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BACKGROUND: Determination of vessel resection in patients with pancreatectomy after neo-adjuvant chemotherapy remains controversial. The recently introduced computed tomography-based vascular burden index presents a potential solution to this challenge. This study aimed to evaluate the model performance for the prediction of vascular resection and pathological invasion. METHODS: Patients who underwent surgery after neo-adjuvant chemotherapy were included. Two independent reviewers measured the vascular tumour burden index around the adjacent artery (AVBI), and vein (VVBI). The area under the curve was compared to assess the predictive capacity of vascular burden index values and their changes for vascular resection and pathological vascular invasion. RESULTS: Among 252 patients, 179 and 73 had borderline resectable and locally advanced pancreatic cancer, respectively. Concurrent vessel resection and pathological vascular invasion were observed in 121 (48.0 %) and 42 (16.6 %) patients, respectively. In all patients, the VVBI (area under the curve: 0.872) and AVBI (0.911) after neo-adjuvant therapy significantly predicted vessel resection. In patients with vascular resection, the VVBI after neo-adjuvant chemotherapy (0.752) and delta value of the AVBI (0.706) demonstrated better performance for predicting pathological invasion of the resected vein. The regression of the AVBI and VVBI was an independent prognostic factor for survival (hazard ratio: 0.54, 95 % confidence interval: 0.34-0.85; P = 0.009) CONCLUSIONS: Regressed VVBI on serial computed tomography scans is useful for predicting vein resection and pathological venous invasion before surgery. The delta value of the AVBI may therefore be helpful for predicting pathological arterial invasion after neo-adjuvant chemotherapy.
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OBJECTIVE: To develop and validate a preoperative risk score incorporating carbohydrate antigen (CA) 19-9, CT, and fluorine-18-fluorodeoxyglucose (18F-FDG) PET/CT variables to predict recurrence-free survival (RFS) after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS: Patients with resectable PDAC who underwent upfront surgery between 2014 and 2017 (development set) or between 2018 and 2019 (test set) were retrospectively evaluated. In the development set, a risk-scoring system was developed using the multivariable Cox proportional hazards model, including variables associated with RFS. In the test set, the performance of the risk score was evaluated using the Harrell C-index and compared with that of the postoperative pathological tumor stage. RESULTS: A total of 529 patients, including 335 (198 male; mean age ± standard deviation, 64 ± 9 years) and 194 (103 male; mean age, 66 ± 9 years) patients in the development and test sets, respectively, were evaluated. The risk score included five variables predicting RFS: tumor size (hazard ratio [HR], 1.29 per 1 cm increment; P < 0.001), maximal standardized uptake values of tumor ≥ 5.2 (HR, 1.29; P = 0.06), suspicious regional lymph nodes (HR, 1.43; P = 0.02), possible distant metastasis on 18F-FDG PET/CT (HR, 2.32; P = 0.03), and CA 19-9 (HR, 1.02 per 100 U/mL increment; P = 0.002). In the test set, the risk score showed good performance in predicting RFS (C-index, 0.61), similar to that of the pathologic tumor stage (C-index, 0.64; P = 0.17). CONCLUSION: The proposed risk score based on preoperative CA 19-9, CT, and 18F-FDG PET/CT variables may have clinical utility in selecting high-risk patients with resectable PDAC.
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Antígeno CA-19-9 , Carcinoma Ductal Pancreático , Fluordesoxiglucose F18 , Neoplasias Pancreáticas , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Compostos Radiofarmacêuticos , Humanos , Masculino , Feminino , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Pessoa de Meia-Idade , Carcinoma Ductal Pancreático/diagnóstico por imagem , Carcinoma Ductal Pancreático/cirurgia , Carcinoma Ductal Pancreático/patologia , Carcinoma Ductal Pancreático/mortalidade , Idoso , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/cirurgia , Neoplasias Pancreáticas/patologia , Neoplasias Pancreáticas/mortalidade , Estudos Retrospectivos , Antígeno CA-19-9/sangue , Tomografia Computadorizada por Raios X/métodos , Recidiva Local de Neoplasia/diagnóstico por imagem , Medição de Risco , Intervalo Livre de Doença , Valor Preditivo dos TestesRESUMO
BACKGROUND AND OBJECTIVES: Pancreatic neuroendocrine tumor (PanNET), although rare in incidence, is increasing in recent years. Several clinicopathologic and molecular factors have been suggested for patient stratification due to the extensive heterogeneity of PanNETs. We aimed to discover the prognostic role of assessing the tumor border of PanNETs with pre-operative computed tomography (CT) images and correlate them with other clinicopathologic factors. METHODS: The radiologic, macroscopic, and microscopic tumor border of 183 surgically resected PanNET cases was evaluated using preoperative CT images (well defined vs. poorly defined), gross images (expansile vs. infiltrative), and hematoxylin and eosin-stained slides (pushing vs. infiltrative). The clinicopathologic and prognostic significance of the tumor border status was compared with other clinicopathologic factors. RESULTS: A poorly defined radiologic tumor border was observed in 65 PanNET cases (35.5 %), and were more frequent in male patients (P = 0.031), and tumor with larger size, infiltrative macroscopic growth pattern, infiltrative microscopic tumor border, higher tumor grade, higher pT category, lymph node metastasis, lymphovascular and perineural invasions (all, P < 0.001). Patients with PanNET with a poorly defined radiologic tumor border had significantly worse overall survival (OS) and recurrence-free survival (RFS; both, P < 0.001). Multivariable analysis revealed that PanNET with a poorly defined radiologic border is an independent poor prognostic factor for both OS (P = 0.049) and RFS (P = 0.027). CONCLUSION: Pre-operative CT-based tumor border evaluation can provide additional information regarding survival and recurrence in patients with PanNET.
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Tumores Neuroendócrinos , Neoplasias Pancreáticas , Tomografia Computadorizada por Raios X , Humanos , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/patologia , Neoplasias Pancreáticas/cirurgia , Masculino , Feminino , Pessoa de Meia-Idade , Tumores Neuroendócrinos/diagnóstico por imagem , Tumores Neuroendócrinos/patologia , Prognóstico , Idoso , Adulto , Estudos Retrospectivos , Idoso de 80 Anos ou mais , Adulto JovemRESUMO
OBJECTIVES: The purpose of this study was to compare the different versions of the National Comprehensive Cancer Network (NCCN) guidelines for defining resectability of pancreatic ductal adenocarcinoma (PDAC) in predicting margin-negative (R0) resection, and to assess inter-reader agreement. METHODS: This retrospective study included 283 patients (mean age, 65.1 years ± 9.4 [SD]; 155 men) who underwent upfront pancreatectomy for PDAC between 2017 and 2019. Two radiologists independently determined the resectability on preoperative CT according to the 2017, 2019, and 2020 NCCN guidelines. The sensitivity and specificity for R0 resection were analyzed using a multivariable logistic regression analysis with generalized estimating equations. Inter-reader agreement was assessed using kappa statistics. RESULTS: R0 resection was accomplished in 239 patients (84.5%). The sensitivity and specificity averaged across two readers were, respectively, 76.6% and 29.5% for the 2020 guidelines, 74.1% and 32.9% for the 2019 guidelines, and 72.6% and 34.1% for the 2017 guidelines. Compared with the 2020 guidelines, both 2019 and 2017 guidelines showed significantly lower sensitivity for R0 resection (p ≤ .009). Specificity was significantly higher with the 2017 guidelines (p = .043) than with the 2020 guidelines. Inter-reader agreements for determining the resectability of PDCA were strong (k ≥ 0.83) with all guidelines, being highest with the 2020 guidelines (k = 0.91). CONCLUSION: The 2020 NCCN guidelines showed significantly higher sensitivity for prediction of R0 resection than the 2017 and 2019 guidelines.
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Carcinoma Ductal Pancreático , Margens de Excisão , Pancreatectomia , Neoplasias Pancreáticas , Guias de Prática Clínica como Assunto , Sensibilidade e Especificidade , Tomografia Computadorizada por Raios X , Humanos , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/cirurgia , Neoplasias Pancreáticas/patologia , Masculino , Feminino , Idoso , Estudos Retrospectivos , Carcinoma Ductal Pancreático/diagnóstico por imagem , Carcinoma Ductal Pancreático/cirurgia , Carcinoma Ductal Pancreático/patologia , Pancreatectomia/métodos , Tomografia Computadorizada por Raios X/métodos , Pessoa de Meia-IdadeRESUMO
Postoperative pancreatic fistula is a life-threatening complication with an unmet need for accurate prediction. This study was aimed to develop preoperative artificial intelligence-based prediction models. Patients who underwent pancreaticoduodenectomy were enrolled and stratified into model development and validation sets by surgery between 2016 and 2017 or in 2018, respectively. Machine learning models based on clinical and body composition data, and deep learning models based on computed tomographic data, were developed, combined by ensemble voting, and final models were selected comparison with earlier model. Among the 1333 participants (training, n = 881; test, n = 452), postoperative pancreatic fistula occurred in 421 (47.8%) and 134 (31.8%) and clinically relevant postoperative pancreatic fistula occurred in 59 (6.7%) and 27 (6.0%) participants in the training and test datasets, respectively. In the test dataset, the area under the receiver operating curve [AUC (95% confidence interval)] of the selected preoperative model for predicting all and clinically relevant postoperative pancreatic fistula was 0.75 (0.71-0.80) and 0.68 (0.58-0.78). The ensemble model showed better predictive performance than the individual ML and DL models.
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Aprendizado Profundo , Fístula Pancreática , Humanos , Fístula Pancreática/diagnóstico , Fístula Pancreática/etiologia , Pancreaticoduodenectomia/efeitos adversos , Inteligência Artificial , Fatores de Risco , Curva ROC , Complicações Pós-Operatórias/etiologiaRESUMO
BACKGROUND: Surgically resected grade 1-2 (G1-2) pancreatic neuroendocrine tumors (PanNETs) exhibit diverse clinical outcomes, highlighting the need for reliable prognostic biomarkers. Our study aimed to develop and validate CT-based radiomics model for predicting postsurgical outcome in patients with G1-2 PanNETs, and to compare its performance with the current clinical staging system. METHODS: This multicenter retrospective study included patients who underwent dynamic CT and subsequent curative resection for G1-2 PanNETs. A radiomics-based model (R-score) for predicting recurrence-free survival (RFS) was developed from a development set (441 patients from one institution) using least absolute shrinkage and selection operator-Cox regression analysis. A clinical model (C-model) consisting of age and tumor stage according to the 8th American Joint Committee on Cancer staging system was built, and an integrative model combining the C-model and the R-score (CR-model) was developed using multivariable Cox regression analysis. Using an external test set (159 patients from another institution), the models' performance for predicting RFS and overall survival (OS) was evaluated using Harrell's C-index. The incremental value of adding the R-score to the C-model was evaluated using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS: The median follow-up periods were 68.3 and 59.7 months in the development and test sets, respectively. In the development set, 58 patients (13.2%) experienced recurrence and 35 (7.9%) died. In the test set, tumors recurred in 14 patients (8.8%) and 12 (7.5%) died. In the test set, the R-score had a C-index of 0.716 for RFS and 0.674 for OS. Compared with the C-model, the CR-model showed higher C-index (RFS, 0.734 vs. 0.662, p = 0.012; OS, 0.781 vs. 0.675, p = 0.043). CR-model also showed improved classification (NRI, 0.330, p < 0.001) and discrimination (IDI, 0.071, p < 0.001) for prediction of 3-year RFS. CONCLUSIONS: Our CR-model outperformed the current clinical staging system in prediction of the prognosis for G1-2 PanNETs and added incremental value for predicting postoperative recurrence. The CR-model enables precise identification of high-risk patients, guiding personalized treatment planning to improve outcomes in surgically resected grade 1-2 PanNETs.
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Tumores Neuroendócrinos , Neoplasias Pancreáticas , Humanos , Prognóstico , Tumores Neuroendócrinos/diagnóstico por imagem , Tumores Neuroendócrinos/cirurgia , Tumores Neuroendócrinos/patologia , Estudos Retrospectivos , Radiômica , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/cirurgia , Tomografia Computadorizada por Raios X/métodosRESUMO
OBJECTIVE: To investigate the imaging characteristics of large duct pancreatic ductal adenocarcinoma (LD-PDAC) on computed tomography (CT) and magnetic resonance imaging (MRI). MATERIALS AND METHODS: Thirty-five patients with LD-PDAC (63.2 ± 9.7 years) were retrospectively evaluated. Tumor morphology on CT and MRI (predominantly solid mass vs. solid mass with prominent cysts vs. predominantly cystic mass) was evaluated. Additionally, the visibility, quantity, shape (oval vs. branching vs. irregular), and MRI signal intensity of neoplastic cysts within the LD-PDAC were investigated. The radiological diagnoses rendered for LD-PDAC in radiology reports were reviewed. RESULTS: LD-PDAC was more commonly observed as a solid mass with prominent cysts (45.7% [16/35] on CT and 37.1% [13/35] on MRI) or a predominantly cystic mass (20.0% [7/35] on CT and 40.0% [14/35] on MRI) and less commonly as a predominantly solid mass on CT (34.3% [12/35]) and MRI (22.9% [8/35]). The tumor morphology on imaging was significantly associated with the size of the cancer gland on histopathological examination (P = 0.020 [CT] and 0.013 [MRI]). Neoplastic cysts were visible in 88.6% (31/35) and 91.4% (32/35) of the LD-PDAC cases on CT and MRI, respectively. The cysts appeared as branching (51.6% [16/35] on CT and 59.4% [19/35] on MRI) or oval shapes (45.2% [14/35] on CT and 31.2% [10/35] on MRI) with fluid-like MRI signal intensity. In the radiology reports, 10 LD-PDAC cases (28.6%) were misinterpreted as diseases other than typical PDAC, particularly intraductal papillary mucinous neoplasms. CONCLUSION: LD-PDAC frequently appears as a solid mass with prominent cysts or as a predominantly cystic mass on CT and MRI. Radiologists should be familiar with the imaging features of LD-PDAC to avoid misdiagnosis.
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Carcinoma Ductal Pancreático , Cistos , Neoplasias Pancreáticas , Humanos , Estudos Retrospectivos , Neoplasias Pancreáticas/patologia , Carcinoma Ductal Pancreático/diagnóstico por imagem , Carcinoma Ductal Pancreático/patologia , Imageamento por Ressonância Magnética/métodos , Tomografia Computadorizada por Raios X/métodos , Neoplasias PancreáticasRESUMO
OBJECTIVES: We aimed to evaluate the prognostic value of tumor-to-parenchymal contrast enhancement ratio on portal venous-phase CT (CER on PVP) and compare its prognostic performance to prevailing grading and staging systems in pancreatic neuroendocrine neoplasms (PanNENs). METHODS: In this retrospective study, data on 465 patients (development cohort) who underwent upfront curative-intent resection for PanNEN were used to assess the performance of CER on PVP and tumor size measured by CT (CT-Size) in predicting recurrence-free survival (RFS) using Harrell's C-index and to determine their optimal cutoffs to stratify RFS using a multi-way partitioning algorithm. External data on 184 patients (test cohort) were used to validate the performance of CER on PVP in predicting RFS and overall survival (OS) and compare its predictive performance with those of CT-Size, 2019 World Health Organization classification system (WHO), and the 8th American Joint Committee on Cancer staging system (AJCC). RESULTS: In the test cohort, CER on PVP showed C-indexes of 0.83 (95% confidence interval [CI], 0.74-0.91) and 0.84 (95% CI, 0.73-0.95) for predicting RFS and OS, respectively, which were higher than those for the WHO (C-index: 0.73 for RFS [p = .002] and 0.72 for OS [p = .004]) and AJCC (C-index, 0.67 for RFS [p = .002] and 0.58 for OS [p = .002]). CT-Size obtained C-indexes of 0.71 for RFS and 0.61 for OS. CONCLUSIONS: CER on PVP showed superior predictive performance on postoperative survival in PanNEN than current grading and staging systems, indicating its potential as a noninvasive preoperative prognostic tool. KEY POINTS: ⢠In pancreatic neuroendocrine neoplasms, the tumor-to-parenchymal enhancement ratio on portal venous-phase CT (CER on PVP) showed acceptable predictive performance of postoperative outcomes. ⢠CER on PVP showed superior predictive performance of postoperative survival over the current WHO classification and AJCC staging system.
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Tumores Neuroendócrinos , Neoplasias Pancreáticas , Humanos , Prognóstico , Estudos Retrospectivos , Tumores Neuroendócrinos/patologia , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/patologia , Tomografia Computadorizada por Raios X , Estadiamento de NeoplasiasRESUMO
Background Deep learning (DL) may facilitate the diagnosis of various pancreatic lesions at imaging. Purpose To develop and validate a DL-based approach for automatic identification of patients with various solid and cystic pancreatic neoplasms at abdominal CT and compare its diagnostic performance with that of radiologists. Materials and Methods In this retrospective study, a three-dimensional nnU-Net-based DL model was trained using the CT data of patients who underwent resection for pancreatic lesions between January 2014 and March 2015 and a subset of patients without pancreatic abnormality who underwent CT in 2014. Performance of the DL-based approach to identify patients with pancreatic lesions was evaluated in a temporally independent cohort (test set 1) and a temporally and spatially independent cohort (test set 2) and was compared with that of two board-certified radiologists. Performance was assessed using receiver operating characteristic analysis. Results The study included 852 patients in the training set (median age, 60 years [range, 19-85 years]; 462 men), 603 patients in test set 1 (median age, 58 years [range, 18-82 years]; 376 men), and 589 patients in test set 2 (median age, 63 years [range, 18-99 years]; 343 men). In test set 1, the DL-based approach had an area under the receiver operating characteristic curve (AUC) of 0.91 (95% CI: 0.89, 0.94) and showed slightly worse performance in test set 2 (AUC, 0.87 [95% CI: 0.84, 0.89]). The DL-based approach showed high sensitivity in identifying patients with solid lesions of any size (98%-100%) or cystic lesions measuring 1.0 cm or larger (92%-93%), which was comparable with the radiologists (95%-100% for solid lesions [P = .51 to P > .99]; 93%-98% for cystic lesions ≥1.0 cm [P = .38 to P > .99]). Conclusion The deep learning-based approach demonstrated high performance in identifying patients with various solid and cystic pancreatic lesions at CT. © RSNA, 2022 Online supplemental material is available for this article.
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Aprendizado Profundo , Cisto Pancreático , Neoplasias Pancreáticas , Masculino , Humanos , Pessoa de Meia-Idade , Estudos Retrospectivos , Neoplasias Pancreáticas/cirurgia , Tomografia Computadorizada por Raios X/métodosRESUMO
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis even after curative resection. A deep learning-based stratification of postoperative survival in the preoperative setting may aid the treatment decisions for improving prognosis. This study was aimed to develop a deep learning model based on preoperative data for predicting postoperative survival. METHODS: The patients who underwent surgery for PDAC between January 2014 and May 2015. Clinical data-based machine learning models and computed tomography (CT) data-based deep learning models were developed separately, and ensemble learning was utilized to combine two models. The primary outcomes were the prediction of 2-year overall survival (OS) and 1-year recurrence-free survival (RFS). The model's performance was measured by area under the receiver operating curve (AUC) and was compared with that of American Joint Committee on Cancer (AJCC) 8th stage. RESULTS: The median OS and RFS were 23 and 10 months in training dataset (n = 229), and 22 and 11 months in test dataset (n = 53), respectively. The AUC of the ensemble model for predicting 2-year OS and 1-year RFS in the test dataset was 0.76 and 0.74, respectively. The performance of the ensemble model was comparable to that of the AJCC in predicting 2-year OS (AUC, 0.67; P = 0.35) and superior to the AJCC in predicting 1-year RFS (AUC, 0.54; P = 0.049). CONCLUSION: Our ensemble model based on routine preoperative variables showed good performance for predicting prognosis for PDAC patients after surgery.
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Carcinoma Ductal Pancreático , Aprendizado Profundo , Neoplasias Pancreáticas , Humanos , Prognóstico , Estudos Retrospectivos , Neoplasias PancreáticasRESUMO
BACKGROUND: Accurate assessment of pancreatic ductal adenocarcinoma (PDAC) resectability after neoadjuvant therapy (NAT) is crucial. Recently, the NCCN introduced criteria for resection of PDAC following NAT. METHODS: We analyzed 127 patients who underwent NAT and pancreatectomy for PDAC between January 2010 and March 2020. CT-determined resectability according to the NCCN guideline and CA 19-9 level was evaluated before and after NAT. Diagnostic performance of the NCCN criteria for margin-negative (R0) resection was investigated and compared with CT alone. RESULTS: R0 resection was achieved in 104 (81.9%) patients. After NAT, there were 30 (23.6%) resectable, 90 (70.9%) borderline resectable, and seven (5.5%) locally advanced tumors. Significantly decreased or stable CA 19-9 levels were noted in 114 (89.8%) patients. The sensitivity and specificity of the NCCN criteria were 87.5% (91/104) and 21.7% (5/23), respectively, which were significantly different from CT including only resectable PDAC (26.9% [28/104] and 91.3% [21/23]; P < .001), but less prominently different from CT including resectable and borderline resectable PDAC (95.2% [99/104]; P = .022 and 8.7% [2/23]; P = .375). CONCLUSIONS: The NCCN criteria for resection following NAT showed high sensitivity and low specificity for predicting R0 resection. It had supplementary benefit over CT alone, mainly in preventing underestimation of R0 resection.
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Carcinoma Ductal Pancreático , Terapia Neoadjuvante , Pancreatectomia , Neoplasias Pancreáticas , Tomografia Computadorizada por Raios X , Carcinoma Ductal Pancreático/diagnóstico por imagem , Carcinoma Ductal Pancreático/cirurgia , Humanos , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/cirurgia , Estudos RetrospectivosRESUMO
BACKGROUND AND AIMS: The accurate differential diagnosis between autoimmune pancreatitis (AIP) and pancreatic ductal adenocarcinoma (PDAC) is clinically important. We aimed to determine significant MRI features for differentiating AIP from PDAC, including assessment of diffusion-weighted imaging (DWI). METHODS: We performed a systematic search using three databases. The pooled diagnostic odds ratio was calculated using a bivariate random effects model to determine significant MRI features for differentiating AIP from PDAC. The pooled sensitivity and specificity were calculated. The qualitative systematic review for DWI assessment was performed. RESULTS: Of nine studies (775 patients), multiple main pancreatic duct (MPD) strictures, absence of upstream marked MPD dilatation, peripancreatic rim, and duct penetration sign were significant MRI features for differentiating AIP from PDAC. Absence of MPD dilatation had the highest pooled sensitivity (87%, 95% CI=68-96%), whereas peripancreatic rim had the highest pooled specificity (100%, 95% CI=88-100%). Of 12 studies evaluating DWI, seven reported statistically significant differences in apparent diffusion coefficient (ADC) values between AIP and PDAC; however, four reported lower ADC values in AIP than in PDAC, but three reported the opposite result. CONCLUSION: The four significant MRI features can be useful to differentiate AIP from PDAC, but DWI assessment might be limited.
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Doenças Autoimunes , Pancreatite Autoimune , Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Pancreatite , Doenças Autoimunes/diagnóstico por imagem , Doenças Autoimunes/patologia , Pancreatite Autoimune/diagnóstico por imagem , Carcinoma Ductal Pancreático/diagnóstico por imagem , Carcinoma Ductal Pancreático/patologia , Diagnóstico Diferencial , Humanos , Imageamento por Ressonância Magnética/métodos , Ductos Pancreáticos/diagnóstico por imagem , Ductos Pancreáticos/patologia , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/patologia , Pancreatite/diagnóstico , Neoplasias PancreáticasRESUMO
BACKGROUND: Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) can develop in patients with and without risk factors for hepatocellular carcinoma (HCC). PURPOSE: To compare the clinical and magnetic resonance imaging (MRI) characteristics of cHCC-CCA in patients with and without risk factors for HCC, and to assess the influence of risk factors on patient prognosis. STUDY TYPE: Retrospective. POPULATION: A total of 152 patients with surgically confirmed cHCC-CCA. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T/T1-weighted dual gradient-echo in- and opposed-phase, T2-weighted turbo-spin-echo, diffusion-weighted single-shot spin-echo echo-planar, and T1-weighted three-dimensional gradient-echo contrast-enhanced sequences. ASSESSMENT: MRI features according to the Liver Imaging Reporting and Data System (LI-RADS) and pathologic findings based on revised classification were compared between patients with and without risk factors for HCC. Overall survival (OS) and recurrence-free survival (RFS) were also compared between the two groups, and factors associated with survival were evaluated. STATISTICAL TESTS: The clinico-pathologic and MRI features of the two groups were compared using Student's t-tests, Mann-Whitney U-tests, and chi-square tests. OS and RFS were evaluated by the Kaplan-Meier method, and factors associated with survival were evaluated by Cox proportional hazard model. RESULTS: cHCC-CCA in patients with risk factors were more frequently classified as LI-RADS category 4 or 5 (LR-4/5; probably or definitely HCC) (48.7%), whereas those without risk factors were more frequently classified as category M (LR-M; probably malignant, not specific for HCC) (63.6%). RFS and OS did not differ significantly according to risk factors (P = 0.63 and 0.83). Multivariable analysis showed that pathologic tumor type (hazard ratio 2.02; P < 0.05) and LI-RADS category (hazard ratio 2.19; P < 0.05) were significantly associated with RFS and OS, respectively. DATA CONCLUSION: Although MRI features of cHCC-CCA differed significantly between patients with and without risk factors for HCC, postsurgical prognosis did not. LI-RADS category and pathologic tumor type were independently correlated with postsurgical prognosis in patients with cHCC-CCA. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.
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Neoplasias dos Ductos Biliares , Carcinoma Hepatocelular , Colangiocarcinoma , Neoplasias Hepáticas , Ductos Biliares Intra-Hepáticos , Carcinoma Hepatocelular/diagnóstico por imagem , Colangiocarcinoma/diagnóstico por imagem , Humanos , Neoplasias Hepáticas/diagnóstico por imagem , Imageamento por Ressonância Magnética , Prognóstico , Estudos Retrospectivos , Fatores de RiscoRESUMO
OBJECTIVES: We aimed to assess the ability of CT-determined resectability, as defined by a recent version of NCCN criteria, and associated CT findings to predict margin-negative (R0) resection in patients with PDAC after neoadjuvant FOLFIRINOX chemotherapy. METHODS: Sixty-four patients (36 men and 28 women; mean age, 58.8 years) with borderline resectable or unresectable PDAC who received neoadjuvant FOLFIRINOX were evaluated retrospectively. CT findings were independently assessed by two abdominal radiologists according to NCCN criteria (version 3. 2019). Tumor resectability was classified as resectable, borderline resectable, or unresectable, and change in resectability was classified as regression, stability, or progression. The associations of R0 resection rate with CT-determined resectability and change in resectability categories were evaluated, as were the sensitivity and specificity of NCCN criteria for R0 resection. Factors associated with R0 resection were identified by logistic regression analysis. RESULTS: R0 resection rate did not differ significantly among the resectable, borderline resectable, or unresectable PDAC (67-73%, p = 0.95) or among PDAC with regression, stability, or progression (56-77%, p = 0.39). The sensitivity and specificity for R0 resection were 67% and 37%, respectively, for resectability (resectable/borderline vs. unresectable) and 80% and 21%, respectively, for changes in resectability (regression/stable vs. progression). Low-contrast enhancement of soft tissue contacting artery (≤ 46.4 HU) was independently associated with R0 resection (p = 0.01). CONCLUSION: CT-determined resectability after neoadjuvant FOLFIRINOX chemotherapy was relatively insensitive and non-specific for predicting R0 resection. Low-contrast enhancement of soft tissue contacting artery may increase the ability of CT to predict R0 resection. KEY POINTS: ⢠Margin-negative resection rate of pancreatic cancer following FOLFIRINOX therapy did not differ among each resectability (67-73%, p = 0.95) based on NCCN criteria or changes in resectability categories (56-77%, p = 0.39). ⢠The sensitivity and specificity for margin-negative resection were 67% and 37% for resectability (resectable/borderline vs. unresectable) and 80% and 21% for changes in resectability (regression/stable vs. progression). ⢠Low-contrast enhancement of soft tissue contacting artery (≤ 46.4 HU) was independently associated with margin-negative resection (p = 0.01).
Assuntos
Adenocarcinoma , Neoplasias Pancreáticas , Adenocarcinoma/diagnóstico por imagem , Adenocarcinoma/tratamento farmacológico , Adenocarcinoma/cirurgia , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Feminino , Fluoruracila , Humanos , Irinotecano , Leucovorina , Masculino , Pessoa de Meia-Idade , Terapia Neoadjuvante , Estadiamento de Neoplasias , Oxaliplatina , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/tratamento farmacológico , Neoplasias Pancreáticas/cirurgia , Estudos Retrospectivos , Tomografia Computadorizada por Raios X , Resultado do TratamentoRESUMO
OBJECTIVES: We aimed to systematically evaluate the diagnostic accuracy of CT-determined resectability following neoadjuvant treatment for predicting margin-negative resection (R0 resection) in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: Original studies with sufficient details to obtain the sensitivity and specificity of CT-determined resectability following neoadjuvant treatment, with a reference on the pathological margin status, were identified in PubMed, EMBASE, and Cochrane databases until February 24, 2020. The identified studies were divided into two groups based on the criteria of R0 resectable tumor (ordinary criterion: resectable PDAC alone; extended criterion: resectable and borderline resectable PDAC). The meta-analytic summary of the sensitivity and specificity for each criterion was estimated separately using a bivariate random-effect model. Summary results of the two criteria were compared using a joint-model bivariate meta-regression. RESULTS: Of 739 studies initially searched, 6 studies (6 with ordinary criterion and 5 with extended criterion) were included for analysis. The meta-analytic summary of sensitivity and specificity was 45% (95% confidence interval [CI], 19-73%; I2 = 88.3%) and 85% (95% CI, 65-94%; I2 = 60.5%) for the ordinary criterion, and 81% (95% CI, 71-87%; I2 = 0.0%) and 42% (95% CI, 28-57%; I2 = 6.2%) for the extended criterion, respectively. The diagnostic accuracy significantly differed between the two criteria (p = 0.02). CONCLUSIONS: For determining resectability on CT, the ordinary criterion might be highly specific but insensitive for predicting R0 resection, whereas the extended criterion increased sensitivity but would decrease specificity. Further investigations using quantitative parameters may improve the identification of R0 resection. KEY POINTS: ⢠CT-determined resectability of PDAC after neoadjuvant treatment using the ordinary criterion shows low sensitivity and high specificity in predicting R0 resection. ⢠With the extended criterion, CT-determined resectability shows higher sensitivity but lower specificity than with the ordinary criterion. ⢠CT-determined resectability with both criteria achieved suboptimal diagnostic performances, suggesting that care should be taken while selecting surgical candidates and when determining the surgical extent after neoadjuvant treatment in patients with PDAC.
Assuntos
Adenocarcinoma , Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Carcinoma Ductal Pancreático/diagnóstico por imagem , Carcinoma Ductal Pancreático/cirurgia , Humanos , Terapia Neoadjuvante , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/cirurgia , Tomografia Computadorizada por Raios XRESUMO
OBJECTIVES: To identify multiparametric MRI biomarkers to predict the tumor response to neoadjuvant FOLFIRINOX therapy in patients with borderline resectable (BR) or locally advanced (LA) pancreatic ductal adenocarcinoma (PDAC). METHODS: From May 2016 to March 2018, adult patients with BR or LA PDAC were prospectively enrolled in this study. They received eight cycles of FOLFIRINOX therapy and underwent multiparametric MRI twice (at baseline and after the second cycle). MRI evaluations included dynamic contrast-enhanced MRI, intravoxel incoherent motion diffusion-weighted imaging, and assessment of T2* relaxivity (R2*) and the change in T1 relaxivity (ΔR1, equilibrium phase R1 minus non-enhanced R1) of the tumors. Factors to predict the responders determined by the best overall response during FOLFIRINOX therapy and those to predict progression-free survival (PFS) and overall survival (OS) were evaluated using multivariable logistic regression and the Cox proportional hazard model. RESULTS: Forty-one patients (mean age, 60.3 years ± 9.3; 24 men) were included. Among the clinical and MRI factors, the baseline ΔR1 (adjusted odds ratio, 31.07; p = 0.008) was the only independent predictor for tumor response. The baseline ΔR1 was also an independent predictor for PFS (adjusted hazard ratio, 0.40; p = 0.033) along with R0 resection. The use of a cutoff ΔR1 value of ≥ 1.31 s-1 enabled prognostic stratification (median PFS, 16.0 months vs.10.0 months; p = 0.029; median OS, 34.9 months vs. 16.6 months; p = 0 .023, respectively). CONCLUSIONS: The baseline tumor ΔR1 value may be useful to predict tumor response and survival in patients with BR or LA PDAC receiving FOLFIRINOX neoadjuvant therapy. KEY POINTS: ⢠Baseline ΔR1 was an independent predictor for tumor response (adjusted odds ratio, 31.07; p = 0.008) and progression-free survival (adjusted hazard ratio, 0.40; p = 0.033) in patients with borderline resectable or locally advanced pancreatic ductal adenocarcinoma receiving neoadjuvant FOLFIRINOX therapy. ⢠The criterion of baseline ΔR1 value ≥ 1.31 s-1 allowed for the prediction of favorable tumor response and survival outcome after neoadjuvant FOLFIRINOX therapy.
Assuntos
Imageamento por Ressonância Magnética Multiparamétrica , Neoplasias Pancreáticas , Adulto , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Fluoruracila , Humanos , Irinotecano , Leucovorina , Masculino , Pessoa de Meia-Idade , Terapia Neoadjuvante , Oxaliplatina , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/tratamento farmacológicoRESUMO
Radiologic imaging is important for evaluating extrahepatic bile duct (EHD) cancers; it is used for staging tumors and evaluating the suitability of surgical resection, as surgery may be contraindicated in some cases regardless of tumor stage. However, the published general recommendations for EHD cancer and recommendations guided by the perspectives of radiologists are limited. The Korean Society of Abdominal Radiology (KSAR) study group for EHD cancer developed key questions and corresponding recommendations for the radiologic evaluation of EHD cancer and organized them into 4 sections: nomenclature and definition, imaging technique, cancer evaluation, and tumor response. A structured reporting form was also developed to allow the progressive accumulation of standardized data, which will facilitate multicenter studies and contribute more evidence for the development of recommendations.
Assuntos
Neoplasias dos Ductos Biliares/diagnóstico por imagem , Ductos Biliares Extra-Hepáticos/diagnóstico por imagem , Neoplasias dos Ductos Biliares/patologia , Neoplasias dos Ductos Biliares/cirurgia , Ductos Biliares Extra-Hepáticos/anatomia & histologia , Vasos Sanguíneos/diagnóstico por imagem , Colangiopancreatografia por Ressonância Magnética , Humanos , Imageamento por Ressonância Magnética , Metástase Neoplásica , Estadiamento de Neoplasias , Sociedades Médicas , Tomografia Computadorizada por Raios XRESUMO
OBJECTIVES: To systematically determine the diagnostic performance of computed tomography (CT) and magnetic resonance imaging (MRI) for differentiating autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC), with a comparison between the two imaging modalities. METHODS: Literature search was conducted using PubMed and EMBASE databases to identify original articles published between 2009 and 2019 reporting the diagnostic performance of CT and MRI for differentiating AIP from PDAC. The meta-analytic sensitivity and specificity of CT and MRI were calculated, and compared using a bivariate random effects model. Subgroup analysis for differentiating focal AIP from PDAC was performed. RESULTS: Of the 856 articles screened, 11 eligible articles are remained, i.e., five studies for CT, four for MRI, and two for both. The meta-analytic summary sensitivity and specificity of CT were 59% (95% confidence interval [CI], 41-75%) and 99% (95% CI, 88-100%), respectively, while those of MRI were 84% (95% CI, 68-93%) and 97% (95% CI, 87-99%). MRI had a significantly higher meta-analytic summary sensitivity than CT (84% vs. 59%, p = 0.02) but a similar specificity (97% vs. 99%, p = 0.18). In the subgroup analysis for focal AIP, the sensitivity for distinguishing between focal AIP and PDAC was lower than that for the overall analysis. MRI had a higher sensitivity than CT (76% vs. 50%, p = 0.28) but a similar specificity (97% vs. 98%, p = 0.07). CONCLUSION: MRI might be clinically more useful to evaluate patients with AIP, particularly for differentiating AIP from PDAC. KEY POINTS: ⢠MRI had an overall good diagnostic performance to differentiate AIP from PDAC with a meta-analytic summary estimate of 83% for sensitivity and of 97% for specificity. ⢠CT had a very high specificity (99%), but a suboptimal sensitivity (59%) for differentiating AIP from PDAC. ⢠Compared with CT, MRI had a higher sensitivity, but a similar specificity.
Assuntos
Adenocarcinoma , Doenças Autoimunes , Pancreatite Autoimune , Neoplasias Pancreáticas , Pancreatite , Adenocarcinoma/diagnóstico por imagem , Doenças Autoimunes/diagnóstico por imagem , Diagnóstico Diferencial , Humanos , Imageamento por Ressonância Magnética , Neoplasias Pancreáticas/diagnóstico por imagem , Pancreatite/diagnóstico por imagem , Sensibilidade e Especificidade , Tomografia Computadorizada por Raios XRESUMO
BACKGROUND: Although lymph node metastasis is a poor prognostic factor in patients with pancreatic ductal adenocarcinoma (PDAC), our understanding of lymph node size in association with PDAC is limited. Increased nodal size in preoperative imaging has been used to detect node metastasis. We evaluated whether lymph node size can be used as a surrogate preoperative marker of lymph node metastasis. METHODS: We assessed nodal size and compared it to the nodal metastatic status of 200 patients with surgically resected PDAC. The size of all lymph nodes and metastatic nodal foci were measured along the long and short axis, and the relationships between nodal size and metastatic status were compared at six cutoff points. RESULTS: A total of 4,525 lymph nodes were examined, 9.1% of which were metastatic. The mean size of the metastatic nodes (long axis, 6.9±5.0 mm; short axis, 4.3±3.1 mm) was significantly larger than that of the non-metastatic nodes (long axis, 5.0±4.0 mm; short axis, 3.0±2.0 mm; all p<.001). Using a 10 mm cutoff, the sensitivity, specificity, positive predictive value, overall accuracy, and area under curve was 24.8%, 88.0%, 17.1%, 82.3%, and 0.60 for the long axis and 7.0%, 99.0%, 40.3%, 90.6%, and 0.61 for the short axis, respectively. CONCLUSIONS: The metastatic nodes are larger than the non-metastatic nodes in PDAC patients. However, the difference in nodal size was too small to be identified with preoperative imaging. The performance of preoperative radiologic imaging to predict lymph nodal metastasis was not good. Therefore, nodal size cannot be used a surrogate preoperative marker of lymph node metastasis.
RESUMO
Background No preoperative model is available for predicting postsurgical prognosis of patients with resectable pancreatic ductal adenocarcinoma (PDAC). Purpose To develop and validate a preoperative risk scoring system using clinical and CT variables to predict recurrence-free survival (RFS) after upfront surgery in patients with resectable PDAC. Materials and Methods In this retrospective study, consecutive patients with resectable PDAC underwent upfront surgery from January 2014 to December 2015 (development set) and from January 2016 to January 2017 (test set). In the development set, multivariable Cox proportional hazard modeling with bootstrapping was used to select clinical and CT variables associated with RFS and to construct a risk scoring system. The discrimination capability of the risk score was assessed by using the Harrell C-index and compared with that of pathologic American Joint Committee on Cancer tumor stage. The risk score was validated in the test set. Results A total of 395 patients were evaluated, including 262 patients (mean age ± standard deviation, 64 years ± 10; 155 men) in the development set and 133 (mean age, 64 years ± 9; 79 men) in the test set. Five independent variables predicted risk of recurrence or death: tumor size (hazard ratio [HR], 1.23; 95% confidence interval [CI]: 1.05, 1.44; P = .009), hypodense tumor in the portal venous phase (HR, 1.66; 95% CI: 1.01, 2.73; P = .04), tumor necrosis (HR, 2.04; 95% CI: 1.38, 3.03; P < .001), peripancreatic tumor infiltration (HR, 1.50; 95% CI: 1.07, 2.11; P = .02), and suspicious metastatic lymph nodes (HR, 1.94; 95% CI: 1.38, 2.72; P < .001). In the test set, the risk score showed good discrimination capability (C-index of 0.68; 95% CI: 0.63, 0.74) and outperformed the pathologic tumor stage (C-index of 0.60; 95% CI: 0.55, 0.66; P = .03). Patients were categorized into favorable, intermediate, and poor prognosis groups with 1-year RFS of 0.87, 0.58, and 0.26, respectively. Conclusion The presented preoperative risk score can predict recurrence-free survival after upfront surgery in patients with resectable pancreatic ductal adenocarcinoma. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Pandharipande and Anderson in this issue.