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Adding Value of MRI over CT in Predicting Peritoneal Cancer Index and Completeness of Cytoreduction.

ABSTRACT: This study aimed to investigate the adding value of MRI over CT for preoperative cytoreductive surgery with hyperthermic intraperitoneal chemotherapies (CRS/HIPEC). Imaging and intraoperative peritoneal cancer index (PCI) were calculated in 62 patients with peritoneal metastasis. Predictive models for the completeness of cytoreductive score using PCI data were established using decision tree algorithms. In gastric cancer patients, a large discrepancy and poor agreement was appreciated between CT and surgical PCI, and a nonsignificant difference was noted between MRI and surgical PCI. In colon cancer patients, a better agreement and higher correlation with a smaller error was observed in PCI score using MRI than in that using CT. However, the addition of MRI to CT was limited for appendiceal and ovarian cancer patients. For predicting incomplete cytoreduction, CT models yielded inadequate accuracy while MRI models were more accurate with fair discrimination ability. CT was suitable for estimating PCI and surgery outcome in appendiceal and ovarian cancer patients, while further MRI in addition to CT was recommended for colon and gastric cancer patients. However, for classifying patients with peritoneal carcinomatosis into complete and incomplete cytoreduction, MRI was more effective than CT.

SUBMITTER: Lin CN

PROVIDER: S-EPMC8068380 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Adding Value of MRI over CT in Predicting Peritoneal Cancer Index and Completeness of Cytoreduction.

Lin Chia-Ni CN Huang Weh-Shih WS Huang Tzu-Hao TH Chen Chao-Yu CY Huang Cheng-Yi CY Wang Ting-Yao TY Liao Yu-San YS Lee Li-Wen LW

Diagnostics (Basel, Switzerland) 20210408 4

<h4>Background</h4>This study aimed to investigate the adding value of MRI over CT for preoperative cytoreductive surgery with hyperthermic intraperitoneal chemotherapies (CRS/HIPEC).<h4>Methods</h4>Imaging and intraoperative peritoneal cancer index (PCI) were calculated in 62 patients with peritoneal metastasis. Predictive models for the completeness of cytoreductive score using PCI data were established using decision tree algorithms.<h4>Results</h4>In gastric cancer patients, a large discrepa ...[more]

PMID: 33917997

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Project description:The cornerstone of ovarian cancer treatment is complete surgical cytoreduction. The gold-standard option in the absence of extra-abdominal metastases and intra-abdominal inoperable circumstances is primary cytoreductive surgery (CRS). However, achieving complete cytoreduction is challenging, and only possible in a selected patient population. Preoperative imaging modalities such as [18F]FDG PET/CT could be useful in patient selection for cytoreductive surgery. In our systematic review and meta-analysis, we aimed to evaluate the role of preoperative [18F]FDG PET/CT in predicting complete cytoreduction in primary and secondary debulking surgeries. Publications were pooled from two databases (PubMed, Mendeley) with predefined keywords "(ovarian cancer) AND (FDG OR PET) AND (cytoreductive surgery)". The quality of the included studies was assessed with the Prediction model Risk Of Bias Assessment Tool (PROBAST). During statistical analysis, MetaDiSc 1.4 software and the DerSimonian-Laird method (random effects models) were used. Primary and secondary cytoreductive surgeries were evaluated. Pooled sensitivities, specificities, positive predictive values (PPVs), and negative predictive values (NPVs) were calculated and statistically analyzed. Results were presented in forest plot diagrams and summary receiver operating characteristic (SROC) curves. Overall, eight publications were included in our meta-analysis. Four publications presented results of primary, three presented results of secondary cytoreductions, and two presented data related to both primary and secondary surgery. Pooled sensitivities, specificities, and positive and negative predictive values were the following: in the case of primary surgeries: 0.65 (95% CI 0.60-0.71), 0.73 (95% CI 0.66-0.80), 0.82 (95% CI 0.77-0.87), 0.52 (95% CI 0.46-0.59); and in the case of secondary surgeries: 0.91 (95% CI 0.84-0.95), 0.48 (95% CI 0.30-0.67), 0.88 (95% CI 0.81-0.93), 0.56 (95% CI 0.35-0.75), respectively. The PPVs of [18F]FDG PET/CT proved to be higher in cases of secondary debulking surgeries; therefore, it can be a valuable predictor of complete successful secondary cytoreduction.

Project description:ObjectivesTo investigate the potential of intratumoral and peritumoral radiomics derived from T2-weighted MRI to preoperatively predict extrapelvic peritoneal metastasis (EPM) in patients with epithelial ovarian cancer (EOC).MethodsIn this retrospective study, 488 patients from four centers were enrolled and divided into training (n = 245), internal test (n = 105), and external test (n = 138) sets. Intratumoral and peritumoral models were constructed based on radiomics features extracted from the corresponding regions. A combined intratumoral and peritumoral model was developed via a feature-level fusion. An ensemble model was created by integrating this combined model with specific independent clinical predictors. The robustness and generalizability of these models were assessed using tenfold cross-validation and both internal and external testing. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC). The Shapley Additive Explanation method was employed for model interpretation.ResultsThe ensemble model showed superior performance across the tenfold cross-validation, with the highest mean AUC of 0.844 ± 0.063. On the internal test set, the peritumoral and ensemble models significantly outperformed the intratumoral model (AUC = 0.786 and 0.832 vs. 0.652, p = 0.007 and p < 0.001, respectively). On the external test set, the AUC of the ensemble model significantly exceeded those of the intratumoral and peritumoral models (0.843 vs. 0.750 and 0.789, p = 0.008 and 0.047, respectively).ConclusionPeritumoral radiomics provide more informative insights about EPM than intratumoral radiomics. The ensemble model based on MRI has the potential to preoperatively predict EPM in EOC patients.Critical relevance statementIntegrating both intratumoral and peritumoral radiomics information based on MRI with clinical characteristics is a promising noninvasive method to predict EPM to guide preoperative clinical decision-making for EOC patients.Key pointsPeritumoral radiomics can provide valuable information about extrapelvic peritoneal metastasis in epithelial ovarian cancer. The ensemble model demonstrated satisfactory performance in predicting extrapelvic peritoneal metastasis. Combining intratumoral and peritumoral MRI radiomics contributes to clinical decision-making in epithelial ovarian cancer.

Project description:BackgroundBioelectric impedance analysis (BIA)-measured body composition and nutritional status have been used as prognostic indicators in various cancer cohorts. This study investigated whether BIA could provide information on prognosis in peritoneal carcinomatosis patients undergoing cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC).MethodsWe retrospectively analyzed the data of 99 patients with preoperative BIA data among those who underwent CRS and HIPEC. The association between BIA-derived parameters and intraoperative peritoneal cancer index (PCI) score was assessed. Predictive analysis for the occurrence of postoperative morbidities including major complications (Clavien-Dindo classification 3-4) and re-admission within 30 days after surgery as well as 1 year mortality was also performed.ResultsBIA-derived mineral (r = 0.224, p = 0.027), fat (r = - 0.202, p = 0.048), and total body water (TBW)/fat-free mass (FFM) (r = - 0.280, p = 0.005) showed significant associations with intraoperative PCI score. Lower TBW/FFM was an independent predictor of major postoperative complications (OR 0.047, 95% CI 0.003-0.749, p = 0.031) and re-admission (OR 0.094, 95% CI 0.014-0.657, p = 0.017) within 30 days after surgery. Higher fat mass was also independently associated with a higher risk of major postoperative complications (OR 1.120, 95% CI 1.006-1.248, p = 0.039) and re-admission (OR 1.123, 95% CI 1.024-1.230, p = 0.013). Intraoperative PCI score > 20 (OR 4.489, 95% CI 1.191-16.917, p = 0.027) and re-admission within 30 days after surgery (OR 5.269, 95% CI 1.288-21.547, p = 0.021) independently predicted postoperative 1-year mortality.ConclusionsWe demonstrate that preoperative BIA-derived TBW/FFM and fat mass were significantly correlated with metastatic extent, assessed by PCI score, in patients with peritoneal carcinomatosis. In addition, BIA-derived TBW/FFM and fat mass showed independent predictability for postoperative 30-day major complications and re-admission in patients undergoing CRS and HIPEC. Our findings suggest that assessment of BIA may improve discrete risk stratification in patients who are planned to receive CRS and HIPEC.

Project description:PurposeTo identify patient and tumor features that predict true-positive, false-positive, and negative breast preoperative MRI outcomes.Materials and methodsUsing a breast MRI database from a large regional cancer center, the authors retrospectively identified all women with unilateral breast cancer who underwent preoperative MRI from January 2005 to February 2015. A total of 1396 women with complete data were included. Patient features (ie, age, breast density) and index tumor features (ie, type, grade, hormone receptor, human epidermal growth factor receptor type 2/neu, Ki-67) were extracted and compared with preoperative MRI outcomes (ie, true positive, false positive, negative) using univariate (ie, Fisher exact) and multivariate machine learning approaches (ie, least absolute shrinkage and selection operator, AutoPrognosis). Overall prediction performance was summarized using the area under the receiver operating characteristic curve (AUC), calculated using internal validation techniques (bootstrap and cross-validation) to account for model training.ResultsAt the examination level, 181 additional cancers were identified among 1396 total preoperative MRI examinations (median patient age, 56 years; range, 25-94 years), resulting in a positive predictive value for biopsy of 43% (181 true-positive findings of 419 core-needle biopsies). In univariate analysis, no patient or tumor feature was associated with a true-positive outcome (P > .05), although greater mammographic density (P = .022) and younger age (< 50 years, P = .025) were associated with false-positive examinations. Machine learning approaches provided weak performance for predicting true-positive, false-positive, and negative examinations (AUC range, 0.50-0.57).ConclusionCommonly used patient and tumor factors driving expert opinion for the use of preoperative MRI provide limited predictive value for determining preoperative MRI outcomes in women. Supplemental material is available for this article. © RSNA, 2020See also the commentary by Grimm in this issue.

Project description:Peritoneal cancer index (PCI) is the surgical variable most commonly used to quantify the extent of peritoneal metastases for pseudomyxoma peritonei (PMP) patients. The present study aimed to investigate the agreement between CT predicted and surgical PCI by the Bland-Altman method for PMP of appendiceal origin. A total of 167 PMP patients of appendiceal origin were included between 2016 and 2021. Bland-Altman analysis was performed for both total PCI and selected PCI (regions 2 + 9-12). After the Bland-Altman plot was drawn, the mean bias and its 95% limit of agreements (LoAs) was quantified. Besides, the correlation coefficients between CT-PCI and surgical PCI were also been calculated. The Bland-Altman plot showed the mean bias ± SD between total CT-PCI and surgical PCI as 0.431 ± 3.005, with the LoAs from - 5.459 to 6.321. There were nine points of difference in total PCI exceeded the 95% LoAs, with the rate of 5.39% (9/167). As for selected CT-PCI, Bland-Altman plot showed the mean bias ± SD between selected CT-PCI and surgical PCI as - 0.287 ± 1.955, with the LoAs from - 4.118 to 3.544. There were ten points of difference in selected PCI exceeded the 95% LoAs, with the rate of 5.99% (10/167). The Spearman's rank correlation coefficient between total CT-PCI and surgical PCI was 0.911, P < 0.001, as for selected CT-PCI and surgical PCI, the coefficient was 0.909, P < 0.001. Although there was a strong correlation for both total and selected CT-PCI with surgical PCI, however, the agreement is still not good in Bland-Altman analysis, which suggested that CT-PCI cannot predict surgical PCI accurately even in professional PMP treatment centers. In brief explanation, CT makes it difficult to distinguish the borderline between tumor tissue and mucus and to detect tumor lesions in the small intestine regions, which caused overestimation or underestimation by CT-PCI. In the future, a multiple linear regression model based on CT-PCI might accurately predict surgical PCI preoperatively.

Dataset Information

Adding Value of MRI over CT in Predicting Peritoneal Cancer Index and Completeness of Cytoreduction.

Publications

Adding Value of MRI over CT in Predicting Peritoneal Cancer Index and Completeness of Cytoreduction.

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