A5008532967- MRI in cancer diagnosis
- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Medical Imaging Techniques and Applications
- Brain Tumor Detection and Classification
- Autoimmune and Inflammatory Disorders Research
- AI in cancer detection
- Breast Lesions and Carcinomas
- Breast Cancer Treatment Studies
- Infrared Thermography in Medicine
- Digital Radiography and Breast Imaging
- Korean Peninsula Historical and Political Studies
- Rheumatoid Arthritis Research and Therapies
- Advanced Fluorescence Microscopy Techniques
- Medical Image Segmentation Techniques
- Spondyloarthritis Studies and Treatments
- Exercise and Physiological Responses
- Orthopedic Infections and Treatments
- Esophageal Cancer Research and Treatment
- Optical Imaging and Spectroscopy Techniques
- Osteomyelitis and Bone Disorders Research
- Cancer Genomics and Diagnostics
- Colorectal Cancer Surgical Treatments
- Diverse Topics in Contemporary Research
University of Washington
2018-2025
Fred Hutch Cancer Center
2023-2024
Seattle Cancer Care Alliance
2018-2022
Background Contrast-enhanced mammography (CEM) and abbreviated breast MRI (ABMRI) are emerging alternatives to standard for supplemental cancer screening. Purpose To compare the diagnostic performance of CEM, ABMRI, MRI. Materials Methods This single-institution, prospective, blinded reader study included female participants referred from January 2018 June 2021. CEM was performed within 14 days MRI; ABMRI produced images. Two readers independently interpreted each after a washout period....
Background The Eastern Cooperative Oncology Group–American College of Radiology Imaging Network Cancer Research Group multicenter A6702 trial identified an optimal apparent diffusion coefficient (ADC) cutoff to potentially reduce biopsies by 21% without affecting sensitivity. Whether this performance can be achieved in clinical settings has not yet been established. Purpose To validate the point-of-care ADC measurements with for reducing unnecessary lesions detected at breast MRI. Materials...
Breast cancer diagnosis is inherently multimodal. To assess a patient's status, physicians integrate imaging findings with variety of clinical risk factor data. Despite this, deep learning approaches for automatic breast classification often only utilize image data or non-image data, but not both simultaneously. In this work, we implemented and compared strategies the fusion tabular in an end-to-end trainable manner, evaluating at different stages model (fusing intermediate features vs....
The intravoxel incoherent motion (IVIM) model of diffusion weighted imaging (DWI) provides biomarkers for breast tumor characterization. It has been extensively applied both diagnostic and prognostic goals in cancer, with increasing evidence supporting its clinical relevance. However, variable performance exists literature owing to the heterogeneity datasets quantification methods. This work used retrospective anonymized MRI data (302 patients) from three sites employing different software...
Models using clinical and MRI-based radiomic features identified from ductal carcinoma in situ lesions improved prediction of disease upstaging at surgery compared with standard information alone.
Objective Chronic nonbacterial osteomyelitis (CNO) is an autoinflammatory bone disease. An inexpensive and rapid imaging tool, infrared thermal imaging, was evaluated for its utility to detect active lesions in extremities of children with CNO. Methods Children suspected CNO healthy controls were enrolled. All subjects underwent the lower extremities. Patients group also received a magnetic resonance (MRI) examination. Hyperintensity within marrow on fluid‐sensitive T2‐weighted MRI sequence...
Purpose To investigate the impact of longitudinal variation in functional tumor volume (FTV) underestimation and overestimation predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC). Materials Methods Women with breast cancer who were enrolled prospective I-SPY 2 TRIAL (Investigation Serial Studies to Predict Your Therapeutic Response Imaging Molecular Analysis 2) from May 2010 November 2016 eligible for this retrospective analysis. Participants underwent four...
Purpose To examine the clinical value of multiband (MB) sensitivity encoding (SENSE)–accelerated diffusion-weighted imaging (DWI) for breast by performing quantitative and qualitative comparisons with conventional echo-planar imaging, or DWI (cDWI). Materials Methods In this prospective study (ClinicalTrials.gov identifier NCT03607552), women cancer were recruited from July 2018 to 2019 undergo additional MB SENSE during 3-T MRI examinations. The cDWI acquisitions assessed both...
Abstract INTRODUCTION Ductal carcinoma in situ (DCIS) is a non-lethal pre-invasive breast cancer that can co-exist with invasive disease. Dynamic contrast-enhanced (DCE) MRI sensitive for the detection of high-grade DCIS and while Oncotype Score 12-gene assay assess recurrence risk. In practice, it difficult to distinguish low- from high-risk DCIS, which leads overtreatment up half women diagnosed DCIS. We hypothesize radiomic phenotypes derived DCE-MRI data may serve as prognostic markers...
Diffusion weighted imaging (DWI) is emerging as a viable tool for non-contrast MRI breast cancer screening, but it unclear what factors on DWI impact lesion detectability. In this prospective clinical trial, we evaluated and that affected detection. Cancers were overall more detectable at higher b=1200 vs b=800 s/mm2, the background parenchymal signal (BPS) impacted visibility b value. Cancer histologic type also detectability DWI. Overall, our findings suggest interpretation values further...
Gradient nonlinearity (GNL) induces spatial bias in diffusion b-value that confounds apparent coefficient (ADC) measurements for anatomy offset from MRI scanner isocenter. For emerging vendor-provided GNL correction (GNC) a standardized quality control (QC) procedure is desired to streamline GNC application multi-site imaging trials utilize ADC tumor monitoring and therapy response assessment. This QC was developed tested on four systems with on-line trial-specific phantoms patient scans...
Motivation: Apparent Diffusion Coefficient (ADC) measures can help reduce false positives in breast MRI. Goal(s): Explore different approaches for measuring lesion ADC that emphasize aspects of tumor microenvironment and biology their effect on reducing unnecessary biopsies. Approach: Nine were computed each using b value combinations segmentation techniques. Different selecting threshold explored to Results: Applying cutoffs, the largest reduction benign biopsies (~20%) was achieved...
Motivation: Determine best-practice quantitative DCE-MRI for predicting breast cancer (BC) response to neoadjuvant chemotherapy (NAC) in a multi-center (MC) and multi-vendor platform (MP) setting. Goal(s): Evaluate effects of different pharmacokinetic analysis approaches on Ktrans its predictive performance. Approach: 15 BC patients treated with NAC underwent longitudinal at 3 sites using 3T systems from vendors. Variations included Tofts model vs. Shutter-Speed (SSM), ROI- voxel-based...
Motivation: Improve accuracy of ADC measurement by correcting spatial nonuniformity diffusion weighting caused gradient nonlinearity (GNL) using novel vendor implemented on-scanner tools Goal(s): Evaluate GNL correction breast tumor in a treatment response study Approach: Implement correction, evaluate uncorrected and corrected ADCs, bias changes pre-treatment post one cycle neoadjuvant chemotherapy. Results: Preliminary results from this indicate adequate performance the DWI assessment to...
Motivation: Intravoxel incoherent motion (IVIM) MRI is helpful in breast tumor characterization, but variable performance exists the literature. Goal(s): Translational assessment of multisite lesion data based on 1st order radiomics features from each IVIM parameters perfusion fraction (fp), pseudodiffusivity (Dp) and tissue diffusivity (Dt) derived multiple software platforms. Approach: This work used retrospective anonymized three sites employing different to estimate fp, Dp Dt, their...
Motivation: Investigate water exchange rate constant (kio) in monitoring breast cancer (BC) response to neoadjuvant chemotherapy (NAC). Goal(s): Evaluate changes kio and voxel fraction of filtered during NAC. Approach: BC patients treated with NAC underwent longitudinal high spatiotemporal resolution DCE-MRI at three sites using different 3T vendor systems. Voxel values were obtained the shutter-speed modeling a biologically relevant DCE achievable range. Results: Fractions decreased...
Motivation: Validate Shutter-Speed model (SSM) DCE-MRI as a robust predictor of breast cancer (BC) response to neoadjuvant chemotherapy (NAC) in multi-center and multi-vendor platform setting. Goal(s): Compare tumor size, semi-quantitative, quantitative for early prediction NAC response. Approach: BC patients treated with underwent longitudinal high spatiotemporal resolution at three sites using 3T Siemens, GE, or Philips system. Semi-quantitative signal-enhancement-ratio (SER) Tofts (TM)...
Motivation: EPI-based DWI suffers from ghosting, chemical shift, and distortion artifacts. FSE-based DW-PROPELLER has been shown to overcome the above artifacts but at cost of longer scanner time. Goal(s): To evaluate combination with a deep learning (DL)-based reconstruction provide motion-robust distortion-free high spatial resolution breast DWI. Approach: Phantom in-vivo images were acquired using followed by both conventional DL reconstruction. Results: showed less distortion, shift...
Quantitative dynamic contrast-enhanced (DCE) MRI as a promising method for the prediction of breast cancer response to neoadjuvant chemotherapy (NAC) has been demonstrated mostly in single-center and single-vendor platform studies. This preliminary study reports initial experience implementing quantitative DCE-MRI multi-center (MC) multi-vendor (MP) settings predict NAC response. data, including B
Diffusion weighted MRI (DWI) has emerged as a promising adjunct to reduce unnecessary biopsies prompted by breast through use of apparent diffusion coefficient (ADC) measures. The purpose this study was investigate the effects different lesion ADC measurement approaches and cutoffs on diagnostic performance DWI in high-risk screening cohort identify optimal approach for clinical incorporation.