Alternative methods for virtual heart transplant—Size matching for pediatric heart transplantation with and without donor medical images available

Jonathan D. Plasencia, Yiannis Kamarianakis, Justin R. Ryan, Tara Karamlou, Susan S. Park, John J. Nigro, David Frakes, Stephen G. Pophal, Carl F. Lagerstrom, Daniel A. Velez, Steven D. Zangwill

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: Listed pediatric heart transplant patients have the highest solid-organ waitlist mortality rate. The donor-recipient body weight (DRBW) ratio is the clinical standard for allograft size matching but may unnecessarily limit a patient's donor pool. To overcome DRBW ratio limitations, two methods of performing virtual heart transplant fit assessments were developed that account for patient-specific nuances. Method 1 uses an allograft total cardiac volume (TCV) prediction model informed by patient data wherein a matched allograft 3-D reconstruction is selected from a virtual library for assessment. Method 2 uses donor images for a direct virtual transplant assessment. Methods: Assessments were performed in medical image reconstruction software. The allograft model was developed using allometric/isometric scaling assumptions and cross-validation. Results: The final predictive model included gender, height, and weight. The 25th-, 50th-, and 75th-percentiles for TCV percentage errors were −13% (over-prediction), −1%, and 8% (under-prediction), respectively. Two examples illustrating the potential of virtual assessments are presented. Conclusion: Transplant centers can apply these methods to perform their virtual assessments using existing technology. These techniques have potential to improve organ allocation. With additional experience and refinement, virtual transplants may become standard of care for determining suitability of donor organ size for an identified recipient.

Original languageEnglish (US)
JournalPediatric Transplantation
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Heart Transplantation
Tissue Donors
Allografts
Pediatrics
Transplants
Cardiac Volume
Body Weight
Digital Libraries
Computer-Assisted Image Processing
Organ Size
Standard of Care
Software
Technology
Weights and Measures
Mortality

Keywords

  • heart transplant
  • pediatric transplant
  • virtual fit assessment
  • virtual transplant

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Transplantation

Cite this

Alternative methods for virtual heart transplant—Size matching for pediatric heart transplantation with and without donor medical images available. / Plasencia, Jonathan D.; Kamarianakis, Yiannis; Ryan, Justin R.; Karamlou, Tara; Park, Susan S.; Nigro, John J.; Frakes, David; Pophal, Stephen G.; Lagerstrom, Carl F.; Velez, Daniel A.; Zangwill, Steven D.

In: Pediatric Transplantation, 01.01.2018.

Research output: Contribution to journalArticle

Plasencia, Jonathan D. ; Kamarianakis, Yiannis ; Ryan, Justin R. ; Karamlou, Tara ; Park, Susan S. ; Nigro, John J. ; Frakes, David ; Pophal, Stephen G. ; Lagerstrom, Carl F. ; Velez, Daniel A. ; Zangwill, Steven D. / Alternative methods for virtual heart transplant—Size matching for pediatric heart transplantation with and without donor medical images available. In: Pediatric Transplantation. 2018.
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abstract = "Background: Listed pediatric heart transplant patients have the highest solid-organ waitlist mortality rate. The donor-recipient body weight (DRBW) ratio is the clinical standard for allograft size matching but may unnecessarily limit a patient's donor pool. To overcome DRBW ratio limitations, two methods of performing virtual heart transplant fit assessments were developed that account for patient-specific nuances. Method 1 uses an allograft total cardiac volume (TCV) prediction model informed by patient data wherein a matched allograft 3-D reconstruction is selected from a virtual library for assessment. Method 2 uses donor images for a direct virtual transplant assessment. Methods: Assessments were performed in medical image reconstruction software. The allograft model was developed using allometric/isometric scaling assumptions and cross-validation. Results: The final predictive model included gender, height, and weight. The 25th-, 50th-, and 75th-percentiles for TCV percentage errors were −13{\%} (over-prediction), −1{\%}, and 8{\%} (under-prediction), respectively. Two examples illustrating the potential of virtual assessments are presented. Conclusion: Transplant centers can apply these methods to perform their virtual assessments using existing technology. These techniques have potential to improve organ allocation. With additional experience and refinement, virtual transplants may become standard of care for determining suitability of donor organ size for an identified recipient.",
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