Quantitative imaging features and postoperative hepatic insufficiency: A multi-institutional expanded cohort Journal Article

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Authors: Pak, L. M.; Chakraborty, J.; Gonen, M.; Chapman, W. C.; Do, R. K. G.; Groot Koerkamp, B.; Verhoef, K.; Lee, S. Y.; Massani, M.; van der Stok, E. P.; Simpson, A. L.; Memorial Sloan Kettering Cancer Center Hepatopancreatobiliary Service
Contributors: Jarnagin, W. R.; Allen, P. J.; D'Angelica, M. I.; DeMatteo, R. P.; Kingham, T. P.; Balachandran, V. P.
Article Title: Quantitative imaging features and postoperative hepatic insufficiency: A multi-institutional expanded cohort
Abstract: Background: Post-hepatectomy liver insufficiency (PHLI) is a significant cause of morbidity and mortality after liver resection. Quantitative imaging analysis using CT scans measures variations in pixel intensity related to perfusion. A preliminary study demonstrated a correlation between quantitative imaging features of the future liver remnant (FLR) parenchyma from preoperative CT scans and PHLI. The objective of this study was to explore the potential application of quantitative imaging analysis in PHLI in an expanded, multi-institutional cohort. Study Design: We retrospectively identified patients from 5 high-volume academic centers who developed PHLI after major hepatectomy, and matched them to control patients without PHLI (by extent of resection, preoperative chemotherapy treatment, age [±5 years], and sex). Quantitative imaging features were extracted from the FLR in the preoperative CT scan, and the most discriminatory features were identified using conditional logistic regression. Percent remnant liver volume (RLV) was defined as follows: (FLR volume)/(total liver volume) × 100. Significant clinical and imaging features were combined in a multivariate analysis using conditional logistic regression. Results: From 2000 to 2015, 74 patients with PHLI and 74 matched controls were identified. The most common indications for surgery were colorectal liver metastases (53%), hepatocellular carcinoma (37%), and cholangiocarcinoma (9%). Two CT imaging features (FD1_4: image complexity; ACM1_10: spatial distribution of pixel intensity) were strongly associated with PHLI and remained associated with PHLI on multivariate analysis (p = 0.018 and p = 0.023, respectively), independent of clinical variables, including preoperative bilirubin and %RLV. Conclusions: Quantitative imaging features are independently associated with PHLI and are a promising preoperative risk stratification tool. © 2018 American College of Surgeons
Keywords: adult; controlled study; aged; cancer surgery; major clinical study; liver cell carcinoma; preoperative care; treatment indication; image analysis; cohort analysis; retrospective study; bilirubin; liver failure; quantitative analysis; liver resection; bile duct carcinoma; university hospital; liver weight; preoperative chemotherapy; colorectal liver metastasis; human; male; female; priority journal; article; high volume hospital; x-ray computed tomography
Journal Title: Journal of the American College of Surgeons
Volume: 226
Issue: 5
ISSN: 1072-7515
Publisher: Elsevier Science, Inc.  
Date Published: 2018-05-01
Start Page: 835
End Page: 843
Language: English
DOI: 10.1016/j.jamcollsurg.2018.02.001
PROVIDER: scopus
PMCID: PMC5924623
PUBMED: 29454098
DOI/URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85043323888&doi=10.1016%2fj.jamcollsurg.2018.02.001&partnerID=40&md5=ca27410fdbdf7d6cc9c37b8fb2fa8c71
Notes: Article -- Export Date: 1 May 2018 -- Source: Scopus
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MSK Authors
  1. Ronald P Dematteo
    553 Dematteo
  2. Mithat Gonen
    641 Gonen
  3. Peter Allen
    389 Allen
  4. William R Jarnagin
    522 Jarnagin
  5. Kinh Gian Do
    85 Do
  6. Michael D'Angelica
    423 D'Angelica
  7. T Peter Kingham
    252 Kingham
  8. Vinod P Balachandran
    48 Balachandran
  9. Amber L Simpson
    35 Simpson
  10. Jayasree Chakraborty
    15 Chakraborty
  11. Linda Ma
    13 Ma
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