|Best of the Best Oral (pre-recorded)
Other / Misc
|BB01 "Best of the Best" - Oral (pre-recorded)
|"Best of the Best" selected from Abstract Submissions
|OBB-01 ||HepaT1ca - Quantitative Magnetic Resonance Imaging Predicts Individual Future Liver Performance after Liver Resection
Damian Mole, United Kingdom
D. Mole1, J. Fallowfield2, F. Welsh3, A. Sherif1, T. Kendall4, G. Ridgway5, J. Connell5, M. Rees3, for the HepaT1ca Study Team
1Clinical Surgery, University of Edinburgh, United Kingdom, 2Hepatology, University of Edinburgh, United Kingdom, 3Surgery, Hampshire Hospitals Foundation Trust, United Kingdom, 4Pathology, University of Edinburgh, United Kingdom, 5Perspectum Diagnostics Ltd., United Kingdom
Introduction: The future liver performance (FLP) of an individual undergoing liver resection for cancer is critical for their survival and recovery. Here, we report the development and clinical testing of HepT1ca, a novel magnetic resonance image (MRI) technology that combines multiparametric MRI signal processing with automated anatomical liver segmentation to estimate FLP.
Method: HepaT1ca combines iron-corrected T1 (cT1) mapping with a 3D U-net pipeline to automatically delineate the liver volume and Couinaud segments based on anatomical landmarks. HepaT1ca combines quantitative cT1 mapping with accurate estimation of the future liver remnant (FLR) volume to predict FLP. We evaluated the ability of HepaT1ca to predict post-operative morbidity, length of stay and regenerative capacity in a prospective 2-centre observational clinical trial (ClinicalTrials.gov NCT03213314).
Results: 135 of 143 patients recruited and scanned underwent liver resection. 84% of participants had colorectal liver metastases; the remainder had primary liver cancer or other secondary cancers. The HepaT1ca score showed a significant linear correlation with the modified Hyder-Pawlik score, an indicator of post-operative morbidity (adjusted R2=0.26, P< 0.001), and liver regenerative performance (adjusted R2=0.46, P< 0.001). Furthermore, in patients with an FLR < 90%, a mean cT1 >795ms was associated with a longer duration of hospital stay (median (IQR) of 6.5 (5.3-12) vs. 5 (4-7.1); P=0.005). cT1 also correlated with histological measures of inflammation and hepatocyte ballooning.
Conclusion: HepaT1ca is a non-invasive quantitative MRI technology for predicting FLP. HepT1ca informs individualised operative risk and augments patient and surgeon decision-making prior to liver resection.
[Figure: Concept diagram showing use of quantitative MRI in a clinical workflow highlighting exemplar]
|OBB-02 ||Minimally Invasive Approaches to Biliary Tract Cancers and Nodal Sampling: Not All Approaches Are Similar
Bradford Kim, United States
B. Kim, C.-W. Tzeng, N. Ikoma, Y.-J. Chiang, Y.S. Chun, T. Aloia, J.N. Vauthey, H. Tran Cao
Surgical Oncology, MD Anderson Cancer Center, United States
minimally invasive approaches (MIS) to biliary tract cancers become more
commonplace, understanding whether they offer adequate locoregional clearance
is critical. We sought to study how
laparoscopic and robotic approaches compare to open surgery for both intrahepatic
cholangiocarcinoma (ICC) and gallbladder cancer (GBC).
2010-2016, the National Cancer Database was queried for all patients who underwent
hepatic resection of ICC of any stage and T1b or more advanced GBC. Patients were grouped by approach: open(OA),
laparoscopic(LA), and robotic(RA). To
measure appropriateness of oncologic therapy, rate of lymph node (LN)
dissection, quality of LN dissection, and R0 resection were evaluated.
cohort of 8,612 patients [4,034 with ICC (OA:3,281, LA:675, RA:78) and
radical cholecystectomy for 4,578 with GBC (OA:1,893, LA:2,588, RA:97)], MIS
was used 40% of the time. R0 resection
was achieved in 71% OA, 67% LA, and 77% RA, p< 0.001. Rates of LN dissection were 58% for ICC (OA:
61% LA: 46% RA: 44%, p< 0.001) and 49% for GBC (OA: 59% LA: 41% RA: 58%,p< 0.001). When lymphadenectomy was
performed, mean LN number examined was 4.4 (OA: 4.7 LA: 3.7 RA: 4.9, p< 0.001).
When lymphadenectomy was performed, 6+LN
were retrieved rarely in both ICC (OA: 27%, LA 24%, and RA: 35%) and GBC (OA:
15%, LA: 7% and RA: 14%), p< 0.001.
approaches are increasingly used for ICC and GBC, monitoring surgical quality
will be paramount. Laparoscopy, in
particular, may fall short in achieving margin-negative resection and adequate
|OBB-03 ||Hypothermic Oxygenated Perfusion vs. Normothermic Regional Perfusion in Liver Transplantation from Non-heart Beating Donors-first International Comparative Study
Xavier Muller, France
M. Lesurtel1, X. Muller1,2, K. Mohkam1, F. Dondero3, E. Savier4, P. Bucur5, H. Jeddou6, G. Pittau7, P. Dutkowski2
1Department of General Surgery and Liver Transplantation, Croix-Rousse University Hospital, France, 2Department of Surgery and Transplantation, University Hospital Zurich, Switzerland, 3Department of Hepatobiliopancreatic Surgery, Beaujon Hospital, APHP, France, 4Department of Hepatobiliary Surgery and Liver Transplantation, Sorbonne Université Pitié-Salpêtrière Hospital, France, 5Department of Digestive, Oncological, Endocrine, Hepato-Biliary, Pancreatic and Liver Transplant Surgery, Trousseau Hospital, France, 6Department of Hepatobiliary and Digestive Surgery, Pontchaillou University Hospital, France, 7Centre Hépato-Biliaire, Hôpital Paul Brousse, Université Paris Sud, APHP, France
hypothermic oxygenated perfusion (HOPE) and in-situ normothermic
regional perfusion (NRP) improve outcomes in liver transplantation (LT) from
controlled donation after circulatory death (DCD) but a direct comparison is
Methods: This multicentre study included all NRP procedures
performed in France and all HOPE procedures performed in Zurich up to 2020, starting
in 2015 and 2012, respectively. The primary endpoint was 1-year graft survival.
To account for differences in graft utilization, an intention-to-treat analysis
was performed including perfused grafts which were discarded. A propensity
score matching was applied to correct for major donor, graft and recipient
Results: A total of 225 NRP and 104
HOPE procedures were performed with 107 (47%) and 92 (88%) transplants per group. NRP grafts were retrieved from younger donors (50 vs. 61, p< 0.001) with shorter functional donor warm ischemia times
(22 vs. 31min, p< 0.001). We
observed no difference in ischemic cholangiopathy (3.3% vs. 2.2%, NS), primary non-function (0% vs 4.3% p=0.12) and hepatic
artery thrombosis (2.2 vs. 2.2%, NS)
resulting in comparable graft survival rates (Figure). However, the
intention-to-treat analysis disclosed superior graft survival after HOPE. Propensity
score-matched analysis showed higher peak serum transaminases after HOPE (ALT 1576
vs. 468 and AST 3559 vs. 653, p< 0.001), while
graft and patient survival were comparable.
Conclusion: In DCD LT, NRP and HOPE both achieved benchmark
graft and patient survival rates with comparable outcomes in risk-adjusted
donor-recipient combinations. However, utilization rates were significantly
higher in the HOPE cohort suggesting superior clinical effectiveness.
[Tumor-censored graft survival (A) and intention-to-treat analysis for graft survival (B)]
|OBB-04 ||Single-center Experience of Liver Transplantation for Cholangiocarcinoma
Ola Ahmed, United States
O. Ahmed1, N. Vachharajani2, S.-H. Chang3, Y. Park3, A. Khan2, W. Chapman2, M. Doyle2
1Department of Surgery, Washington University School of Medicine,, United States, 2Department of Surgery, Washington University School of Medicine, United States, 3Division of Public Health Sciences, Washington University School of Medicine, United States
Introduction: Cholangiocarcinoma remains a rare and aggressive biliary
malignancy. Traditionally, curative resection was considered the cornerstone of
treatment, however, more recently liver transplantation (LT) offered an
alternative option for unresectable patients. The aim is to assess clinical
outcomes in patients with cholangiocarcinoma proceeding to LT.
Methods: Prior to 2007, all resectable patients proceeded to a
curative resection. A hilar cholangiocarcinoma protocol was commenced in 2007
within our institution whereby diagnosed patients were enrolled onto a registry
and considered for LT. Data on all patients with a diagnosis of
cholangiocarcinoma between 2007 and 2019 were studied within a prospectively
maintained institutional database.
Results: A total of 58 patients were initially enrolled and
considered for LT. Thirty-eight patients proceeded to LT upon completion of
neoadjuvant chemoradiation (26 male, mean age 55.6 +/- 11.4). Common
complications included hepatic artery stenosis (n=3), portal vein stenosis
(n=7) and bile leak (n= 3). Re-transplantation was required for 4 patients
occurring within 30 (n=3) and 45 days (n=1), respectively. Twelve patients
developed recurrence (31.6%), 2 were intrahepatic. There were 11 deaths during
the study period (n=9 from recurrent disease; n=2 unrelated causes). Overall
1-, 3- and 5- year survival rates were 94.3%, 56.9% and 50.6% respectively.
Disease-free survival was 87.8%, 57.8% and 46.2% at 1-, 3 and 5- years. Graft
survival was rates were 83.7%, 52% and 44.5% at 1-, 3- and 5- years respectively.
Conclusion: Liver transplantation provides a 50% 5-year survival rate
for appropriately selected patients who would otherwise have no surgical
|OBB-06 ||An Online Calculator to Predict Recurrence after Hepatectomy for Colorectal Liver Metastasis: Reflecting the New Era of Genetic and Biological Features
Anghela Paredes, United States
A. Moro1, D. Tsilimigras1, R. Mehta1, A. Guglielmi2, S. Alexandrescu3, G. Poultsides4, K. Sasaki5, F. Aucejo5, T. Pawlik6, A. Paredes1
1The Ohio State University Wexner Medical Center, Columbus, United States, 2University of Verona, Verona, Italy, 3Fundeni Clinical Institute, Bucharest, Romania, 4Stanford University, California, United States, 5Cleveland Clinic, Cleveland, United States, 6Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, United States
Introduction: The risk of recurrence after hepatectomy for colorectal liver metastasis (CRLM) remains high. The objective of the current study was to develop a novel online calculator to estimate the risk of CRLM recurrence using pathological, genetic, and morphologic tumor characteristics.
Methods: Patients who underwent hepatectomy for CRLM between 2001-2018 were identified from a multi-institutional international database. A prognostic model was developed in the training set and validated using an external cohort. An online calculator to estimate 1, 3, 5-year recurrence-free survival(RFS) was developed and compared with the clinical risk score (CRS) using Harell's c-index.
Results: Among 1,125 patients who underwent CRLM resection, one-third of patients had mtKRAS (n=343, 30.4%). Overall 1-, 3-, 5-year RFS was 61.1%, 33.9%, and 28.1 %, respectively. An on-line calculator that included clinical, pathological, KRAS status, as well as response to chemotherapy was developed (https://medicalcal.shinyapps.io/CRLM_RFS/)(Figure). 5-year RFS among low, intermediate, and high-risk group patients was 43.1%, 16.1%, and 3.3%, respectively (p< 0.001). The new prognostic model performed better than the CRS among all patients with CRLM (c-index:0.71 vs. 0.61), as well as among patients with wtKRAS (c-index: 0.68 vs. 0.62) or mtKRAS (c-index:0.73 vs. 0.61) tumors. External validation of the on-line prognostic calculator revealed good to very-good accuracy (c-index:0.66).
Conclusion: A novel online calculator that incorporated patient, tumor, KRAS status, as well as response to chemotherapy was more accurate in stratifying patients relative to RFS compared with the traditional CRS. These data highlight the importance of incorporating clinical and genetic information in estimating prognosis among patients with CRLM.
|OBB-08 ||Predicting Individual 10-year Survival after Resection of Colorectal Liver Metastases
Florian E. Buisman, Netherlands
F.E. Buisman1, W.R. Jarnagin2, T.P. Kingham2, D.J. Grünhagen1, E.R. Steyerberg3, C. Verhoef1, M.I. D'Angelica2, B. Groot Koerkamp1
1Erasmus MC, Netherlands, 2Memorial Sloan Kettering Cancer Center, United States, 3Leiden University Medical Center, Netherlands
Background: The aim of this study was to
predict the chance of 10-year overall survival (OS) for individual patients
after resection of CRLM based on patient, tumor, and treatment characteristics.
Methods: Consecutive patients after
complete resection of CRLM were included from two centers (1992-2008). A
simplified score was built to categorize patients into 5 categories regarding
the likelihood of 10-year OS. Discrimination was assessed using the time-dependent
Area Under the Curve (AUC) at 10-years after resection of CRLM, and with
Results: A total of 3990 patients were
eligible. The 10-year OS rate probability was 30%, with 497 actual 10 year
survivors. Independent factors for 10-year OS were; age at resection CRLM,
location colorectal cancer (CRC), nodal status CRC, number CRLM, diameter CRLM,
resection margin, extrahepatic disease,
KRAS mutation status, BRAF mutation status, and histopathological growth
pattern. Perioperative HAIP chemotherapy was the only independent treatment
factor for 10-year OS. The individual predicted 10-year OS ranged from 6% to 53%.
Five risk groups were identified based on the independent factors with a chance
of 10-year OS of 9% (n=601), 22% (n=885), 30% (n=1401), 44%(n=614), and
55%(n=489). Internal-external cross-validation validation demonstrated a pooled
AUC of 0.71 (95%CI 0.53-0.90) of the full model and 0.69 (95%CI 0.50-0.88) of
the simplified model.
Conclusion: The probability of 10-year
survival can be predicted after resection of CRLM based on 11 independent
prognostic factors and varies from 6% to 53%.
[Predicting individual 10-year survival after resection of colorectal liver metastases]
|OBB-09 ||Long Term Outcome of Patients with Close Resection Margin after Hepatectomy for HCC: A Propensity Score Analysis at a Single Centre
Wing Chiu Dai, Hong Kong
W. Dai, T. Cheung, A. Chan, T. Wong, W. She, K. Ma, K. Chu, M. Chan, C. Lo
Surgery, University of Hong Kong, Hong Kong
Introduction: Traditionally, hepatectomy
was recommended only if 10mm margin can be achieved. We analyzed the long term
outcome of those with close resection margin after hepatectomy for HCC.
Methods: From 1989-2017, 1793
patients underwent resection of HCC at Queen Mary Hospital, Hong Kong. 1697
patients (94.6%) achieved R0 resection. 216 (12.7%), 838 (49.4%) and 605 (35.7%)
patients had resection margin 0.5-2mm, >2-10mm and >10mm respectively. The
outcomes of those with close margin (0.5-2mm) (CM group) were compared with
those with wide margin (>10mm) (WM group) using propensity score matching in
terms of tumour size, number and differentiation in a ratio of 1:2.
Result: After matching, there
were 211 patients in the CM group and 422 patients in the WM group. The
demographic data was comparable between the 2 group as shown in table 1 except CM group had significantly more
blood loss (800ml vs 600ml, p= 0.007). The
1-year, 3-year, 5-year and 10-year overall survival was 91.5%, 72.8%, 59.8% and 43.5% for the CM group and 89.3%, 71.7% ,
58.8% and 44.4% for the WM group, respectively (P=0.759) [Figure 1]. The
1-year, 3-year, 5-year and 10-year disease free survival was 64.9%, 46.1%, 37%
and 27.1% for the CM group and 62.1%, 415.2%, 39.3% and 30.8% for the WM group,
Conclusion: Surgeons should
always aim for wide negative margin. However, resection of HCC with close
margin could still achieve good long term survival and, thus, resection should
not be excluded from those anticipated to have close resection margin.
[Overall survival of patients of CM group vs WM group after resection of HCC]
| ||CM group (n=211)||WM group (n=422)||P-value|
|Age||59.0 (24-80)||57.0 (18-82)||0.267|
|AFP (ng/ml)||39.5 (1-530600)||76 (1-1111200)||0.378|
|ICG retention at 15min (%)||10.05 (1.2-53.1)||10.3 (1.6-52.7)||0.718|
|Blood loss (L)||0.8 (0.01-10.0)||0.6 (0.01-15.0)||0.007|
|Tumour size (cm)||5 (0.7-22.0)||5 (1.0-23.0)||0.538|
|No of tumour||1 (1-multiple)||1 (1-multiple)||0.755|
|Presence of microvascular invasion||104 (49.3%)||198 (46.9%)||0.574|
|Follow up duration (months)||46.9 (3.2-267.5)||58.8 (1.2-335.7)||0.045|
[Demographic data of patients in CM group and WM group]
|OBB-10 ||Can Peri-operative Lactate Kinetics Predict Liver Failure Following Major Liver Resection?
Bobby VM Dasari, United Kingdom
J. Alderman1, A. Owen1, N. Murphy1, J. Hodson2, K.J. Roberts3, M. Abradelo3, D.F. Mirza3, P. Muiesan3, B.V. Dasari3
1Critical Care Unit, Queen Elizabeth Hospital, United Kingdom, 2University of Birmingham, United Kingdom, 3HPB and Liver Transplantation Unit, Queen Elizabeth Hospital, United Kingdom
Introduction: Evidence from sepsis literature, and growing evidence in trauma suggest hyperlactataemia is prognostic of poor outcome. Some evidence suggests a similar relationship following liver resection.The current study is aimed at assessing the relationship between lactate kinetics and post hepatectomy liver failure
Methods: A dataset was collated of up
to 50 sequential serum lactate concentrations in all patients who underwent major hepatic resection from 2015-2019. Lactate values were taken from the start of surgery. Data were analysed using 'R'
(R-Studio v1.2.5001). Values were split into 24h epochs, and means were compared
using Mann-Whitney U tests.
Results: A total of 1275 patients were included (58.4% male). Scatterplots
with best fit lines (generalised additive model) of lactate concentration
against time were produced and were compared between subgroups (Figure 1). For
patients undergoing major liver resection, postoperative day 1-3 lactate was significantly elevated in those who developed PHLF(A-C) compared to those with no PHLF (Table 1) and
subsequent kinetic profile was different.
Conclusion: These data suggest that early and sustained hyperlactatemia
may predict subsequent PHLF. We plan further analysis to characterise individual patients' lactate trajectories via machine learning, using this data to build and ratify a model predicting patients' risk of PHLF and other adverse outcomes based on their lactate dynamics and other factors influencing the post hepatic resection outcomes.
| ||No PHLF
(mmol/L)||No PHLF vs PHLF A-C||PHLF C
(mmol/L)||No PHLF vs PHLF C|
|Day 1 mean peak lactate||3.44||4.67||p<0.00001||5.424||p<0.00001|
|Day 2 mean peak lactate||2.69||4.92||p<0.00001||5.68||p<0.00001|
|Day 3 mean peak lactate||2.04||2.86||p<0.00001||3.70||p<0.00001|