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Brown C, Ray C, Kuketz G, Virostko J. Changes in Pancreas Volume in Living Donor Liver Transplant Recipients. Transplantation 2024:00007890-990000000-00732. [PMID: 38637920 DOI: 10.1097/tp.0000000000005031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
BACKGROUND Metabolic factors have a significant role in the morbidity and mortality associated with chronic liver disease. The pancreas has a central role in metabolism and metabolic risk factors but has been largely ignored in liver transplantation. Small pancreas volume has been demonstrated in pathologic conditions such as type 1 and 2 diabetes. METHODS This study assessed abdominal imaging before and after liver transplantation to determine if liver transplantation induces changes in pancreas volume in living donor liver transplant recipients. Our secondary outcome is to correlate pancreas volume with demographic, clinical, and outcome data. We conducted a retrospective study of pancreas volume in patients enrolled in the adult-to-adult living donor liver transplantation cohort study. Pancreas volume was manually calculated from 413 MRI or computed tomography images and correlated with imaging and clinical data. RESULTS Pancreas volume declined by an average of 24% (87.8 ± 25.2 mL to 66.8 ± 20.4 mL, P < 0.0001), regardless of liver disease etiology. Pancreas volume correlated with portal blood flow, spleen volume, and liver enzyme levels. We found a correlation between smaller pancreas volume pretransplant and longer intensive care unit (ICU) stay across all patients (P < 0.05). Individuals with an ICU stay of <2 d had a larger average pancreas volume pretransplant than those with an ICU stay of 2 d or longer (91.2 mL versus 82.2 mL, P < 0.05). CONCLUSIONS Pancreas volume is dynamic in liver transplant recipients and may reflect altered metabolism and risk of posttransplantation complications.
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Affiliation(s)
- Cristal Brown
- Department of Internal Medicine, Dell Medical School, University of Texas at Austin, Austin, TX
| | - Callaghan Ray
- Department of Diagnostic Medicine, Dell Medical School, University of Texas at Austin, Austin, TX
| | - Garrett Kuketz
- Department of Diagnostic Medicine, Dell Medical School, University of Texas at Austin, Austin, TX
| | - John Virostko
- Department of Diagnostic Medicine, Dell Medical School, University of Texas at Austin, Austin, TX
- Livestrong Cancer Institutes, Dell Medical School, University of Texas at Austin, Austin, TX
- Department of Oncology, Dell Medical School, University of Texas at Austin, Austin, TX
- Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX
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Virostko J, Kuketz G, Higgins E, Wu C, Sorace AG, DiCarlo JC, Avery S, Patt D, Goodgame B, Yankeelov TE. The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy. Eur J Radiol 2021; 136:109534. [PMID: 33454460 PMCID: PMC7897312 DOI: 10.1016/j.ejrad.2021.109534] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 12/11/2020] [Accepted: 01/05/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE This study assesses the rate of enhancement of breast fibroglandular tissue after administration of a magnetic resonance imaging (MRI) gadolinium-based contrast agent and determines its relationship with response to neoadjuvant therapy (NAT) in women with breast cancer. METHOD Women with locally advanced breast cancer (N = 19) were imaged four times over the course of NAT. Dynamic contrast-enhanced (DCE) MRI was acquired after administration of a gadolinium-based contrast agent with a temporal resolution of 7.27 s. The tumor, fibroglandular tissue, and adipose tissue were semi-automatically segmented using a manually drawn region of interest encompassing the tumor followed by fuzzy c-means clustering. The rate and relative intensity of signal enhancement were calculated for each voxel within the tumor and fibroglandular tissue. RESULTS The rate of fibroglandular tissue enhancement after contrast agent injection declined by an average of 29 % over the course of NAT. This decline was present in 16 of the 19 patients in the study. The rate of enhancement is significantly higher in women who achieve pathological complete response (pCR) after both 1 cycle (68 % higher, p < 0.05) and after 3-5 cycles of NAT (58 % higher; p < 0.05). The relative intensity of fibroglandular enhancement correlates with the rate of enhancement (R2 = 0.64, p < 0.001) and is higher in women who achieve pCR after both 1 cycle and after 3-5 cycles of NAT (p < 0.05, both timepoints). CONCLUSION The rate of fibroglandular tissue enhancement declines over the course of therapy, provides novel information not reflected by tumoral measures, and may predict pathological response early in the course of therapy, with smaller declines in enhancement in women who achieve favorable response.
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Affiliation(s)
- John Virostko
- Department of Diagnostic Medicine, University of Texas at Austin, Austin, TX, USA; Livestrong Cancer Institutes, University of Texas at Austin, Austin, TX, USA; Department of Oncology, University of Texas at Austin, Austin, TX, USA.
| | - Garrett Kuketz
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
| | - Erin Higgins
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
| | - Chengyue Wu
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
| | - Anna G. Sorace
- Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, USA,Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, USA,O’Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Julie C. DiCarlo
- Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
| | - Sarah Avery
- Austin Radiological Association, Austin, Texas, USA
| | | | - Boone Goodgame
- Seton Hospital, Austin, Texas, USA,Department of Internal Medicine, University of Texas at Austin, Austin, Texas, USA
| | - Thomas E. Yankeelov
- Department of Diagnostic Medicine, University of Texas at Austin, Austin, Texas, USA,Livestrong Cancer Institutes, University of Texas at Austin, Austin, Texas, USA,Department of Oncology, University of Texas at Austin, Austin, Texas, USA,Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA,Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA,Department of Imaging Physics, MD Anderson Cancer Center, Houston, Texas, USAI
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