Independent Predictor Of Early Recurrence Research Articles

Efficiency evaluation of dual-energy CT to predict the postoperative early recurrence of pancreatic ductal adenocarcinoma

ObjectivesTo evaluate the efficacy of quantitative parameters from dual-energy CT (DECT) and basic CT features in predicting the postoperative early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC). MethodsIn this study, patients with PDAC who underwent radical resection and DECT from 2018 to 2022 were enrolled and categorised into ER and non-ER groups. The clinical data, basic CT features and DECT parameters of all patients were analyzed. Independent predictors of ER were identified with Logistic regression analyses. Three models (model A: basic CT features; model B: DECT parameters; model C: basic CT features + DECT parameters) were established. Receiver operating characteristic curve analysis was utilized to evaluate predictive performance. ResultsA total of 150 patients were enrolled (ER group: n = 63; non-ER group: n = 87). Rim enhancement (odds ratio [OR], 3.32), peripancreatic strands appearance (OR, 2.68), electron density in the pancreatic parenchymal phase (P-Rho; OR, 0.90), arterial enhancement fraction (AEF; OR, 0.05) and pancreatic parenchyma fat fraction in the delayed phase (OR, 1.25) were identified as independent predictors of ER. Model C showed the highest area under the curve of 0.898. In addition, the corresponding ER risk factors were identified separately for resectable and borderline resectable PDAC subgroups. ConclusionsDECT quantitative parameters allow for the noninvasive prediction of postoperative ER in patients with PDAC, and the combination of DECT parameters and basic CT features shows a high prediction efficiency. Our model can help to identify patients with high-risk factors to guide preoperative decision making.

556. PREDICTORS OF EARLY RECURRENCE AFTER OESOPHAGECTOMY AND NEOADJUVANT FLOT

Abstract Background FLOT, a novel type of perioperative chemotherapy, has led to improved survival after surgery for oesophageal adenocarcinoma. Yet, rates of cancer recurrence remain high. There is limited research on predictors for early recurrence (ER) in patients receiving FLOT. The aim of this study was to investigate ER and survival rates and identify risk factors of ER. Methods Patients who underwent neoadjuvant FLOT and oesophagectomy for oesophageal and oesophagogastric junction adenocarcinomas at a single high-volume centre between August 2018 and January 2023 were evaluated for ER, defined as disease present within one year of surgery. Multivariable logistic regression was conducted to identify risk factors for ER. Patients who died in-hospital or within 90 days of surgery and those with positive longitudinal margin were excluded. Results 145 patients were included. 139 (95.9%) and 63 (43.4%) patients fully completed neoadjuvant and adjuvant FLOT. 44 patients (30.3%) developed recurrence and 22 patients (15.2%) had ER in the follow up period. Distant, local or mixed type of recurrence was found in 32, 6 and 6 patients respectively. The estimated recurrence free survival and overall survival at one, two and three years were 81.4%, 66.9%, 52.0% and 89.0%, 73.7%, 65.5% respectively. The estimated median survival after recurrence was 4.9 months. In multivariable analysis ypN3 status was identified to be an independent predictor of ER (OR 13.769, 95%CI 1.358-139.573, p=0.026). Conclusions This study confirms that ER after neoadjuvant FLOT is common. Patients with a high pathological nodal stage are particularly at risk. It is possible that some patients with ER might have undetected metastases prior to surgery and some do not respond well to neoadjuvant treatment. Identifying chemotherapy non-responders is an important area for future research. These results might be beneficial for prognostication and tailoring follow up care, such as regular surveillance imaging, treatment, and frequency of reviews.

Tumor Apparent Diffusion Coefficient is Associated with Early Recurrence of Intrahepatic Cholangiocarcinoma

Rationale and ObjectivesIdentifying intrahepatic cholangiocarcinoma (iCCA) patients who are at high risk for early recurrence (ER) can guide personalized treatment strategy and improve survival. This study aimed to investigate the value of preoperative MRI, especially diffusion-weighted imaging, in predicting ER, including in patients receiving neoadjuvant therapy. Materials and methodsThis study included 175 pathologically-confirmed iCCA patients who underwent curative resection (114 men, 61 women; mean age 59.0±9.56 years). MRI features, particularly apparent diffusion coefficient (ADC), were analyzed and compared between ER and non-ER cases. Survival analyses of ER were evaluated using Cox regression and Kaplan-Meier analysis. ResultsER occurred in 54.3% (95/175) of patients. Multivariate logistic regression analysis identified tumor ADC as the only independent predictor of ER (odds ratio=0.034, P<0.001), with AUCs of 0.758 (95%CI 0.664, 0.836) in the testing cohort and 0.779 (95%CI 0.622, 0.893) in the validation cohort. The optimal ADC threshold was 1.273×10-3mm2/s. Tumor ADC was comparable to the AJCC 8th staging system in predicting ER (AUC 0.758 vs 0.650 in testing cohort and 0.779 vs 0.661 in validation cohort). Multivariate Cox analysis identified high tumor burden score (HR=1.109, P=0.009), non-smooth margin (HR=2.265, P=0.008) and tumor ADC (HR=0.111, P<0.001) as independent risk factors for ER. Lower ADC values were linked to shorter RFS in both testing and validation cohorts (P<0.001 and 0.0219), as well as in patients receiving neoadjuvant therapy (P=0.003). ConclusionPreoperative MRI, particularly ADC, can help predict ER in iCCA, regardless of the application of neoadjuvant therapy, comparable to the AJCC 8th staging system.

Preoperative CT features for characterization of vessels that encapsulate tumor clusters in hepatocellular carcinoma

PurposeTo explore the capability of preoperative CT imaging features, in combination with clinical indicators, for predicting vessels that encapsulate tumor clusters (VETC) pattern and prognosis in hepatocellular carcinoma (HCC). Materials and methodsFrom January 2015 to May 2022, patients with HCC who underwent curative resection and preoperative enhanced CT were retrospectively included. Clinical indicators and imaging featuresassociated with the VETC pattern were determined by logistic regression analyses. The early recurrence (ER) rate was determined using the Kaplan-Meier survival curve. Factors associated with ER after surgical resection were identified by Cox regression analyses. ResultA total of 243 patients with HCCwere evaluated. The total bilirubin > 17.1 μmol/L (odds ratio [OR] 3.43, 95 % Confidence Interval [CI] 1.70, 6.91, p = 0.001), serum α-fetoprotein > 100 ng/mL (OR 2.41, 95 % CI 1.25, 4.67, p = 0.009), intratumor artery (IA) (OR 2.00, 95 % CI 1.04, 3.86,p = 0.039) and arterial peritumoral enhancement (OR 2.60, 95 % CI 1.13, 5.96, p = 0.025) were independent risk factors for VETC+–HCC. The VETC+status andCT feature ofIA were associated with an increased risk of recurrence, with a shorter median RFS, compared to those without these factors (p < 0.001 and p = 0.019, respectively). In multivariable Cox regression analysis, the VETC+(hazard ratio [HR] 2.60, 95 % CI 1.66, 4.09, p < 0.001), morphological patterns of confluent multinodular growth (HR 1.79, 95 % CI 1.10, 2.91,p = 0.019), the number of the tumors (≥2) (HR 2.69, 95 % CI 1.56, 4.65, p < 0.001), and the IA (HR 1.73, 95 % CI 1.12, 2.66, p = 0.013) were independent predictors of ER in patients with HCC after surgical resection. ConclusionPreoperative CT features combined with clinical indicators could predict VETC pattern, and the CT features, along with VETC status, were of prognostic significance for early postoperative recurrence in patients with HCC. Clinical Relevance StatementPreoperative CT features combined with clinical indicators could predict VETC pattern, and the CT features, along with VETC status, were of prognostic significance for early recurrence in patients with HCC after surgical resection.

Characteristics of Abdominal Fat Based on CT Measurements to Predict Early Recurrence After Initial Surgery of NMIBC in Stage Ta/T1

IntroductionThis study aimed to assess the predictive value of abdominal fat characteristics measured by computed tomography (CT) in identifying early recurrence within one year post-initial transurethral resection of bladder tumor (TURBT) in patients with nonmuscle-invasive bladder cancer (NMIBC). A predictive model integrating fat features and clinical factors was developed to guide individualized treatment. Materials and MethodsA retrospective analysis of 203 NMIBC patients from two medical centers was conducted. Abdominal CT images were analyzed using 3D Slicer software. Spearman correlation, logistic regression, and the Lasso algorithm were employed for data analysis. Predictive efficacy was assessed using the area under the curve (AUC) of receiver operating characteristic (ROC) and decision curve analysis (DCA). Calibration was evaluated using the Hosmer-Lemeshow test. ResultsSignificant differences in abdominal fat characteristics were found between the recurrence and nonrecurrence groups. All fat features positively correlated with body mass index (BMI), with bilateral perirenal fat thickness (PrFT) showing superior predictive performance. Multivariate logistic regression identified independent predictors of early recurrence, including tumor number, early perfusion chemotherapy, left and right PrFT, and visceral fat area (VFA) at umbilical and renal hilum levels. The Lasso-based model achieved an AUC of 0.904, outperforming existing models. ConclusionAbdominal fat characteristics, especially bilateral PrFT, strongly correlate with early recurrence in NMIBC. The Lasso-based model, integrating fat and clinical factors, offers superior predictive efficacy and could improve individualized treatment strategies.

Preoperative prediction of microvascular invasion: new insights into personalized therapy for early-stage hepatocellular carcinoma.

Owing to advances in diagnosis and treatment methods over past decades, a growing number of early-stage hepatocellular carcinoma (HCC) diagnoses has enabled a greater of proportion of patients to receive curative treatment. However, a high risk of early recurrence and poor prognosis remain major challenges in HCC therapy. Microvascular invasion (MVI) has been demonstrated to be an essential independent predictor of early recurrence after curative therapy. Currently, biopsy is not generally recommended before treatment to evaluate MVI in HCC according clinical guidelines due to sampling error and the high risk of tumor cell seeding following biopsy. Therefore, the postoperative histopathological examination is recognized as the gold standard of MVI diagnosis, but this lagging indicator greatly impedes clinicians in selecting the optimal effective treatment for prognosis. As imaging can now noninvasively and completely assess the whole tumor and host situation, it is playing an increasingly important role in the preoperative assessment of MVI. Therefore, imaging criteria for MVI diagnosis would be highly desirable for optimizing individualized therapeutic decision-making and achieving a better prognosis. In this review, we summarize the emerging image characteristics of different imaging modalities for predicting MVI. We also discuss whether advances in imaging technique have generated evidence that could be practice-changing and whether advanced imaging techniques will revolutionize therapeutic decision-making of early-stage HCC.

Delta-radiomics Analysis Based on Multi-phase Contrast-enhanced MRI to Predict Early Recurrence in Hepatocellular Carcinoma After Percutaneous Thermal Ablation

Rationale and ObjectivesIt is critical to predict early recurrence (ER) after percutaneous thermal ablation (PTA) for hepatocellular carcinoma (HCC). We aimed to develop and validate a delta-radiomics nomogram based on multi-phase contrast-enhanced magnetic resonance imaging (MRI) to preoperatively predict ER of HCC after PTA. Materials and MethodsWe retrospectively enrolled 164 patients with HCC and divided them into training, temporal validation, and other-scanner validation cohorts (n=110, 29, and 25, respectively). The volumes of interest of the intratumoral and/or peritumoral regions were delineated on preoperative multi-phase MR images. Original radiomics features were extracted from each phase, and delta-radiomics features were calculated. Logistic regression was used to train the corresponding radiomics models. The clinical and radiological characteristics were evaluated and combined to establish a clinical-radiological model. A fusion model comprising the best radiomics scores and clinical-radiological risk factors was constructed and presented as a nomogram. The performance of each model was evaluated and recurrence-free survival (RFS) was assessed. ResultsChild-Pugh grade B, high-risk tumor location, and an incomplete/absent tumor capsule were independent predictors of ER. The optimal radiomics model comprised 12 delta-radiomics features with areas under the curve (AUCs) of 0.834, 0.795, and 0.769 in the training, temporal validation, and other-scanner validation cohorts, respectively. The nomogram showed the best predictive performance with AUCs as 0.893, 0.854, and 0.827 in the three datasets. There was a statistically significant difference in RFS between the risk groups calculated using the delta-radiomics model and nomogram. ConclusionsThe nomogram combined with the delta-radiomic score and clinical-radiological risk factors could non-invasively predict ER of HCC after PTA.

Serum high-density lipoprotein cholesterol levels predict early recurrence and prognosis of intrahepatic cholangiocarcinoma after surgical resection

IntroductionDysregulation in lipid metabolism contributes to the occurrence and development of various cancers. The connection between changes in lipid metabolism and the development of intrahepatic cholangiocarcinoma remains uncertain. Our objective was to investigate the significance of blood lipid levels in patients with intrahepatic cholangiocarcinoma who have undergone surgery. MethodsNinety-seven ICC patients who underwent surgery were retrospectively enrolled. After 92.2 months of follow-up, the Kaplan-Meier analysis and Cox proportional hazard model were used to calculate overall survival and recurrence-free survival. ResultsThe median age of this cohort was 56 years, and 79 (81.4 %) of them were male. Eighty-eight (90.7 %) patients presented with tumor recurrence and 73 (75.3 %) died. In multivariate analyses, high-density lipoprotein cholesterol level (<0.91 vs. ≥ 0.91 mmol/L, hazard ratio [HR] = 2.55; 95 % CI: 1.38–4.71), lymph node metastasis (Yes vs. No, HR = 2.58; 95 % CI: 1.28–5.19), etiology factor (chronic HBV infection vs. others, HR = 0.5; 95 % CI: 0.28–0.88) and multiple tumor lesions (Yes vs. No, HR = 1.85; 95 % CI: 1.01–3.39) were independent predictors of overall survival. However, only high-density lipoprotein cholesterol level (HR = 1.86; 95 % CI: 1.19–2.92) emerged as the independent factor for recurrence-free survival. High-density lipoprotein cholesterol level (HR = 2.07; 95 % CI: 1.26–3.41), etiology factor (HR = 0.49; 95 % CI: 0.29–0.84), and multiple tumor lesions (HR = 2.00; 95 % CI: 1.14–3.51) were independent predictors of early recurrence. For patients who did not experience the spread of cancer to the lymph nodes, there was a significant correlation between the level of high-density lipoprotein cholesterol and their overall survival, recurrence-free survival, and early recurrence. For patients with low pre-operation high-density lipoprotein cholesterol levels, high post-operation high-density lipoprotein cholesterol levels were associated with better prognosis. ConclusionsLow serum high-density lipoprotein cholesterol level might serve as a sign of poor clinical outcomes (overall survival and recurrence-free survival) and early recurrence among intrahepatic cholangiocarcinoma patients. Strengthening the monitoring and intervention of intrahepatic cholangiocarcinoma patients with poor prognosis might be critical for improving the prognosis.

Very Early Recurrence After Curative Resection for Pancreatic Ductal Adenocarcinoma: Proof of Concept for a "Biological R2 Definition".

Very early recurrence after radical surgery for pancreatic ductal adenocarcinoma (PDAC) has been poorly investigated. This study was designed to evaluate this group of patients who developed recurrence, within 12 weeks after surgery, defined as "biological R2 resections (bR2)." Data from patients who underwent surgical resection as upfront procedure or after neoadjuvant treatment for PDAC between 2015 and 2019 were analyzed. Disease-free, disease-specific survival, and independent predictors of early recurrence were examined. The same analysis was performed separately for upfront and neoadjuvant treated patients. Of the 573 patients included in the study, 63 (11%) were classified as bR2. The rate of neoadjuvant treatment was similar in bR2 and in the remaining patients (44 vs. 42%, p = 0.78). After a median follow-up of 27 months, median DFS and DSS for the entire cohort were 17 and 43 months, respectively. Median DSS of bR2 group was 13 months. The only preoperative identifiable independent predictor of very early recurrence was body-tail site lesion, whereas all other were pathological: higher pT (8th classification), G3 differentiation, and high lymph node ratio. These predictors were confirmed for patients undergoing upfront surgery, whereas in the neoadjuvant group the only independent predictor was pT. One of ten patients with "radical" resected PDAC relapses very early after surgery (bR2); hence, imaging must be routinely repeated within 12 weeks. Despite higher biological aggressiveness and worse pathology, this bR2 cluster eludes our preoperative examinations.

Long-term outcomes and early recurrence after resection for metachronous pulmonary metastases from colorectal cancer.

Properly selecting patients for aggressive curative resection for pulmonary metastases (PMs) from colorectal cancer (CRC) is desirable. We purposed to clarify prognostic factors and risk factors for early recurrence after metachronous PM resection. Clinical data of 151 patients who underwent R0 resection for metachronous PMs from CRC at two institutions between 2008 and 2021 were reviewed. Seventy-six patients (50.3%) were male, and the median age was 71 (42-91) years. The numbers of colon/rectal cancers were 76/75, with pStage I/II/III/IV/unknown in 15/34/86/13/3. The duration from primary surgery to PM was 19.7 (1.0-106.4) months. The follow-up period was 41.9 (0.3-156.2) months. The 1-, 3-, and 5-year recurrence-free survival (RFS) rates were 75.1%, 53.7%, and 51.1%, and the 1-, 3-, and 5-year overall survival (OS) rates were 97.7%, 87.5%, and 68.2%. On multivariate analysis, lymph node metastasis of the primary lesion (HR 1.683, 95%CI 1.003-2.824, p = 0.049) was an independent predictor of poor RFS, and history of resection for extrapulmonary metastasis (e-PM) (HR 2.328, 95%CI 1.139-4.761, p = 0.021) was an independent predictor of poor OS. Patients who experienced early recurrence (< 6months) after PM resection showed poorer OS than others (3-year OS 50.8% vs. 90.2%, p = 0.002). On multivariate analysis, e-PM was an independent predictor of early recurrence after PM resection (OR 3.989, 95%CI 1.002-15.885, p = 0.049). Since a history of e-PM was a predictor of early recurrence and poor OS after R0 resection for PM, surgical treatment of patients with a history of e-PM should be considered carefully.

Increased Plasmatic Levels of Exosomes Are Significantly Related to Relapse Rate in Patients with Oral Squamous Cell Carcinoma: A Cohort Study

Background: Oral squamous cell carcinoma (OSCC) is characterized by an immunosuppressive tumor microenvironment. Their plasma-derived exosomes deliver immunomodulatory molecules and cargo that correlate significantly with clinical parameters. This study aims to assess the exosomal profile as a potential tool for early detection of relapse and long-term outcomes in OSCC patients undergoing conventional therapy. Methods: 27 OSCC patients with a median 38-month follow-up were included in this study. The relationship between NTA-derived parameters and clinical pathological parameters was examined, and receiver operating characteristic (ROC) curves were utilized to evaluate the diagnostic efficacy of these values in detecting cancer relapse. Results: Plasmatic levels of exosomes prior to surgery showed a drastic reduction after surgical intervention (8.08E vs. 1.41 × 109 particles/mL, p = 0.006). Postsurgical concentrations of exosomes were higher in patients who experienced relapse compared to those who remained disease-free (2.97 × 109 vs. 1.11 × 109 particles/mL, p = 0.046). Additionally, patients who relapsed exhibited larger exosome sizes after surgery (141.47 vs. 132.31 nm, p = 0.03). Patients with lower concentrations of exosomes prior to surgery demonstrated better disease-free survival compared to those with higher levels (p = 0.012). ROC analysis revealed an area under the curve of 0.82 for presurgical exosome concentration in identifying relapse. Conclusions: Presurgical exosomal plasmatic levels serve as independent predictors of early recurrence and survival in OSCC. All in all, our findings indicate that the detection of peripheral exosomes represents a novel tool for the clinical management of OSCC, with potential implications for prognosis assessment.

Development and External Validation of a Nomogram Including Body Composition Parameters for Predicting Early Recurrence of Hepatocellular Carcinoma After Hepatectomy

Body composition, including adipose and muscle tissues, evaluated by computer tomography is correlated with the prognosis of hepatocellular carcinoma (HCC). However, its relationship with early recurrence (ER) remains unclear. This study aimed at establishing and validating a nomogram based on body composition and clinicopathological indices to predict ER of HCC. One hundred ninety-five patients from institution A formed the training cohort and internal validation cohort, and 50 patients from institution B formed the external validation cohort. Independent predictors of ER were identified using LASSO and Cox regression analyses. The performance of nomogram was evaluated using the calibration curve, concordance index (C-index), area under the curve (AUC), and decision curve analysis (DCA). After data screening, the nomogram was constructed using eight independent predictors of ER, including the tumor size, alpha fetoprotein, body mass index, Edmondson Steiner grade, visceral adipose tissue radiodensity, intermuscular adipose tissue index, intramuscular adipose tissue content, and skeletal muscle area. The calibration curve exhibited excellent concordances, with C-indices of 0.808 (95%CI: 0.771-0.860), 0.802 (95%CI: 0.747-0.942), and 0.804 (95%CI: 0.701-0.861) in training, internal validation, and external validation cohorts, respectively. In addition, compared to conventional staging systems and pure clinical model, the nomogram exhibited a higher AUC and wider range of threshold probabilities in DCA, which indicated better discriminative ability and greater clinical benefit. Finally, patients with nomogram scores of <183.07, 183.07-243.09, and >243.09 were considered to have low, moderate, and high risks of ER, respectively. The nomogram exhibits excellent ER predictive ability for patients with HCC who underwent hepatectomy.

The significance of countable and treatable metastatic liver disease in patients with gallbladder carcinoma after curative-intent surgery: A 10-year experience in China.

Our study was performed to evaluate the significance of countable and treatable metastatic liver disease (CTMLD) in patients with gallbladder carcinoma (GBC) after curative-intent surgery. Resected GBC patients between September 2010 and January 2021 were reviewed. Comparative analyses between patients with CTMLD and those without it were performed. A propensity score matching analysis was conducted for further validation. A total of 326 resected GBC patients were identified (33 with CTMLD). A significantly higher preoperative CA199 level was detected in those with CTMLD (p = 0.0160). Significantly higher incidences of major hepatectomy (p = 0.0010), lymph node metastasis (p < 0.0001), direct liver invasion (p < 0.0001), moderate to poor differentiation status (p < 0.0001), and T3-4 disease (p < 0.0001) were detected in patients with CTMLD. Even sharing comparable surgical margin status, patients with CTMLD still shared a significantly higher recurrence rate (93.9% vs. 57.3%, p < 0.0001) as well as a significantly higher recurrence rate within 6 months after surgery (63.6% vs. 14.7%, p < 0.0001). A significantly worse overall survival (median survival time: 12 vs. 33 months, p < 0.0001) or disease-free survival (median recurrence-free time: 6 vs. 30 months, p < 0.0001) was acquired in patients with CTMLD. After matching, a significantly higher early recurrence rate was still detected. Adjuvant chemotherapy seemed to have survival benefit for patients with CTMLD. CTMLD was an indicator of advanced disease and served as an independent predictor of early recurrence among resected GBC patients. Whether curative-intent surgery is superior to nonsurgical treatment among GBC patients with CTMLD remains to be explored in future prospective studies.

Novel online calculator to predict reduced risk of early recurrence from adjuvant transarterial chemoembolisation for patients with hepatocellular carcinoma

BackgroundThe role of adjuvant transarterial chemoembolisation (TACE) to reduce postoperative recurrence varies widely among patients undergoing hepatectomy with curative intent for hepatocellular carcinoma (HCC). Personalised predictive tool to select which...

A new scoring system with simple preoperative parameters as predictors of early recurrence of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) often recurs early after radical resection, and such early recurrence (ER) is associated with a poor prognosis. Predicting ER is useful for determining the optimal treatment. One hundred fifty-three patients who underwent pancreatectomy for PDAC were divided into an ER group (n = 54) and non-ER group (n = 99). Clinicopathological factors were compared between the groups, and the predictors of ER and prognosis after PDAC resection were examined. The ER group had a higher platelet count, higher platelet-to-lymphocyte ratio (PLR), higher preoperative CA19-9 concentration, higher SPan-1 concentration, larger tumor diameter, and more lymph node metastasis. The receiver operating characteristic (ROC) curve analysis identified cut-off values for PLR, carbohydrate antigen 19-9 (CA19-9), SPan-1, and tumor diameter. In the multivariate analysis, a high PLR, high CA19-9, and tumor diameter of >3.1 cm were independent predictors of ER after resection (all p < 0.05). When the parameter exceeded the cut-off level, 1 point was given, and the total score of the three factors was defined as the ER prediction score. Next, our new ER prediction model using PLR, CA19-9 and tumor diameter (Logit(p) = 1.6 + 1.2 × high PLR + 0.7 × high CA19-9 + 0.5 × tumor diameter > 3.1cm) distinguished ER with an area under the curve of 0.763, a sensitivity of 85.2%, and a specificity of 55.6%. ER after resection of PDAC can be predicted by calculation of a score using the preoperative serum CA19-9 concentration, PLR, and tumor diameter.

The significance of peri-neural invasion in patients with gallbladder carcinoma after curative surgery: a 10year experience in China.

The significance of peri-neural invasion (PNI) in patients with gallbladder carcinoma (GBC) after curative surgery remains unknown. Current study was performed to evaluate the significance of PNI in resected GBC patients in terms of tumor-related biological features and long-term survival. Patients with GBC between September 2010 and September 2020 were reviewed and analyzed. SPSS 25.0 software were used for statistical analysis. A total of 324 resected GBC patients were identified (No. PNI: 64). An elevated preoperative Ca19.9 level (P = 0.001), obstructive jaundice (P = 0.001), liver invasion (P < 0.0001), lymph-vascular invasion (P < 0.0001), lymph-node metastasis (P < 0.0001), and poor or moderate differentiation status (P = 0.036) were more frequently detected in patients with PNI. Major hepatectomy (P = 0.019), bile duct resection (P < 0.0001), combined multi-visceral resections (P = 0.001), and combined major vascular resections and reconstructions (P = 0.002) were also more frequently detected. However, a significantly lower R0 rate (P < 0.0001) was acquired in patients with PNI. Patients with PNI were generally more advanced disease and shared a much worse prognosis even after matching. PNI was an independent prognostic factor of disease-free survival as well as an independent predictor of early recurrence. Postoperative adjuvant chemotherapy has brought an obvious survival benefit in resected GBC patients with PNI. PNI could be regarded as an indicator of worse prognosis and could serve as an independent predictor of early recurrence. Postoperative adjuvant chemotherapy was correlated with an improved survival for resected GBC patients with PNI. Upcoming multicenter studies covering various races are warranted for further validation.

Preoperative prediction of macrotrabecular-massive hepatocellular carcinoma through dynamic contrast-enhanced magnetic resonance imaging-based radiomics.

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is closely related to aggressive phenotype, gene mutation, carcinogenic pathway, and immunohistochemical markers and is a strong independent predictor of early recurrence and poor prognosis. With the development of imaging technology, successful applications of contrast-enhanced magnetic resonance imaging (MRI) have been reported in identifying the MTM-HCC subtype. Radiomics, as an objective and beneficial method for tumour evaluation, is used to convert medical images into high-throughput quantification features that greatly push the development of precision medicine. To establish and verify a nomogram for preoperatively identifying MTM-HCC by comparing different machine learning algorithms. This retrospective study enrolled 232 (training set, 162; test set, 70) hepatocellular carcinoma patients from April 2018 to September 2021. A total of 3111 radiomics features were extracted from dynamic contrast-enhanced MRI, followed by dimension reduction of these features. Logistic regression (LR), K-nearest neighbour (KNN), Bayes, Tree, and support vector machine (SVM) algorithms were used to select the best radiomics signature. We used the relative standard deviation (RSD) and bootstrap methods to quantify the stability of these five algorithms. The algorithm with the lowest RSD represented the best stability, and it was used to construct the best radiomics model. Multivariable logistic analysis was used to select the useful clinical and radiological features, and different predictive models were established. Finally, the predictive performances of the different models were assessed by evaluating the area under the curve (AUC). The RSD values based on LR, KNN, Bayes, Tree, and SVM were 3.8%, 8.6%, 4.3%, 17.7%, and 17.4%, respectively. Therefore, the LR machine learning algorithm was selected to construct the best radiomics signature, which performed well with AUCs of 0.766 and 0.739 in the training and test sets, respectively. In the multivariable analysis, age [odds ratio (OR) = 0.956, P = 0.034], alpha-fetoprotein (OR = 10.066, P < 0.001), tumour size (OR = 3.316, P = 0.002), tumour-to-liver apparent diffusion coefficient (ADC) ratio (OR = 0.156, P = 0.037), and radiomics score (OR = 2.923, P < 0.001) were independent predictors of MTM-HCC. Among the different models, the predictive performances of the clinical-radiomics model and radiological-radiomics model were significantly improved compared to those of the clinical model (AUCs: 0.888 vs 0.836, P = 0.046) and radiological model (AUCs: 0.796 vs 0.688, P = 0.012), respectively, in the training set, highlighting the improved predictive performance of radiomics. The nomogram performed best, with AUCs of 0.896 and 0.805 in the training and test sets, respectively. The nomogram containing radiomics, age, alpha-fetoprotein, tumour size, and tumour-to-liver ADC ratio revealed excellent predictive ability in preoperatively identifying the MTM-HCC subtype.

A novel combined carbohydrate antigen 19-9 and lymphocyte-to-monocyte ratio score can predict early recurrence of resectable pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) often recurs early after radical resection, which causes a poor prognosis. This study aimed to establish a scoring model to assess the optimal treatment in patients who underwent surgery for PDAC. This single-center retrospective study included 127 patients who underwent radical resection for PDAC between 2005 and 2021. Early recurrence (ER) was defined as recurrence within 12months after resection. The predictive effect for ER was evaluated using receiver operating characteristic (ROC) curves of preoperative parameters. ER occurred in 43 (33.9%) patients. The ER group had a significantly worse prognosis than the non-ER group (p < 0.0001). The carbohydrate antigen 19-9 (CA19-9) level and lymphocyte-to-monocyte ratio (LMR) were the strongest diagnostic factors (areas under the ROC curves: 0.74 and 0.68, respectively). The ER prediction score was calculated using optimal cutoff values. A higher CA19-9-LMR score was associated with a worse prognosis in terms of the overall and recurrence-free survival (p = 0.0017 and p < 0.0001, respectively). A multivariate analysis identified a high CA19-9-LMR score as an independent predictor of ER. The CA19-9-LMR scoring model can predict ER after surgery and is applicable for risk stratification in the assessment of patients with resectable PDAC.

Research progress of radiomics in the evaluation of microvascular invasion in hepatocellular carcinoma

Microvascular invasion (MVI) is an independent predictor of early recurrence and poor prognosis following hepatocellular carcinoma (HCC) resection and transplantation. As a novel non-invasive diagnostic tool, radiomics can extract the quantitative imaging features of tumors and peritumoral tissues with high throughput, providing more information on tumor heterogeneity than conventional and functional imaging of visual analysis and having a good application prospect in predicting the presence of MVI in HCC patients, thereby improving the accuracy of HCC diagnosis and prognosis. The value of the multimodal radiomics method based on various imaging methods in evaluating the possibility of MVI in HCC patients is elucidated here in combination with the latest research progress.

A model incorporating histopathology and preoperative gadoxetic acid-enhanced MRI to predict early recurrence of hepatocellular carcinoma without microvascular invasion after curative hepatectomy.

To assess the predictive value of preoperative gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) features and postoperative histopathological grading for early recurrence of hepatocellular carcinoma (HCC) without microvascular invasion (MVI) after curative hepatectomy. A total of 85 MVI-negative HCC cases were retrospectively analyzed. Cox analyses were used to identify the independent predictors of early recurrence (within a 24 months span). The clinical prediction Model-1 or Model-2 was established without or with postoperative pathological factor, respectively. Nomogram models were constructed and receiver operating characteristic (ROC) curve analysis was used to assess the models' predictive ability. Internal validation of the prediction models for early HCC recurrence was performed using a bootstrap re-sampling approach. In the multivariate cox regression analysis, Edmondson-Steiner grade, peritumoral hypointensity on hepatobiliary phase (HBP), and relative intensity ratio (RIR) in HBP were identified as independent variables associated with early recurrence. The C-index of the nomogram models and internal validation were both between 0.7 and 0.8, showing good model fitting and calibration effects. The area under the ROC curve (AUC) was 0.781 for Model-1 based on the two preoperative MRI factors. When a third factor, the Edmondson-Steiner grade, was included (Model-2), the AUC increased to 0.834, and the sensitivity increased from 71.4 to 96.4%. Edmondson-Steiner grade, peritumoral hypointensity on HBP, and RIR on HBP can help predict early recurrence of MVI-negative HCC. In comparison with Model-1 (only imaging features), Model-2 (imaging features + histopathological grades) increases the sensitivity in predicting early recurrence of HCC without MVI. Preoperative GA-enhanced MRI signs are of great value in predicting early postoperative recurrence of HCC without MVI, and a combined pathological model was established to evaluate the feasibility and effectiveness of this technique.