A fitness index for transplantation of machine-perfused cadaveric rat livers.
BACKGROUND
The 110,000 patients currently on the transplant waiting list reflect the critical shortage of viable donor organs. However, a large pool of unused organs, from donors after cardiac death (DCD) that are disqualified because of extensive ischemic injury, may prove transplantable after machine perfusion treatment, fundamentally impacting the availability of treatment for end-stage organ failure. Machine perfusion is an ex-vivo organ preservation and treatment procedure that has the capacity to quantitatively evaluate and resuscitate cadaveric organs for transplantation.


METHODS
To diagnose whether an organ was fresh or ischemic, an initial assessment of liver quality was conducted via dynamic discriminant analysis. Subsequently, to determine whether the organs were sufficiently viable for successful implantation, fitness indices for transplantation were calculated based on squared prediction errors (SPE) for fresh and ischemic livers.


RESULTS
With just three perfusate metabolites, glucose, urea and lactate, the developed MPLSDA model distinguished livers as fresh or ischemic with 90% specificity. The SPE analyses revealed that fresh livers with SPE(F) < 10.03 and WI livers with SPE(WI) < 3.92 yield successful transplantation with 95% specificity.


CONCLUSIONS
The statistical methods used here can discriminate between fresh and ischemic livers based on simple metabolic indicators measured during perfusion. The result is a predictive fitness index for transplantation of rat livers procured after cardiac death. The translational implications of this study are that any donor organ procured from controlled, but most especially from uncontrolled cardiac death donors, will be objectively assessed and its recovery monitored over time, minimizing the critical loss of otherwise viable organs.
Center for Engineering in Medicine, Massachusetts General Hospital, Harvard Medical School, and the Shriners Hospitals for Children, Boston, MA 02114, USA.
Sinem
S
Perk
Maria-Louisa
ML
Izamis
Herman
H
Tolboom
Basak
B
Uygun
Martin L
ML
Yarmush
Korkut
K
Uygun
D000818:Animals; D015415:Biomarkers / Q000378:metabolism; D016002:Discriminant Analysis; D046148:Donor Selection; D005947:Glucose / Q000378:metabolism; D006498:Hepatectomy / Q000009:adverse effects*; D007511:Ischemia / Q000175:diagnosis* / Q000209:etiology / Q000378:metabolism; D019344:Lactic Acid / Q000378:metabolism; D016018:Least-Squares Analysis; D008099:Liver / Q000098:blood supply / Q000378:metabolism / Q000601:surgery*; D016031:Liver Transplantation / Q000379:methods*; D008297:Male; D063305:Organ Dysfunction Scores; D010477:Perfusion / Q000009:adverse effects; D025341:Principal Component Analysis; D051381:Rats; D011917:Rats, Inbred Lew; D013997:Time Factors; D014019:Tissue Donors; D014508:Urea / Q000378:metabolism; D052096:Warm Ischemia / Q000009:adverse effects
D015415:Biomarkers; D019344:Lactic Acid; D014508:Urea; D005947:Glucose