MRI-based nomogram estimates the risk of recurrence of primary nonmetastatic pancreatic neuroendocrine tumors after curative resection

Correlation of MRI characteristics with KRAS mutation status in pancreatic ductal adenocarcinoma

PURPOSE

To investigate MRI features associated with KRAS mutation status in PDAC and their clinical implications.

MATERIALS AND METHODS

In our study, 1474 patients pathologically confirmed PDAC patients between January 2016 and December 2023 were evaluated. Patients with genetic testing (KRAS mutation status) and MRI examination were enrolled and grouped as KRAS-mutated PDAC and non-KRAS-mutated PDAC. Contrast-enhanced MRI features, clinicopathologic findings, and prognosis were compared between two groups.

RESULTS

A total of 308 surgically confirmed PDAC patients (median age, 67 years [IQR, 59, 72]; 183 male and 125 female) with genetic testing data were included, of which 258 had KRAS-mutated PDAC and 50 had non-KRAS-mutated PDAC. KRAS-mutated PDAC demonstrated distinct clinicopathological characteristics, including higher rates of diabetes (OR, 2.450, 95% CI, 1.151-5.212, P = 0.020), pathological peripheral nerve infiltration (OR, 2.296, 95% CI, 1.083-4.867, P = 0.030), and pN stage (OR, 2.006, 95% CI, 1.012-3.976, P = 0.046). The 1-, 3-, 5-year OS rate was worse for KRAS-mutated PDAC (89.9%, 45.4%, 23.2% vs. 95.1%, 60.4% 60.4%, P = 0.045). Rim enhancement (OR = 2.039, 95% CI: 1.053, 3.951, P = 0.035) and larger tumor size (OR = 3.286, 95% CI: 1.523, 7.089, P = 0.002) were identified as distinctive MRI features for KRAS-mutated PDAC.

CONCLUSION

KRAS-mutated PDAC presents unique clinical and pathological features and is associated with poorer prognosis. Rim enhancement and larger tumor size on MRI were identified as features associated with KRAS-mutated PDAC.

Identification of SMAD4-mutated pancreatic ductal adenocarcinoma using preoperative contrast-enhanced MRI and clinical characteristics

AIM

To assess the value of preoperatively contrast-enhanced MRI and clinical characteristics for identification of SMAD4-mutated pancreatic ductal adenocarcinoma (PDAC) patients.

MATERIALS AND METHODS

This retrospective study included patients with surgically confirmed PDAC from January 2016 to December 2022. Based on immunostaining results indicating the mutation of SMAD4, the enrolled participants were grouped into SMAD4-mutated PDAC and non-SMAD4-mutated PDAC. Contrast-enhanced MRI findings, clinical-pathological characteristics, and prognosis were recorded and reviewed. The pathological findings and clinical prognosis were compared between the two groups. Uni- and multivariable logistic regression analyses were further performed to determine the radiological and clinical predictive factors for the mutation of SMAD4.

RESULTS

In total, 428 PDAC patients were enrolled and analyzed, who were grouped as SMAD4-mutated PDAC (n = 224) and non-SMAD4-mutated PDAC (n = 204). SMAD4-mutated PDAC demonstrated higher frequency of pathological fatty infiltration (83.4% vs. 74.2%, P = 0.016), peripheral nerve infiltration (84.4% vs. 76.5%, P = 0.039). and higher recurrence rates (43.6% vs. 58.9%, P = 0.045) than non-SMAD4-mutated PDAC. The 3-year recurrence-free survival rates were worse for SMAD4-mutated PDAC (28.7% vs. 39.1%). In multivariable logistic regression analyses, CA19-9 > 100 U/mL (odds ratio [OR] = 1.519, P = 0.041), CBD dilation (OR = 1.564, P = 0.036), and rim enhancement (OR = 1.631, P = 0.025) were independent predictive factors.

CONCLUSION

Rim enhancement, CBD dilation on contrast-enhanced MRI and higher CA19-9 level are promising radiological and clinical factors for identifying SMAD4-mutated PDAC.

Epidemiology and Prognostic Nomogram for Predicting Long-Term Disease-Specific Survival in Patients With Pancreatic Carcinoid Tumor: A SEER-Based Study

OBJECTIVES

Pancreatic carcinoid tumor (PCT) is described as a malignant form of carcinoid tumors. However, the epidemiology and prognostic factors for PCT are poorly understood.

MATERIALS AND METHODS

The data of 2447 PCT patients were included in this study from the Surveillance, Epidemiology, and End Results database and randomly divided into a training cohort (1959) and a validation cohort (488). The epidemiology of PCT was calculated, and independent prognostic factors were identified to construct a prognostic nomogram for predicting long-term disease-specific survival (DSS) among PCT patients.

RESULTS

The incidence of PCT increased remarkably from 2000 to 2018. The 1-, 5-, and 10-year DSS rates were 96.4%, 90.3%, and 86.5%, respectively. Age at diagnosis, stage, surgery, radiotherapy, and chemotherapy were identified as independent prognostic factors to construct a prognostic nomogram. The C -indices; area under the receiver operating characteristic curves for predicting 1-, 5-, and 10-year DSS, and calibration plots of the nomogram in both cohorts indicated a high discriminatory accuracy, preferable survival predictive ability, and optimal concordances, respectively.

CONCLUSIONS

The incidence of PCT has increased rapidly since 2000. In addition, we established a practical, effective, and accurate prognostic nomogram for predicting the long-term DSS of PCT patients.

A dynamic nomogram to predict invasive fungal super-infection during healthcare-associated bacterial infection in intensive care unit patients: an ambispective cohort study in China

Objectives

Invasive fungal super-infection (IFSI) is an added diagnostic and therapeutic dilemma. We aimed to develop and assess a nomogram of IFSI in patients with healthcare-associated bacterial infection (HABI).

Methods

An ambispective cohort study was conducted in ICU patients with HABI from a tertiary hospital of China. Predictors of IFSI were selected by both the least absolute shrinkage and selection operator (LASSO) method and the two-way stepwise method. The predictive performance of two models built by logistic regression was internal-validated and compared. Then external validity was assessed and a web-based nomogram was deployed.

Results

Between Jan 1, 2019 and June 30, 2023, 12,305 patients with HABI were screened in 14 ICUs, of whom 372 (3.0%) developed IFSI. Among the fungal strains causing IFSI, the most common was C.albicans (34.7%) with a decreasing proportion, followed by C.tropicalis (30.9%), A.fumigatus (13.9%) and C.glabrata (10.1%) with increasing proportions year by year. Compared with LASSO-model that included five predictors (combination of priority antimicrobials, immunosuppressant, MDRO, aCCI and S.aureus), the discriminability of stepwise-model was improved by 6.8% after adding two more predictors of COVID-19 and microbiological test before antibiotics use (P<0.01).And the stepwise-model showed similar discriminability in the derivation (the area under curve, AUC=0.87) and external validation cohorts (AUC=0.84, P=0.46). No significant gaps existed between the proportion of actual diagnosed IFSI and the frequency of IFSI predicted by both two models in derivation cohort and by stepwise-model in external validation cohort (P=0.16, 0.30 and 0.35, respectively).

Conclusion

The incidence of IFSI in ICU patients with HABI appeared to be a temporal rising, and our externally validated nomogram will facilitate the development of targeted and timely prevention and control measures based on specific risks of IFSI.

Prediction of the lymphatic, microvascular, and perineural invasion of pancreatic neuroendocrine tumors using preoperative magnetic resonance imaging

BACKGROUND

Significant correlation between lymphatic, microvascular, and perineural invasion (LMPI) and the prognosis of pancreatic neuroendocrine tumors (PENTs) was confirmed by previous studies. There was no previous study reported the relationship between magnetic resonance imaging (MRI) parameters and LMPI.

AIM

To determine the feasibility of using preoperative MRI of the pancreas to predict LMPI in patients with non-functioning PENTs (NFPNETs).

METHODS

A total of 61 patients with NFPNETs who underwent MRI scans and lymphadenectomy from May 2011 to June 2018 were included in this retrospective study. The patients were divided into group 1 (n = 34, LMPI negative) and group 2 (n = 27, LMPI positive). The clinical characteristics and qualitative MRI features were collected. In order to predict LMPI status in NF-PNETs, a multivariate logistic regression model was constructed. Diagnostic performance was evaluated by calculating the receiver operator characteristic (ROC) curve with area under ROC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy.

RESULTS

There were significant differences in the lymph node metastasis stage, tumor grade, neuron-specific enolase levels, tumor margin, main pancreatic ductal dilatation, common bile duct dilatation, enhancement pattern, vascular and adjacent tissue involvement, synchronous liver metastases, the long axis of the largest lymph node, the short axis of the largest lymph node, number of the lymph nodes with short axis > 5 or 10 mm, and tumor volume between two groups (P < 0.05). Multivariate analysis showed that tumor margin (odds ratio = 11.523, P < 0.001) was a predictive factor for LMPI of NF-PNETs. The area under the receiver value for the predictive performance of combined predictive factors was 0.855. The sensitivity, specificity, PPV, NPV and accuracy of the model were 48.1% (14/27), 97.1% (33/34), 97.1% (13/14), 70.2% (33/47) and 0.754, respectively.

CONCLUSION

Using preoperative MRI, ill-defined tumor margins can effectively predict LMPI in patients with NF-PNETs.

Clinical Prediction Models for Recurrence in Patients with Resectable Grade 1 and 2 Sporadic Non-Functional Pancreatic Neuroendocrine Tumors: A Systematic Review

Recurrence after resection in patients with non-functional pancreatic neuroendocrine tumors (NF-pNET) has a considerable impact on overall survival. Accurate risk stratification will tailor optimal follow-up strategies. This systematic review assessed available prediction models, including their quality. This systematic review followed PRISMA and CHARMS guidelines. PubMed, Embase, and the Cochrane Library were searched up to December 2022 for studies that developed, updated, or validated prediction models for recurrence in resectable grade 1 or 2 NF-pNET. Studies were critically appraised. After screening 1883 studies, 14 studies with 3583 patients were included: 13 original prediction models and 1 prediction model validation. Four models were developed for preoperative and nine for postoperative use. Six models were presented as scoring systems, five as nomograms, and two as staging systems. The c statistic ranged from 0.67 to 0.94. The most frequently included predictors were tumor grade, tumor size, and lymph node positivity. Critical appraisal deemed all development studies as having a high risk of bias and the validation study as having a low risk of bias. This systematic review identified 13 prediction models for recurrence in resectable NF-pNET with external validations for 3 of them. External validation of prediction models improves their reliability and stimulates use in daily practice.

MRI-based Nomogram Predicts the Risk of Progression of Unresectable Hepatocellular Carcinoma After Combined Lenvatinib and anti-PD-1 Antibody Therapy

RATIONALE AND OBJECTIVES

Combined immune and anti-angiogenic treatment has shown promising results for unresectable hepatocellular carcinoma (HCC), but with a high risk of early progression. In this study, we aimed to investigate whether pre-treatment magnetic resonance imaging (MRI) features and MRI-based nomogram could predict the risk of disease progression of unresectable HCC after first-line lenvatinib/anti-PD-1 antibody therapy.

MATERIALS AND METHODS

Thirty-seven HCC participants with qualified pre-treatment contrast-enhanced MRI were enrolled. All patients received combined lenvatinib and anti-PD-1 antibody treatment. Progression free survival rate was analyzed using the Kaplan-Meier method. Potential clinical-radiological risk factors for progression were analyzed using the log-rank tests and Cox regression model. The performance of MRI-based nomogram was evaluated based on C-index, calibration, and decision curve analyses.

RESULTS

The 6-month and 12-month cumulative progression free survival rates were 59.5% (95% confidence interval (CI), 43.6%-75.4%) and 48.0% (95% CI, 31.7%-64.3%). On multivariate analysis, no or incomplete tumor capsule (hazard ratio (HR) = 15.215 [95% CI 2.707-85.529], p = 0.002), heterogeneous signal on T2-weighted imaging (HR = 28.179 [95% CI 2.437-325.838]; p = 0.008) and arterial contrast-to-noise ratio ≤95.45 (HR = 5.113 [95% CI 1.538-17.00]; p = 0.008) were independent risk factors for disease progression. Satisfactory predictive performance of the nomogram incorporating the three independent imaging features was obtained with a C-index value of 0.880 (95% CI 0.824-0.937), and the combined nomogram had more favorable clinical prediction performance than any single feature.

CONCLUSION

MRI features can be considered effective predictors of disease progression for unresectable HCC with first-line lenvatinib plus anti-PD-1 antibody therapy, and the combined MRI-based nomogram achieved a superior prognostic model, which may help to identify appropriate candidates for the therapy.

Radical Resection in Entero-Pancreatic Neuroendocrine Tumors: Recurrence-Free Survival Rate and Definition of a Risk Score for Recurrence

BACKGROUND

Surgery with radical intent is the only potentially curative option for entero-pancreatic neuroendocrine tumors (EP-NETs) but many patients develop recurrence even after many years. The subset of patients at high risk of disease recurrence has not been clearly defined to date.

OBJECTIVE

The aim of this retrospective study was to define, in a series of completely resected EP-NETs, the recurrence-free survival (RFS) rate and a risk score for disease recurrence.

PATIENTS AND METHODS

This was a multicenter retrospective analysis of sporadic pancreatic NETs (PanNETs) or small intestine NETs (SiNETs) [G1/G2] that underwent R0/R1 surgery (years 2000-2016) with at least a 24-month follow-up. Survival analysis was performed using the Kaplan-Meier method and risk factor analysis was performed using the Cox regression model.

RESULTS

Overall, 441 patients (224 PanNETs and 217 SiNETs) were included, with a median Ki67 of 2% in tumor tissue and 8.2% stage IV disease. Median RFS was 101 months (5-year rate 67.9%). The derived prognostic score defined by multivariable analysis included prognostic parameters, such as TNM stage, lymph node ratio, margin status, and grading. The score distinguished three risk categories with a significantly different RFS (p < 0.01).

CONCLUSIONS

Approximately 30% of patients with EP-NETs recurred within 5 years after radical surgery. Risk factors for recurrence were disease stage, lymph node ratio, margin status, and grading. The definition of risk categories may help in selecting patients who might benefit from adjuvant treatments and more intensive follow-up programs.

Imaging of Pancreatic Neuroendocrine Neoplasms

Pancreatic neuroendocrine neoplasms (panNENs) represent the second most common pancreatic tumors. They are a heterogeneous group of neoplasms with varying clinical expression and biological behavior, from indolent to aggressive ones. PanNENs can be functioning or non-functioning in accordance with their ability or not to produce metabolically active hormones. They are histopathologically classified according to the 2017 World Health Organization (WHO) classification system. Although the final diagnosis of neuroendocrine tumor relies on histologic examination of biopsy or surgical specimens, both morphologic and functional imaging are crucial for patient care. Morphologic imaging with ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) is used for initial evaluation and staging of disease, as well as surveillance and therapy monitoring. Functional imaging techniques with somatostatin receptor scintigraphy (SRS) and positron emission tomography (PET) are used for functional and metabolic assessment that is helpful for therapy management and post-therapeutic re-staging. This article reviews the morphological and functional imaging modalities now available and the imaging features of panNENs. Finally, future imaging challenges, such as radiomics analysis, are illustrated.

The prognostic nomogram including MRI for locally advanced prostate cancer treated by radical prostatectomy

OBJECTIVE

To establish the prognostic nomogram for locally advanced prostate cancer (LAPC) patients treated by radical prostatectomy (RP) based on clinical and multiparametric-MRI (mp-MRI) metrics.

METHODS

One hundred and twenty-one patients diagnosed with LAPC were included in this study. They were all examined by mp-MRI within one week before surgery and treated by RP (36 with RP alone, 48 with neoadjuvant hormonal therapy (NHT) and 37 with neoadjuvant chemohormonal therapy (NCHT)). The biochemical progression-free survival (bPFS) was analyzed by Kaplan-Meier method. Univariate and multivariate analysis were used to determine prognostic factors that were related with bPFS. The prognostic nomogram was established by factors that were significant in multivariate analyses.

RESULTS

The median bPFS had significant difference in the subgroup of treatment (RP alone: 2 [0.00-5.04] vs. NHT: 9.3 [6.746-11.854] vs. NCHT: 11.17 [0.000-25.075] months [Log rank p < .001]), the subgroup of hyperintensity within prostate in DWI (negative: 15.97 [11.202-20.731] vs. positive: 5.2 [2.952-7.448] months [Log rank p < .001]) and the subgroup of pelvic lymph node metastasis (negative: 10.2 [8.404-11.996] vs. unilateral: 4.43 [0.000-11.086] vs. Bilateral: 1.83 [0.636~3.031] [Log rank p < .001]). The method of treatment (hazards ratio [HR], 0.566; 95% confidence interval [CI], 0.356-0.899; p = .016), hyperintensity within prostate in DWI (HR, 2.539; 95% CI, 1.349-4.779; p = .004) and the metastasis burden of pelvic lymph node (HR, 2.492; 95% CI, 1.645-3.777; p < .001) were identified as independent predictors with significance in multivariable Cox regression analysis. The nomogram was established based on these three factors.

CONCLUSION

We established a nomogram based on three significant prognosis factors including the neoadjuvant therapeutic schedule, hyperintensity within prostate in DWI and the metastasis burden of pelvic lymph nodes, which were associated with the clinical outcomes in LAPC patients after surgery.

Diffusion-Weighted MRI Predicts Lymph Node Metastasis and Tumor Aggressiveness in Resectable Pancreatic Neuroendocrine Tumors

OBJECTIVES

The aim of this study was to identify whether diffusion-weighted magnetic resonance imaging (DW-MRI) can predict the malignant behavior of preoperative well-differentiated pancreatic neuroendocrine tumors (PanNETs).

METHOD

Forty patients with PanNETs who underwent pancreatectomy were enrolled in this study. The apparent diffusion coefficient (ADC) values were measured. Clinicopathological factors were compared in patients with high ADC and low ADC values and in patients with and without lymph node metastasis (LNM).

RESULT

The low ADC group was significantly associated with higher Ki-67 index, higher mitotic count, larger tumor size, higher rate of LNM, and venous invasion. In patients with low ADC values, the incidence of LNMs was 33.3%. In patients with high ADC values, there were no patients with LNM being 0%. A significant negative correlation was found between the mean ADC values and the Ki-67 index and between the mean ADC values and the mitotic count. In multivariate analysis, neural invasion and mean ADC values ≤ 1458 were independent predictors of LNM.

CONCLUSION

ADC values obtained using DW-MRI in the preoperative assessment of patients with PanNETs might be a useful predictor of malignant potential, especially LNM.

Prognostic and predictive factors on overall survival and surgical outcomes in pancreatic neuroendocrine tumors: recent advances and controversies

Introduction: Recent advances in diagnostic modalities and therapeutic agents have raised the importance of prognostic factors in predicting overall survival, as well as predictive factors for surgical outcomes, in tailoring therapeutic strategies of patients with pancreatic neuroendocrine neoplasms (panNENs).Areas covered: Numerous recent studies of panNEN patients report the prognostic values of a number of clinically related factors (clinical, laboratory, imaging, treatment-related factors), pathological factors (histological, classification, grading) and molecular factors on long-term survival. In addition, an increasing number of studies showed the usefulness of various factors, specifically biomarkers and molecular makers, in predicting recurrence and mortality related to surgical treatment. Recent findings (from the last 3 years) in each of these areas, as well as recent controversies, are reviewed.Expert commentary: The clinical importance of prognostic and predictive factors for panNENs is markedly increased for both overall outcome and post resection, as a result of recent advances in all aspects of the diagnosis, management and treatment of panNENs. Despite the proven prognostic utility of routinely used tumor grading/classification and staging systems, further studies are required to establish these novel prognostic factors to support their routine clinical use.