Resection Of Colorectal Liver Metastases Research Articles

Impact of the Inflammatory Burden Index on Prognosis After Hepatectomy for Colorectal Liver Metastasis.

The aim of this study was to investigate the prognostic impact of the inflammatory burden index (IBI), a novel inflammation-based biomarker, in patients with colorectal liver metastases (CRLM) after hepatic resection. One hundred fifty patients with CRLM who underwent hepatectomy were retrospectively analyzed. The IBI was defined as C-reactive protein × neutrophil count/lymphocyte count. The relationship of the IBI with overall survival was investigated by univariate and multivariate analyses. Seventy-three (49%) patients had a high IBI (>3.45). In univariate analysis, overall survival was significantly worse in patients with lymph node metastases (P = 0.048), high NLR (P = 0.03), and high IBI (P < 0.01). In multivariate analysis, high IBI (P = 0.048) was an independent and significant predictor of overall survival. Patients with a high IBI had more postoperative complications compared with those with a low IBI (P < 0.01). The IBI was a strong predictor for both short- and long-term outcomes in patients who underwent hepatic resection for CRLM.

The impact of neoadjuvant therapy on the prognostic value of preoperative neutrophil-to-lymphocyte ratio for colorectal liver metastases: a multi-center cohort study

BackgroundNeutrophil-to-lymphocyte ratio (NLR) is a promising prognostic marker for patients undergoing hepatectomy for colorectal liver metastases (CRLM). However, its prognostic value in patients receiving neoadjuvant therapy (NAT) has not been sufficiently addressed.MethodsFrom 2013 to 2023, a cohort of 692 patients with CRLM receiving hepatectomy were enrolled in five centers. Clinicopathological characteristics were obtained from a prospectively maintained multi-center database. The effect of NLR (> 2 versus ≤ 2) on overall survival (OS) and recurrence-free survival was estimated by Kaplan–Meier analysis. Univariable and multivariable Cox regression analysis was applied to investigate the influence of individual clinicopathological parameters on OS.ResultsIn the entire cohort, the median NLR level was 2.11 (0.30–16.33). There were 307 (44.4%) patients receiving NAT followed by hepatectomy, while 385 (55.6%) patients undergoing upfront surgery. Notably, patients in the NAT group showed significantly lower NLR level than those in the upfront surgery group (1.83 versus 2.32, P < 0.001). In the upfront surgery group, high NLR was significantly associated with worse OS, independent of other factors (HR = 1.49, 95% CI 1.08–2.05, P = 0.02). In the NAT group, there was no significant difference in OS between the high NLR and low NLR group.ConclusionThe prognostic value of NLR in surgically resected CRLM is potentially influenced by NAT in the modern era.

Human collagen type I‑based scaffold retains human‑derived fibroblasts in a patient‑derived tumor xenograft mouse model.

The present study aimed to investigate the role of a recombinant protein based on human collagen type I (RCPhC1) as a scaffold in maintaining the human tumor microenvironment within a patient-derived tumor xenograft (PDTX) model. RCPhC1, synthesized under animal component-free conditions, was explored for its potential to support the human-specific stroma associated with tumor growth. PDTX models were established using resected colorectal cancer liver metastasis specimens, and stromal cell populations from humans and mice were compared using three scaffolds: No scaffold (control), Matrigel and recombinant human collagen type I, across two passages. Specific antibodies for human Lamin B and mouse Lamin B were used for immunostaining to distinguish between human and mouse cells. Additionally, the impact of each scaffold on the invasive ability of mouse fibroblasts was assessed using an invasion assay. Patient-derived tumor tissues embedded with RCPhC1 hydrogels had significantly more human Lamin B-positive cells and fewer mouse Lamin B cells than those embedded with no scaffolds or Matrigel. The human Lamin B-positive cells in PDTX tumors with RCPhC1 hydrogels were recognized as fibroblasts. Additionally, these hydrogels significantly reduced the invasion of mouse fibroblast cell lines in vitro compared with Matrigel. The present study investigated RCPhC1 hydrogels as a new scaffold material for tumor engraftment in PDTX mouse models, and identified a promising experimental tool for maintaining the tumor microenvironment.

Robotic Subtotal Caudate Lobe Hepatic Resection for Paracaval Colorectal Metastasis: Technique of Inferior Vena Cava Dissection and Handling.

Minimally invasive technique for surgical management of colorectal metastasis is becoming the standard practice in the United States. Paracaval colorectal metastasis is a technically challenging tumor to resect due to its location.1-4 Abutment of the inferior vena cava (IVC) often requires advanced technique for vascular dissection and potential need for partial venous resection. The authors describe their technique of robotic subtotal caudate lobe resection for paracaval tumor requiring tangential IVC resection. A 76-year-old man after partial nonanatomic liver resection of colorectal metastases in segments 2, 4, and 8 presented with a new paracaval caudate tumor. A positron emission tomography (PET) scan showed a 3-cm FDG avid tumor with a standard uptake value (SUV) of 8.3 without extrahepatic metastasis. After a diagnostic laparoscopy, subtotal caudate lobe resection was undertaken. Short hepatic veins were divided to fully mobilize the Spiegel and paracaval portion. Liver transection was performed along the right side of the IVC. Upon the final IVC dissection, vascular abutment by the dorsal aspect of the tumor was encountered. Meticulous vascular dissection, performed with partial tangential IVC resection, was completed to gain complete tumor resection. The operation time was 3.5h, with 100ml of blood loss. The postoperative course was uneventful, and the patient was discharged home on postoperative day 2. The pathology results showed a moderately differentiated metastatic adenocarcinoma (3.8 × 3 × 1.8 cm) with a histologically negative vascular margin. The patient currently is 2 years from the operation without recurrence of disease. The authors describe a safe and feasible technique of robotic subtotal caudate lobe hepatic resection with partial IVC resection, which can be useful to practicing hepatobiliary surgeons.

Initial experience of parenchyma-sparing liver resection with systematic selective hepatic vein reconstruction for colorectal metastases

ObjectivesThis study aims to assess the feasibility and short-term and intermediate-term technical success rate of the concept of systematic selective hepatic vein (HV) reconstruction for parenchyma-sparing hepatectomies (PSHs) in patients...

Textbook Outcomes and Quality of Life Assessment Following Liver Resection for Colorectal Metastasis.

It is unknown if textbook outcomes (TBOs) correlate with patient-reported health-related quality of life (HRQoL) parameters in patients undergoing hepatic resection for colorectal liver metastasises. Understanding this relationship is required to inform treatment decisions and optimise patient care. This single-centre analysis aims to assess this correlation and provide insight into the impact of liver resection on patient well-being in this population. Single-centre analysis of all liver resections performed for colorectal liver metastases (CRLM) at our centre from 2018 to 2023. The EuroQol-5D (EQ-5D) validated telephone questionnaire was used to assess HRQoL. The impact of a TBO on overall survival and recurrence-free survival was investigated using Kaplan-Meier curve analysis. A Cox model was used to determine factors associated with improved survival. 185 patients underwent liver resection for CRLM between 2018 and 2023. 55% of eligible patients completed the EQ-5D telephone questionnaire. TBOs were achieved in 68.2% of CRLM at our institution. Achieving TBOs in this cohort was associated with improved HRQoL (p = 0.061). This study demonstrates excellent long-term HRQoL in patients who undergo resection for CRLM. Achieving TBO in this cohort is associated with improved patient-reported HRQoL. Our findings strengthen the utility of the previously defined textbook outcomes in CRLM.

The Effect of Health Insurance on Racial Disparities in Patients With Isolated Colorectal Liver Metastases.

Although resection of colorectal liver metastases (CRLM) improves survival, factors including race and health insurance are associated with disparities in care. The aim of this study was to evaluate the effect of health insurance on racial disparities in CRLM resection. A retrospective study of patients with CRC with synchronous CRLM was performed using the National Cancer Database (2004-2020). The primary outcome was resection liver resection. Multivariable logistic regression (MVR) was performed to evaluate the association of race and insurance with the odds of resection. Forty-four thousand and six hundred sixteen patients were included. Resection rates were lower among Blacks compared to White patients (12.9% vs. 17.3%). By MVR, Black patients (OR 0.76 vs. White), uninsured and Medicaid-insured patients (OR 0.49 and OR 0.71 vs. private insurance) were less likely to undergo resection. On MVR of race stratified by insurance, Black patients with private and Medicare insurance had decreased odds of resection compared to White (OR 0.71 and OR 0.64). Although Black patients with CRLM have lower odds of hepatic resection compared to White, when stratified by insurance, this was only present among private- and Medicare-insured. Further investigation is warranted to understand other factors associated with racial disparities in this population.

Patterns and predictors of recurrence after curative resection of colorectal liver metastasis (CRLM)

Patterns and predictors of recurrence after curative resection of colorectal liver metastasis (CRLM)

A comparison of clinical risk scores for survival prediction after curative-intent resection of colorectal liver metastases.

A comparison of clinical risk scores for survival prediction after curative-intent resection of colorectal liver metastases.

Spleen hypertrophy predicts liver-specific complications in patients undergoing major liver resection for colorectal liver metastases, after preoperative chemotherapy.

Spleen hypertrophy predicts liver-specific complications in patients undergoing major liver resection for colorectal liver metastases, after preoperative chemotherapy.

Preoperative sarcopenia at the T4 vertebral level predicts postoperative major complications in patients undergoing major liver resection for colorectal metastases.

Preoperative sarcopenia at the T4 vertebral level predicts postoperative major complications in patients undergoing major liver resection for colorectal metastases.

Strategies for Recurrent Colorectal Liver Metastases Based on Prognostic Factors and Resectability: Potential Benefit of Multidisciplinary Treatment.

Colorectal liver metastasis (CLM) is classified into technical and oncologic categories, with recommended treatments for each resectability category. However, the classification of recurrent CLM has not been established to date. This study evaluated patients with CLM who underwent initial liver resection between 2006 and 2020 and subsequently experienced liver recurrence. Long-term outcomes and prognostic factors associated with recurrent CLM were investigated. From 949 patients who underwent an initial liver resection, the analysis included 392 patients with liver recurrence. Repeat liver resection was associated with a significantly longer prognosis than non-resection (5-year overall survival [OS] from initial liver resection: 66.3 % vs 27.2 %, p < 0.0001). Multivariable analysis indicated the following independent prognostic factors: four or more recurrent tumors (p = 0.015), tumor 5 cm or larger in size (p = 0.004), and presence of extrahepatic diseases (p = 0.003). The patients were stratified into resectable, borderline resectable, and unresectable recurrent CLM groups based on these criteria. The prognosis varied significantly across the groups, with 5-year OS rates of 67.3 % for resectable recurrent CLM, 30.8 % for borderline resectable recurrent CLM, and 2.6 % for unresectable recurrent CLM (p < 0.0001). Patients with borderline resectable recurrent CLM who did not receive adjuvant chemotherapy after initial liver resection had a positive prognostic impact of preoperative chemotherapy (p = 0.049). The significant independent predictors of recurrent CLM prognosis were four or more tumors, tumor size of 5 cm or larger, and the presence of extrahepatic diseases at recurrence. It is critical to onsider the current condition and tumor resectability at the time of recurrence, and tailored treatments could further improve recurrent CLM outcomes.

Recurrence Timing and Risk Following Curative Resection of Colorectal Liver Metastases: Insights From a Hazard Function Analysis.

There is no consensus on the optimal surveillance interval for patients undergoing resection of colorectal liver metastases (CRLM). We sought to assess the timing and intensity of recurrence following curative-intent resection of CRLM utilizing a recurrence-free survival (RFS) hazard function analysis. Patients with CRLM who underwent curative-intent resection were identified from a multi-institutional database. The RFS hazard function was used to plot hazard rates and identify the peak of recurrence over time. Among 1804 patients, the median RFS was 19.9 months. In the analytic cohort, the RFS hazard curve peaked at 5.9 months (peak hazard rate: 0.054) and gradually declined, indicative of early recurrence. In subgroup analyses, patients with high and medium tumor burden scores (TBS) had RFS hazard peaks at 4.9 months (peak hazard rate: 0.060) and 5.8 months (peak hazard rate: 0.054), respectively. In contrast, patients with low TBS had a later peak at 7.5 months, with the lowest peak hazard rate of 0.047. The recurrence peak for CRLM patients occurred approximately 6 months postsurgery, highlighting the need for intensified early postoperative surveillance. Patients with high TBS experienced earlier recurrence, underscoring the importance of close monitoring, particularly during the first 6 months after surgery.

Pushing boundaries: simultaneous minimal-invasive resection of complex colorectal liver metastases and its primary tumor.

Synchronous liver metastases occur in approximately 15-20% of patients with colorectal cancer. Optimal oncological treatment of oligometastatic disease combines surgical resection and systemic therapy. Open simultaneous resection of the primary and liver metastases is well described, but there is not much evidence for the increasing use of the minimally invasive approach. We here report the results of our experience of simultaneous minimally invasive resections. A prospective database of patients with resection of colorectal liver metastases (CRLM) at the Charité - Universitätsmedizin Berlin was used for retrospective data analysis. We report all patients undergoing simultaneous minimal invasive resection of colorectal cancer and its synchronous liver metastases between May 2015 and December 2021. Out of 281 patients undergoing resection of CRLM, 33 (11.7%) patients had simultaneous minimal invasive resection of the colorectal primary. The primary tumor was located mostly within the rectum (n = 17; 48.6%), followed by the descending colon (n = 6; 17.1%). CRLM were localized in both liver lobes in 69.7% (n = 23) of cases. Following resection of the colorectal tumor, an anastomosis was performed in 31 of 33 patients (93.9%), with no anastomotic leakage observed in the follow up. Simultaneous liver resections were performed mostly as subsegment (n = 20) or bisegment resections (n = 11). Mean IWATE-Score of all hepatic resections was 5.5 (± 2.4). Complication rates (Clavien-Dindo ≥ 3) were similar compared between low/intermediate and advanced/expert difficulty for liver resection (n = 4, 17.4% vs. n = 2, 20.0%; p = 1.0). In one case conversion to open resection was required. Our data indicate that simultaneous minimal invasive resection of CRLM and the primary tumor is a safe and feasible procedure. Complication rates were consistent across different levels of difficulty (low to expert) in liver resections. Therefore, indications for simultaneous resection may be expanded.

HPB SO72 - Predicting Major Intra-operative Blood Loss in Patients undergoing Liver Resection: A Machine Learning Radiomics Analysis Using Pre-Operative Liver CTs

Abstract Background Liver resection offers the best opportunity for curing patients with colorectal metastases and is an important treatment option for patients with hepatocellular carcinoma. However, it can be associated with significant morbidity and mortality, with one of the primary reasons being due to intra-operative blood loss which serves as an important predictor of post-operative outcomes. Predicting blood loss pre-operatively would be a powerful tool for clinicians in identifying higher risk patients. In this study, we examine whether radiomic features of the liver can predict major blood loss (&amp;gt;500 mls) alongside clinical and morphometric features in patients undergoing resection for colorectal metastases. Method Patient data was extracted from a prospectively maintained database of individuals undergoing resection for colorectal liver metastases (CRLMs). Radiomic features were extracted from pre-operative portal venous phase CTs. The background liver was randomly segmented in a two-dimensional plane away from cancer areas. Highly correlated features were dropped, and further feature selection techniques applied. Nested cross validation was performed to train and evaluate the machine learning models with the selected radiomic, clinical, and morphometric features. Results Radiomic features (159) were extracted from 106 patients, and 10 radiomic features comprised of first order and texture features, 3 morphometric, and 4 clinical features were selected for the machine learning models. The models demonstrated a robust ability to discriminate between major and minor blood loss. The best performing machine learning model demonstrated an AUC of 0.76 (95% CI 0.7-0.82). Other performance metrics for this model included a mean accuracy of 0.78 and an F1 Score of 0.87 on the validation data. Conclusion Pre-operative CT radiomic, clinical, and morphometric features have shown a modest ability to predict major intra-operative blood loss in patients undergoing hepatic resection for colorectal liver metastases. Further work is needed to validate and refine these models to improve performance. Additionally, we plan to incorporate data from other centres to validate our findings in further experiments to create a robust tool to guide surgical practice in this patient cohort.

HPB O06 - A computer tomography-based radiomics signature predicts overall survival following curative resection of colorectal liver metastasis: A multicentre, retrospective study

Abstract Background Colorectal cancer liver metastasis (CRLM) has a heterogeneous outcome and improved prognostic biomarkers are needed to aid patient-tailored management. Here, we assess the value of Computer Tomography (CT)-guided radiomics in the prognostication of post-resection CRLM using data from two large tertiary referral centres in the UK. Method Patient data was extracted from prospectively maintained databases of patients undergoing CRLM resection at two centres. CRLM and regions of interest from background normal liver were segmented. Radiomics features were extracted from portal venous phase CT images using open-source software. Feature selection techniques were applied. Machine learning models incorporating radiomic or clinical features, and their combination, were developed and assessed for mortality prediction at fixed time points. Cox proportional hazard regression was utilised for risk score generation to classify patients as high or low-risk for overall survival estimation. The models were evaluated on unseen testing data. Results Radiomics features (269) were generated from 959 metastases in 399 patients across the two sites. Models with combined clinical and radiomic features performed similarly to those with radiomic features alone, and often outperformed models with clinical features alone demonstrating good discrimination and risk prediction at 2 and 3 years. The computed radiomic scores allowed us to generate Kaplan–Meier curves which showed CRLM patients in the high-risk group had a lower overall survival vs the low-risk group(p&amp;lt;0.05). This risk-score independently predicted mortality in our multivariate Cox proportional-hazards model. Conclusion We demonstrate a robust combination of CT-based radiomics features can predict CRLM outcomes across two different hospital sites. Our radiomic risk-scores predicts overall survival and can prognosticate patients into high and low risk groups. These findings support the prognostic utility of CT-based radiomics in patients undergoing resection of CRLM and provide rationale for further investigation in a prospective, multi-centre setting.

Classifying histopathological growth patterns for resected colorectal liver metastasis with a deep learning analysis.

Histopathological growth patterns are one of the strongest prognostic factors in patients with resected colorectal liver metastases. Development of an efficient, objective and ideally automated histopathological growth pattern scoring method can substantially help the implementation of histopathological growth pattern assessment in daily practice and research. This study aimed to develop and validate a deep-learning algorithm, namely neural image compression, to distinguish desmoplastic from non-desmoplastic histopathological growth patterns of colorectal liver metastases based on digital haematoxylin and eosin-stained slides. The algorithm was developed using digitalized whole-slide images obtained in a single-centre (Erasmus MC Cancer Institute, the Netherlands) cohort of patients who underwent first curative intent resection for colorectal liver metastases between January 2000 and February 2019. External validation was performed on whole-slide images of patients resected between October 2004 and December 2017 in another institution (Radboud University Medical Center, the Netherlands). The outcomes of interest were the automated classification of dichotomous hepatic growth patterns, distinguishing between desmoplastic hepatic growth pattern and non-desmoplatic growth pattern by a deep-learning model; secondary outcome was the correlation of these classifications with overall survival in the histopathology manual-assessed histopathological growth pattern and those assessed using neural image compression. Nine hundred and thirty-two patients, corresponding to 3.641 whole-slide images, were reviewed to develop the algorithm and 870 whole-slide images were used for external validation. Median follow-up for the development and the validation cohorts was 43 and 29 months respectively. The neural image compression approach achieved significant discriminatory power to classify 100% desmoplastic histopathological growth pattern with an area under the curve of 0.93 in the development cohort and 0.95 upon external validation. Both the histopathology manual-scored histopathological growth pattern and neural image compression-classified histopathological growth pattern achieved a similar multivariable hazard ratio for desmoplastic versus non-desmoplastic growth pattern in the development cohort (histopathology manual score: 0.63 versus neural image compression: 0.64) and in the validation cohort (histopathology manual score: 0.40 versus neural image compression: 0.48). The neural image compression approach is suitable for pathology-based classification tasks of colorectal liver metastases.

Liver Resection With Extrahepatic Disease: A Population-Based Analysis of Thoughtful Selection.

The oncologic benefit of liver resection for colorectal liver metastases (CRLM) in the setting of concurrent extrahepatic disease (EHD) is controversial. We performed a population-based, cross-sectional study to determine the practice patterns and overall survival (OS) of patients with CRLM + EHD who underwent liver resection. Patients with CRLM + EHD were identified using the California Cancer Registry from 2000 to 2019. Records were linked to the Office of Statewide Health Planning Inpatient Database. Patient demographics, clinical characteristics, and survival were compared between CRLM + EHD patients with and without liver resection. Of 170 978 patients with CRLM, 62 003 (36%) had concurrent EHD (CRLM + EHD). In all, 3736 (6%) of CRLM + EHD underwent liver resection compared to 22% of patients with liver limited CRLM. Compared to CRLM + EHD without liver resection, CRLM + EHD with resection were younger, had fewer comorbidities, received higher frequencies of perioperative chemotherapy, and were more likely to have only a single site of EHD rather than multiple sites. Median OS was significantly higher for CRLM + EHD with resection compared to without (52 vs. 27 months, HR 0.46 [95% CI 0.44-0.47], p < 0.001). Regarding the location of EHD, this survival benefit was observed with liver resection for lung, peritoneal, intraabdominal lymph nodes, ovarian, and bone metastases. In a large population-based setting, subsets of CRLM + EHD patients that undergo liver resection are associated with prolonged survival. These results support surgery with thoughtful patient selection to optimize survival outcomes in this population.

Resection of colorectal liver metastases with second-line aflibercept plus FOLFIRI: Results from the RESECTION prospective French cohort

AimTo evaluate R0/R1 resection rate in patients with colorectal liver metastases (CLM) treated with aflibercept plus FOLFIRI after failure of a prior oxaliplatin-based regimen in daily clinical practice. MethodsThis French, multicentre, prospective, observational cohort (NCT05178745) included patients with CLM (alone or predominant; up to 5 lung nodules <2 cm allowed) initiating aflibercept plus FOLFIRI every 2 weeks per physician choice. Primary endpoint was R0/R1 resection rate. Secondary endpoints included overall survival (OS), progression-free survival (PFS), radiological and pathological responses, and safety. ResultsA total of 137 patients (median age 65 years, RAS/BRAF mutant 57 %/9 %) were enrolled at 22 French sites. CLM (median 4) were synchronous in 82 %, bilobar in 71 % and located in liver only in 54 %. Overall, 17 % of patients had R0/R1 resection (21 % for patients with liver-only disease). A major pathological response per Blazer score was observed in 55 % of resected patients, along with significantly longer OS (median 34.8 vs 9.1 months, p < 0.0001) and PFS (median 11.4 vs 4.9 months, p < 0.0001) compared to non-resected patients. Post-operative complications occurred in 17 % of patients (all Dindo-Clavien grade I-II) and there was no post-operative deaths. Overall, 34 % had grade ≥ 3 adverse events, mainly general health deterioration and diarrhea. ConclusionsResults suggest that aflibercept plus FOLFIRI, after failure of a prior oxaliplatin-based regimen, allows R0/R1 resection of CLM in almost 20 % of patients with a major pathological response in most cases and a median OS prolonged by more than 3-fold versus non-resected patients.

Preoperative identification of early extrahepatic recurrence after hepatectomy for colorectal liver metastases: A machine learning approach.

Machine learning (ML) may provide novel insights into data patterns and improve model prediction accuracy. The current study sought to develop and validate an ML model to predict early extra-hepatic recurrence (EEHR) among patients undergoing resection of colorectal liver metastasis (CRLM). Patients with CRLM who underwent curative-intent resection between 2000 and 2020 were identified from an international multi-institutional database. An eXtreme gradient boosting (XGBoost) model was developed to estimate the risk of EEHR, defined as extrahepatic recurrence within 12months after hepatectomy, using clinicopathological factors. The relative importance of factors was determined using Shapley additive explanations (SHAP) values. Among 1410 patients undergoing curative-intent resection, 131 (9.3%) patients experienced EEHR. Median OS among patients with and without EEHR was 35.4months (interquartile range [IQR] 29.9-46.7) versus 120.5months (IQR 97.2-134.0), respectively (p<0.001). The ML predictive model had c-index values of 0.77 (95% CI, 0.72-0.81) and 0.77 (95% CI, 0.73-0.80) in the entire dataset and the validation data set with bootstrapping resamples, respectively. The SHAP algorithm demonstrated that T and N primary tumor categories, as well as tumor burden score were the three most important predictors of EEHR. An easy-to-use risk calculator for EEHR was developed and made available online at: https://junkawashima.shinyapps.io/EEHR/. An easy-to-use online calculator was developed using ML to help clinicians predict the chance of EEHR after curative-intent resection for CRLM. This tool may help clinicians in decision-making related to treatment strategies for patients with CRLM.