Correlation of MR features and histogram-derived parameters with aggressiveness and outcomes after resection in pancreatic ductal adenocarcinoma

Robertis, Riccardo De; Beleù, Alessandro; Cardobi, Nicolò; Frigerio, Isabella; Ortolani, Silvia; Gobbo, Stefano; Maris, Bogdan Mihai; Melisi, Davide; Montemezzi, Stefania; D’Onofrio, Mirko

doi:10.1007/s00261-020-02509-3

Cited by 11 publications

(10 citation statements)

References 26 publications

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“…Changes in histogram metrics, shape and asymmetry reflect microstructural and functional differences in tumor composition correlated to biological aggressiveness and prognosis; these might be of relevant interest to develop targeted therapeutic strategies for cancer patients, for example to identify those patients that could benefit from preoperative chemotherapy rather than upfront surgery. The predictive and prognostic role of histogram-derived parameters was confirmed by previous studies, which demonstrated their usefulness in the identification of pancreatic neuroendocrine neoplasms (panNENs) with higher biological aggressiveness and worse prognosis, and to assess the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs) [ 10 , 11 , 12 , 13 , 14 , 15 ]. Histogram analysis also demonstrated a potential role in predicting recurrence-free survival after surgical resection in patients with PDAC [ 14 ].…”

Section: Introductionmentioning

confidence: 73%

Correlation between ADC Histogram-Derived Metrics and the Time to Metastases in Resectable Pancreatic Adenocarcinoma

Robertis

Tomaiuolo

Pasquazzo

et al. 2022

Cancers

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Background: A non-invasive method to improve the prognostic stratification would be clinically beneficial in patients with resectable pancreatic adenocarcinoma (PDAC). The aim of this study was to correlate conventional magnetic resonance (MR) features and the metrics derived from the histogram analysis of apparent diffusion coefficient (ADC) maps, with the risk and the time to metastases (TTM) after surgery in patients with PDAC. Methods: pre-operative MR examinations of 120 patients were retrospectively analyzed. Patients were grouped according to the presence (M+) or absence (M−) of metastases during follow-up. Conventional MR features and histogram-derived metrics were compared between M+ and M− patients using the Fisher’s or Mann–Whitney tests; receiver operating characteristic (ROC) curves were constructed for the features that showed a significant difference between groups. A Cox regression analysis was performed to identify the features with a significant effect on the TTM, and Kaplan–Meier curves were constructed for significant features. Results: 68.3% patients developed metastases over a mean follow-up time of 29 months (range, 3–54 months). ADC skewness and kurtosis were significantly higher in M+ than in M− patients (p < 0.001). Skewness had a significant effect on the risk of metastases (hazard ratio—HR = 5.22, p < 0.001). Patients with an ADC skewness ≥0.23 had a significantly shorter TTM than those with a skewness <0.22 (11.7 vs. 30.8 months, p < 0.001). Conclusions: pre-operative histogram analysis of ADC maps provides parameters correlated to the metastatic potential of PDAC. Higher ADC skewness seems to be associated with a significantly shorter TTM in patients with resectable PDAC.

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Section: Introductionmentioning

confidence: 73%

Correlation between ADC Histogram-Derived Metrics and the Time to Metastases in Resectable Pancreatic Adenocarcinoma

Robertis

Tomaiuolo

Pasquazzo

et al. 2022

Cancers

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“…Moreover, shape-based features are independent of imaging acquisition parameters and imaging preprocessing techniques, and thus may be highly reproducible. In addition, recent studies (22)(23)(24)(25) have suggested that texture features indicating inhomogeneity in imaging are associated with increased intra-tumor heterogeneity of PDAC. The results of this study indicated that some texture features may be closely related to adverse tumor biology in PV-SMV involvement.…”

Section: Discussionmentioning

confidence: 99%

“…Radiomics (20,21) is a data-centric field that processes radiological imaging data by extracting large amounts of quantitative image features, which are subsequently employed to construct novel imaging biomarkers, namely radiomics signature. Previous radiomics studies on PDAC (22)(23)(24)(25) have indicated that quantitative image features were closely related to adverse pathological features, therapeutic response, and prognosis after neoadjuvant therapy. However, radiomics research on distinguishing surgical PV-SMV invasion in patients with PDAC is lacking.…”

Section: Introductionmentioning

confidence: 99%

Radiomics-Assisted Presurgical Prediction for Surgical Portal Vein-Superior Mesenteric Vein Invasion in Pancreatic Ductal Adenocarcinoma

Chen

Zhou

et al. 2020

Front. Oncol.

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Objectives To develop a radiomics signature for predicting surgical portal vein-superior mesenteric vein (PV-SMV) in patients with pancreatic ductal adenocarcinoma (PDAC) and measure the effect of providing the predictions of radiomics signature to radiologists with different diagnostic experiences during imaging interpretation. Methods Between February 2008 and June 2020, 146 patients with PDAC in pancreatic head or uncinate process from two institutions were retrospectively included and randomly split into a training (n = 88) and a validation (n =58) cohort. Intraoperative vascular exploration findings were used to identify surgical PV-SMV invasion. Radiomics features were extracted from the portal venous phase CT images. Radiomics signature was built with a linear elastic-net regression model. Area under receiver operating characteristic curve (AUC) of the radiomics signature was calculated. A senior and a junior radiologist independently review CT scans and made the diagnosis for PV-SMV invasion both with and without radiomics score (Radscore) assistance. A 2-sided Pearson’s chi-squared test was conducted to evaluate whether there was a difference in sensitivity, specificity, and accuracy between the radiomics signature and the unassisted radiologists. To assess the incremental value of providing Radscore predictions to the radiologists, we compared the performance between unassisted evaluation and Radscore-assisted evaluation by using the McNemar test. Results Numbers of patients identified as presence of surgical PV-SMV invasion were 33 (37.5%) and 19 (32.8%) in the training and validation cohort, respectively. The radiomics signature achieved an AUC of 0.848 (95% confidence interval, 0.724–0.971) in the validation cohort and had a comparable sensitivity, specificity, and accuracy as the senior radiologist in predicting PV-SMV invasion (all p -values > 0.05). Providing predictions of radiomics signature increased both radiologists’ sensitivity in identifying PV-SMV invasion, while only the increase of the junior radiologist was significant (63.2 vs 89.5%, p -value = 0.025) instead of the senior radiologist (73.7 vs 89.5%, p -value = 0.08). Both radiologists’ accuracy had no significant increase when provided radiomics signature assistance (both p -values > 0.05). Conclusions The radiomics signature can predict surgical PV-SMV invasion in patients with PDAC and may have incremental value to the diagnostic performance of radiologists during imaging interpretation.

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“…In recent years, the research in the field of radiology strongly focused on the extraction of inner tumor features by the high throughput analysis of biomedical images through the process known as radiomics. Previous reports have shown that a radiomic approach to PDAC may show promising results [ 12 , 13 , 14 ], but the application of such analysis to clinical practice is still very limited, due to its complexity. However, a simplified approach to radiomics may be feasible: for example, Choi et al [ 15 ] reported a correlation between non-complex features, as tumor margins, and DPC4 expression in PDAC patients.…”

Section: Introductionmentioning

confidence: 99%

CT Simplified Radiomic Approach to Assess the Metastatic Ductal Adenocarcinoma of the Pancreas

D’Onofrio

Robertis

Aluffi

et al. 2021

Cancers

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The aim of this study was to perform a simplified radiomic analysis of pancreatic ductal adenocarcinoma based on qualitative and quantitative tumor features and to compare the results between metastatic and non-metastatic patients. A search of our radiological, surgical, and pathological databases identified 1218 patients with a newly diagnosed pancreatic ductal adenocarcinoma who were referred to our Institution between January 2014 and December 2018. Computed Tomography (CT) examinations were reviewed analyzing qualitative and quantitative features. Two hundred eighty-eight patients fulfilled the inclusion criteria and were included in this study. Overall, metastases were present at diagnosis in 86/288 patients, while no metastases were identified in 202/288 patients. Ill-defined margins and a hypodense appearance on portal-phase images were significantly more common among patients with metastases compared to non-metastatic patients (p < 0.05). Metastatic tumors showed a significantly larger size and significantly lower arterial index, perfusion index, and permeability index compared to non-metastatic tumors (p < 0.05). In the management of pancreatic ductal adenocarcinoma, early detection and correct staging are key elements. The study of computerized tomography characteristics of pancreatic ductal adenocarcinoma showed substantial differences, both qualitative and quantitative, between metastatic and non-metastatic disease.

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Correlation of MR features and histogram-derived parameters with aggressiveness and outcomes after resection in pancreatic ductal adenocarcinoma

Cited by 11 publications

References 26 publications

Correlation between ADC Histogram-Derived Metrics and the Time to Metastases in Resectable Pancreatic Adenocarcinoma

Correlation between ADC Histogram-Derived Metrics and the Time to Metastases in Resectable Pancreatic Adenocarcinoma

Radiomics-Assisted Presurgical Prediction for Surgical Portal Vein-Superior Mesenteric Vein Invasion in Pancreatic Ductal Adenocarcinoma

CT Simplified Radiomic Approach to Assess the Metastatic Ductal Adenocarcinoma of the Pancreas

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