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1. Enhancement-constrained acceleration: A robust reconstruction framework in breast DCE-MRI

   https://doi.org/10.1371/journal.pone.0258621  

   Easley, Ty O. ; Ren, Zhen ; Kim, Byol ; Karczmar, Gregory S. ; Barber, Rina F. ; Pineda, Federico D. ( October 2021 , PLOS ONE)

   Chen, Xi (Ed.)

   In patients with dense breasts or at high risk of breast cancer, dynamic contrast enhanced MRI (DCE-MRI) is a highly sensitive diagnostic tool. However, its specificity is highly variable and sometimes low; quantitative measurements of contrast uptake parameters may improve specificity and mitigate this issue. To improve diagnostic accuracy, data need to be captured at high spatial and temporal resolution. While many methods exist to accelerate MRI temporal resolution, not all are optimized to capture breast DCE-MRI dynamics. We propose a novel, flexible, and powerful framework for the reconstruction of highly-undersampled DCE-MRI data: enhancement-constrained acceleration (ECA). Enhancement-constrained acceleration uses an assumption of smooth enhancement at small time-scale to estimate points of smooth enhancement curves in small time intervals at each voxel. This method is tested in silico with physiologically realistic virtual phantoms, simulating state-of-the-art ultrafast acquisitions at 3.5s temporal resolution reconstructed at 0.25s temporal resolution (demo code available here). Virtual phantoms were developed from real patient data and parametrized in continuous time with arterial input function (AIF) models and lesion enhancement functions. Enhancement-constrained acceleration was compared to standard ultrafast reconstruction in estimating the bolus arrival time and initial slope of enhancement from reconstructed images. We found that the ECA method reconstructed images at 0.25s temporal resolution with no significant loss in image fidelity, a 4x reduction in the error of bolus arrival time estimation in lesions ( p < 0.01) and 11x error reduction in blood vessels ( p < 0.01). Our results suggest that ECA is a powerful and versatile tool for breast DCE-MRI. 

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2. Acceptability of 3D‐printed breast models and their impact on the decisional conflict of breast cancer patients: A feasibility study

   https://doi.org/10.1002/jso.26420  

   Santiago, Lumarie ; Volk, Robert J. ; Checka, Cristina M. ; Black, Dalliah ; Lee, Joanna ; Colen, Jessica S. ; Akay, Catherine ; Caudle, Abigail ; Kuerer, Henry ; Arribas, Elsa M. ( February 2021 , Journal of Surgical Oncology)

   To evaluate the acceptability and impact of 3D‐printed breast models (3D‐BMs) on treatment‐related decisional conflict (DC) of breast cancer patients.

   Patients with breast cancer were accrued in a prospective institutional review board‐approved trial. All patients underwent contrast‐enhanced breast magnetic resonance imaging (MRI). A personalized 3D‐BM was derived from MRI. DC was evaluated pre‐ and post‐3D‐BM review. 3D‐BM acceptability was assessed post‐3D‐BM review.

   DC surveys before and after 3D‐BM review and 3D‐BM acceptability surveys were completed by 25 patients. 3D‐BM were generated in two patients with bilateral breast cancer. The mean patient age was 48.8 years (28−72). The tumor stage was Tis (7), 1 (8), 2 (8), and 3 (4). The nodal staging was 0 (19), 1 (7), and 3 (1). Tumors were unifocal (15), multifocal (8), or multicentric (4). Patients underwent mastectomy (13) and segmental mastectomy (14) with (20) or without (7) oncoplastic intervention. Neoadjuvant therapy was given to seven patients. Patients rated the acceptability of the 3D‐BM as good/excellent in understanding their condition (24/24), understanding disease size (25/25), 3D‐BM detail (22/25), understanding their surgical options (24/25), encouraging to ask questions (23/25), 3D‐BM size (24/25), and impartial to surgical options (17/24). There was a significant reduction in the overall DC post‐3D‐BM review, indicating patients became more assured of their treatment choice (p = 0.002). Reduction post‐3D‐BM review was also observed in the uncertainty (p = 0.012), feeling informed about options (p = 0.005), clarity about values (p = 0.032), and effective (p = 0.002) Decisional Conflict Scale subscales.

   3D‐BMs are an acceptable tool to decrease DC in breast cancer patients.

    

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3. Development and validation of a life expectancy calculator for US patients with prostate cancer

   https://doi.org/10.1111/bju.15740  

   Chase, Elizabeth C. ; Bryant, Alex K. ; Sun, Yilun ; Jackson, William C. ; Spratt, Daniel E. ; Dess, Robert T. ; Schipper, Matthew J. ( April 2022 , BJU International)

   To develop and validate an accurate, usable prediction model for other‐cause mortality (OCM) in patients with prostate cancer diagnosed in the United States.

   Model training was performed using the National Health and Nutrition Examination Survey 1999–2010 including men aged >40 years with follow‐up to the year 2014. The model was validated in the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial prostate cancer cohort, which enrolled patients between 1993 and 2001 with follow‐up to the year 2015. Time‐dependent area under the curve (AUC) and calibration were assessed in the validation cohort. Analyses were performed to assess algorithmic bias.

   The 2420 patient training cohort had 459 deaths over a median follow‐up of 8.8 years among survivors. The final model included eight predictors: age; education; marital status; diabetes; hypertension; stroke; body mass index; and smoking. It had an AUC of 0.75 at 10 years for predicting OCM in the validation cohort of 8220 patients. The final model significantly outperformed the Social Security Administration life tables and showed adequate predictive performance across race, educational attainment, and marital status subgroups. There is evidence of major variability in life expectancy that is not captured by age, with life expectancy predictions differing by 10 or more years among patients of the same age.

   Using two national cohorts, we have developed and validated a simple and useful prediction model for OCM for patients with prostate cancer treated in the United States, which will allow for more personalized treatment in accordance with guidelines.

    

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4. Comparison of germline mutations in African American and Caucasian men with metastatic prostate cancer

   https://doi.org/10.1002/pros.24123  

   Ledet, Elisa M. ; Burgess, Earle F. ; Sokolova, Alexandra O. ; Jaeger, Ellen B. ; Hatton, Whitley ; Moses, Marcus ; Miller, Patrick ; Cotogno, Patrick ; Layton, Jodi ; Barata, Pedro ; et al ( April 2021 , The Prostate)

   The goal of this study is to evaluate germline genetic variants in African American men with metastatic prostate cancer as compared to those in Caucasian men with metastatic prostate cancer in an effort to understand the role of genetic factors in these populations.

   African American and Caucasian men with metastatic prostate cancer who had germline testing using multigene panels were used to generate comparisons. Germline genetic results, clinical parameters, and family histories between the two populations were analyzed.

   A total of 867 patients were included in this retrospective study, including 188 African American and 669 Caucasian patients. There was no significant difference in the likelihood of a pathogenic or likely‐pathogenic variants (PV/LPVs) between African American and Caucasian patients (p = .09). African American patients were more likely to have a variant of unknown significance than Caucasians (odds ratio [OR] = 1.95;p < .0001). BRCA1 PV/LPVs were higher in African Americans (OR = 4.86;p = .04). African American patients were less likely to have a PV/LPV in non‐BRCA DNA repair genes (OR = 0.30;p = .008). Family history of breast (OR = 2.09;p = .002) or ovarian cancer (OR = 2.33;p = .04) predicted PV/LPVs in Caucasians but not African‐Americans. This underscores the limitations of family history in AA men and the importance of personal history to guide germline testing in AA men.

   In metastatic prostate cancer patients, PV/LPVs of tested genes did not vary by race, BRCA1 PV/LPVs were more common in the African American subset. However, PV/LPVs in non‐BRCA DNA repair genes were less likely to be encountered in African Americans. Family history associated with genetic testing results in Caucasians only.

    

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5. A Pilot Study on Patient-specific Computational Forecasting of Prostate Cancer Growth during Active Surveillance Using an Imaging-informed Biomechanistic Model

   https://doi.org/10.1158/2767-9764.CRC-23-0449  

   Lorenzo, Guillermo ; Heiselman, Jon S. ; Liss, Michael A. ; Miga, Michael I. ; Gomez, Hector ; Yankeelov, Thomas E. ; Reali, Alessandro ; Hughes, Thomas J. R. ( March 2024 , Cancer Research Communications)

   Personalization of a biomechanistic model of prostate cancer with mpMRI data enables the prediction of tumor progression, thereby showing promise to guide clinical decision-making during AS for each individual patient.

    

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