationale And Objectives: Adoption of the Prostate Imaging Reporting & Data System (PI-RADS) has been shown to increase detection of clinically significant prostate cancer on prostate mpMRI. We propose that a rule-based algorithm based on Regular Expression (RegEx) matching can be used to automatically categorize prostate mpMRI reports into categories as a means by which to assess for opportunities for quality improvement.
Materials And Methods: All prostate mpMRIs performed in the Duke University Health System from January 2, 2015, to January 29, 2021, were analyzed.
There is uncertainty with how to proceed when targeted prostate biopsy of suspicious multiparametric magnetic resonance imaging (mpMRI) lesions return without clinically significant prostate cancer (csPCa). While possible, there are error sources that could contribute to such discordance including the mpMRI read, mpMRI-ultrasound fusion, biopsy technique, and histologic classification. Consequences are potentially significant; mistakenly missing csPCa can lead to delays in curative treatment.
View Article and Find Full Text PDFPurpose: Manual measurement of body composition on computed tomography (CT) is time-consuming, limiting its clinical use. We validate a software program, Automatic Body composition Analyzer using Computed tomography image Segmentation (ABACS), for the automated measurement of body composition by comparing its performance to manual segmentation in a cohort of patients with bladder cancer.
Method: We performed a retrospective analysis of 285 patients treated for bladder cancer at the Duke University Health System from 1996 to 2017.