Functional tumour burden of peritoneal carcinomatosis derived from DWI could predict incomplete tumour debulking in advanced ovarian carcinoma

Assessment of Intraoperative Scoring Systems for Predicting Cytoreduction Outcome in Peritoneal Metastatic Disease: A Systematic Review and Meta-analysis

BACKGROUND

Cytoreductive surgery (CRS) is a widely acknowledged treatment approach for peritoneal metastasis, showing favorable prognosis and long-term survival. Intraoperative scoring systems quantify tumoral burden before CRS and may predict complete cytoreduction (CC). This study reviews the intraoperative scoring systems for predicting CC and optimal cytoreduction (OC) and evaluates the predictive performance of the Peritoneal Cancer Index (PCI) and Predictive Index Value (PIV).

METHODS

Systematic searches were conducted in Embase, MEDLINE, and Web of Science. Meta-analyses of extracted data were performed to compare the absolute predictive performances of PCI and PIV.

RESULTS

Thirty-eight studies (5834 patients) focusing on gynecological (n = 34; 89.5%), gastrointestinal (n = 2; 5.3%) malignancies, and on tumors of various origins (n = 2; 5.3%) were identified. Seventy-seven models assessing the predictive performance of scoring systems (54 for CC and 23 for OC) were identified with PCI (n = 39/77) and PIV (n = 16/77) being the most common. Twenty models (26.0%) reinterpreted previous scoring systems of which ten (13%) used a modified version of PIV (reclassification). Meta-analyses of models predicting CC based on PCI (n = 21) and PIV (n = 8) provided an AUC estimate of 0.83 (95% confidence interval [CI] 0.79-0.86; Q = 119.6, p = 0.0001; I2 = 74.1%) and 0.74 (95% CI 0.68-0.81; Q = 7.2, p = 0.41; I2 = 11.0%), respectively.

CONCLUSIONS

Peritoneal Cancer Index models demonstrate an excellent estimate of CC, while PIV shows an acceptable performance. There is a need for high-quality studies to address management differences, establish standardized cutoff values, and focus on non-gynecological malignancies.

Estimating pathological prognostic factors in epithelial ovarian cancers using apparent diffusion coefficients of functional tumor volume

PURPOSE

To assess the utility of apparent diffusion coefficients (ADCs) of whole tumor volume (WTV) and functional tumor volume (FTV) in determining the pathologicalprognostic factors in epithelial ovarian cancers (EOCs).

METHODS

A total of 155 consecutive patients who were diagnosed with EOC between January 2017 and August 2022 and underwent both conventional magnetic resonance imaging and diffusion-weighted imaging were assessed in this study. The maximum, minimum, and mean ADC values of the whole tumor (ADCwmax, ADCwmin, and ADCwmean, respectively) and functional tumor (ADCfmax, ADCfmin, and ADCfmean, respectively) as well as the WTV and FTV were derived from the ADC maps. The univariate and multivariate logistic regression analyses and receiver operating characteristic curve (ROC) analysis were used to assess the correlation between these ADC values and the pathological prognostic factors, namely subtypes, lymph node metastasis (LNM), Ki-67 index, and p53 expression.

RESULTS

The ADCfmean value was significantly lower in type II EOC, LNM-positive, and high-Ki-67 index groups compared to the type I EOC, LNM-negative, and low-Ki-67 index groups (p ≤ 0.001). Similarly, the ADCwmean and ADCfmean values were lower in the mutant-p53 group compared to the wild-type-p53 group (p ≤ 0.001). Additionally, the ADCfmean showed the highest area under the ROC curve (AUC) for evaluating type II EOC (0.725), LNM-positive (0.782), and high-Ki-67 index (0.688) samples among the given ROC curves, while both ADCwmean and ADCfmean showed high AUCs for assessing p53 expression (0.694 and 0.678, respectively).

CONCLUSION

The FTV-derived ADC values, especially ADCfmean, can be used to assess preoperative prognostic factors in EOCs.

A modified diffusion-weighted magnetic resonance imaging-based model from the radiologist's perspective: improved performance in determining the surgical resectability of advanced high-grade serous ovarian cancer

BACKGROUND

Complete resection of all visible lesions during primary debulking surgery is associated with the most favorable prognosis in patients with advanced high-grade serous ovarian cancer. An accurate preoperative assessment of resectability is pivotal for tailored management.

OBJECTIVE

This study aimed to assess the potential value of a modified model that integrates the original 8 radiologic criteria of the Memorial Sloan Kettering Cancer Center model with imaging features of the subcapsular or diaphragm and mesenteric lesions depicted on diffusion-weighted magnetic resonance imaging and growth patterns of all lesions for predicting the resectability of advanced high-grade serous ovarian cancer.

STUDY DESIGN

This study included 184 patients with high-grade serous ovarian cancer who underwent preoperative diffusion-weighted magnetic resonance imaging between December 2018 and May 2023 at 2 medical centers. The patient cohort was divided into 3 subsets, namely a study cohort (n=100), an internal validation cohort (n=46), and an external validation cohort (n=38). Preoperative radiologic evaluations were independently conducted by 2 radiologists using both the Memorial Sloan Kettering Cancer Center model and the modified diffusion-weighted magnetic resonance imaging-based model. The morphologic characteristics of the ovarian tumors depicted on magnetic resonance imaging were assessed as either mass-like or infiltrative, and transcriptomic analysis of the primary tumor samples was performed. Univariate and multivariate statistical analyses were performed.

RESULTS

In the study cohort, both the scores derived using the Memorial Sloan Kettering Cancer Center (intraclass correlation coefficients of 0.980 and 0.959, respectively; both P<.001) and modified diffusion-weighted magnetic resonance imaging-based models (intraclass correlation coefficients of 0.962 and 0.940, respectively; both P<.001) demonstrated excellent intra- and interobserver agreement. The Memorial Sloan Kettering Cancer Center model (odds ratio, 1.825; 95% confidence interval, 1.390-2.395; P<.001) and the modified diffusion-weighted magnetic resonance imaging-based model (odds ratio, 1.776; 95% confidence interval, 1.410-2.238; P<.001) independently predicted surgical resectability. The modified diffusion-weighted magnetic resonance imaging-based model demonstrated improved predictive performance with an area under the curve of 0.867 in the study cohort and 0.806 and 0.913 in the internal and external validation cohorts, respectively. Using the modified diffusion-weighted magnetic resonance imaging-based model, patients with scores of 0 to 2, 3 to 4, 5 to 6, 7 to 10, and ≥11 achieved complete tumor debulking rates of 90.3%, 66.7%, 53.3%, 11.8%, and 0%, respectively. Most patients with incomplete tumor debulking had infiltrative tumors, and both the Memorial Sloan Kettering Cancer Center and the modified diffusion-weighted magnetic resonance imaging-based models yielded higher scores. The molecular differences between the 2 morphologic subtypes were identified.

CONCLUSION

When compared with the Memorial Sloan Kettering Cancer Center model, the modified diffusion-weighted magnetic resonance imaging-based model demonstrated enhanced accuracy in the preoperative prediction of resectability for advanced high-grade serous ovarian cancer. Patients with scores of 0 to 6 were eligible for primary debulking surgery.

Quantitative tumor burden imaging parameters of the spleen at MRI for predicting treatment response in patients with acute leukemia

Objectives

To study the value of standardized volume and intravoxel incoherent motion (IVIM) parameters of the spleen based on tumor burden for predicting treatment response in newly diagnosed acute leukemia (AL).

Methods

Patients with newly diagnosed AL were recruited and underwent abdominal IVIM diffusion-weighted imaging within one week before the first induction chemotherapy. Quantitative parameters of magnetic resonance imaging (MRI) included the standardized volume (representing volumetric tumor burden) and IVIM parameters (standard apparent diffusion coefficient [sADC]; pure diffusion coefficient [D]; pseudo-diffusion coefficient [D∗]; and pseudo-perfusion fraction [f], representing functional tumor burden) of the spleen. Clinical biomarkers of tumor burden were collected. Patients were divided into complete remission (CR) and non-CR groups according to the treatment response after the first standardized induction chemotherapy, and the MRI and clinical parameters were compared between the two groups. The correlations of MRI parameters with clinical biomarkers were analyzed. Multivariate logistic regression was performed to determine the independent predictors for treatment response. Receiver operating characteristic curves were used to analyze the predicted performance.

Results

76 AL patients (CR: n = 43; non-CR: n = 33) were evaluated. Standardized spleen volume, sADC, D, f, white blood cell counts, and lactate dehydrogenase were significantly different between CR and non-CR groups (all p < 0.05). Standardized spleen volume, sADC, and D were correlated with white blood cell and lactate dehydrogenase, and f was correlated with lactate dehydrogenase (all p < 0.05). Standardized spleen volume (hazard ratio = 4.055, p = 0.042), D (hazard ratio = 0.991, p = 0.027), and f (hazard ratio = 1.142, p = 0.008) were independent predictors for treatment response, and the combination of standardized spleen volume, D, and f showed more favorable discrimination (area under the curve = 0.856) than individual predictors.

Conclusion

Standardized volume, D, and f of the spleen could be used to predict treatment response in newly diagnosed AL, and the combination of morphological and functional parameters would further improve the predicted performance. IVIM parameters of the spleen may be viable indicators for evaluating functional tumor burden in AL.

Development of a prediction model for gross residual in high-grade serous ovarian cancer by combining preoperative assessments of abdominal and pelvic metastases and multiparametric MRI

RATIONALE AND OBJECTIVES

To preoperatively predict residual tumor (RT) in patients with high-grade serous ovarian carcinoma (HGSOC) via a radiomic-clinical nomogram.

METHODS

A total of 128 patients with advanced HGSOC were enrolled (training cohort: n=106; validation cohort: n=22). Serum cancer antigen-125 (CA125), serum human epididymis protein 4 (HE-4) level, and neutrophil-to-lymphocyte ratio (NLR) were obtained from the medical records. Metastases in abdomen and pelvis (MAP) of HGSOC patients was evaluated and scored based on preoperative abdominal and pelvic enhanced CT, MRI and/or PET-CT. A volume of interest (VOI) of each tumor was manually contoured along the boundary slice-by-slice. Radiomic features were extracted from the T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) images. Univariate and multivariate analyses were used to determine the independent predictors of RT status. Least absolute shrinkage and selection operator (LASSO) logistic regression was performed to select optimal features and construct radiomic models. A radiomic-clinical nomogram incorporating radiomic signature and clinical parameters was developed and evaluated in training and validation cohorts.

RESULTS

MAP score (p = 0.002), HE-4 level (p = 0.001) and NLR (p = 0.008) were independent predictors of RT status. The final radiomic-clinical nomogram showed satisfactory prediction performance in training (AUC = 0.936), cross validation (AUC = 0.906) and separate validation cohorts (AUC = 0.900), and fitted well in calibration curves (p > 0.05). Decision curve further confirmed the clinical application value of the nomogram.

CONCLUSION

The proposed MRI-based radiomic-clinical nomogram achieved excellent preoperative prediction of the RT status in HGSOC.

Preoperative prediction of miliary changes in the small bowel mesentery in advanced high-grade serous ovarian cancer using MRI radiomics nomogram

PURPOSE

To develop and validate an MRI-based radiomics nomogram for the preoperative prediction of miliary changes in the small bowel mesentery (MCSBM) in advanced high-grade serous ovarian cancer (HGSOC).

MATERIALS AND METHODS

One hundred and twenty-eight patients with pathologically proved  advanced HGSOC (training cohort: n = 91; validation cohort: n = 37) were retrospectively included. All patients were initially evaluated as MCSBM-negative by preoperative imaging modalities but were finally confirmed by surgery and histopathology (MCSBM-positive: n = 53; MCSBM-negative: n = 75). Five radiomics signatures were built based on the features from multisequence magnetic resonance images. Independent clinicoradiological factors and radiomics-fusion signature were further integrated to construct a radiomics nomogram. The performance of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves and clinical utility.

RESULTS

Radiomics signatures, ascites, and tumor size were independent predictors of MCSBM. A nomogram integrating radiomics features and clinicoradiological factors demonstrated satisfactory predictive performance with areas under the curves (AUCs) of 0.871 (95% CI 0.801-0.941) and 0.858 (95% CI 0.739-0.976) in the training and validation cohorts, respectively. The net reclassification index (NRI) and integrated discrimination improvement (IDI) revealed that the nomogram had a significantly improved ability compared with the clinical model in the training cohort (NRI = 0.343, p = 0.002; IDI = 0.299, p < 0.001) and validation cohort (NRI = 0.409, p = 0.015; IDI = 0.283, p = 0.001).

CONCLUSION

Our proposed nomogram has the potential to serve as a noninvasive tool for the prediction of MCSBM, which is helpful for the individualized assessment of advanced HGSOC patients.

Diffusion-Weighted Magnetic Resonance Imaging and Morphological Characteristics Evaluation for Outcome Prediction of Primary Debulking Surgery for Advanced High-Grade Serous Ovarian Carcinoma

BACKGROUND

Preoperative assessment of whether a successful primary debulking surgery (PDS) can be performed in patients with advanced high-grade serous ovarian carcinoma (HGSOC) remains a challenge. A reliable model to precisely predict resectability is highly demanded.

PURPOSE

To investigate the value of diffusion-weighted MRI (DW-MRI) combined with morphological characteristics to predict the PDS outcome in advanced HGSOC patients.

STUDY TYPE

Prospective.

SUBJECTS

A total of 95 consecutive patients with histopathologically confirmed advanced HGSOC (ranged from 39 to 77 years).

FIELDS STRENGTH/SEQUENCE

A 3.0 T, readout-segmented echo-planar DWI.

ASSESSMENT

The MRI morphological characteristics of the primary ovarian tumor, a peritoneal carcinomatosis index (PCI) derived from DWI (DWI-PCI) and histogram analysis of the primary ovarian tumor and the largest peritoneal carcinomatosis were assessed by three radiologists. Three different models were developed to predict the resectability, including a clinicoradiologic model combing MRI morphological characteristic with ascites and CA125 level; DWI-PCI alone; and a fusion model combining the clinical-morphological information and DWI-PCI.

STATISTICAL TESTS

Multivariate logistic regression analyses, receiver operating characteristic (ROC) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI) were used. A P < 0.05 was considered to be statistically significant.

RESULTS

Sixty-seven cases appeared as a definite mass, whereas 28 cases as an infiltrative mass. The morphological characteristics and DWI-PCI were independent factors for predicting the resectability, with an AUC of 0.724 and 0.824, respectively. The multivariable predictive model consisted of morphological characteristics, CA-125, and the amount of ascites, with an incremental AUC of 0.818. Combining the application of a clinicoradiologic model and DWI-PCI showed significantly higher AUC of 0.863 than the ones of each of them implemented alone, with a positive NRI and IDI.

DATA CONCLUSIONS

The combination of two clinical factors, MRI morphological characteristics and DWI-PCI provide a reliable and valuable paradigm for the noninvasive prediction of the outcome of PDS.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Association between High Diffusion-Weighted Imaging-Derived Functional Tumor Burden of Peritoneal Carcinomatosis and Overall Survival in Patients with Advanced Ovarian Carcinoma

Objective

To investigate the association between functional tumor burden of peritoneal carcinomatosis (PC) derived from diffusion-weighted imaging (DWI) and overall survival in patients with advanced ovarian carcinoma (OC).

Materials and Methods

This prospective study was approved by the local research ethics committee, and informed consent was obtained. Fifty patients (mean age ± standard deviation, 57 ± 12 years) with stage III–IV OC scheduled for primary or interval debulking surgery (IDS) were recruited between June 2016 and December 2021. DWI (b values: 0, 400, and 800 s/mm²) was acquired with a 16-channel phased-array torso coil. The functional PC burden on DWI was derived based on K-means clustering to discard fat, air, and normal tissue. A score similar to the surgical peritoneal cancer index was assigned to each abdominopelvic region, with additional scores assigned to the involvement of critical sites, denoted as the functional peritoneal cancer index (fPCI). The apparent diffusion coefficient (ADC) of the largest lesion was calculated. Patients were dichotomized by immediate surgical outcome into high- and low-risk groups (with and without residual disease, respectively) with subsequent survival analysis using the Kaplan-Meier curve and log-rank test. Multivariable Cox proportional hazards regression was used to evaluate the association between DWI-derived results and overall survival.

Results

Fifteen (30.0%) patients underwent primary debulking surgery, and 35 (70.0%) patients received neoadjuvant chemotherapy followed by IDS. Complete tumor debulking was achieved in 32 patients. Patients with residual disease after debulking surgery had reduced overall survival (p = 0.043). The fPCI/ADC was negatively associated with overall survival when accounted for clinicopathological information with a hazard ratio of 1.254 for high fPCI/ADC (95% confidence interval, 1.007–1.560; p = 0.043).

Conclusion

A high DWI-derived functional tumor burden was associated with decreased overall survival in patients with advanced OC.

Past, Present, and Future of Serum Tumor Markers in Management of Ovarian Cancer: A Guide for the Radiologist

The ability to accurately detect early ovarian cancer and subsequently monitor treatment response is essential to improving survival for patients with ovarian malignancies. Several serum tumor markers (STMs)-including cancer antigen 125 (CA-125), human epididymis protein 4 (HE4), cancer antigen 19-9 (CA 19-9), and carcinoembryonic antigen (CEA)-have been used as a noninvasive method of identifying ovarian cancer in conjunction with imaging. Although current guidelines do not recommend use of STMs as screening tools for ovarian cancer, these markers have clinical utility in both diagnosis and surveillance for women with ovarian cancer. CA-125 is the most commonly used STM; its level may be elevated in several types of ovarian cancer, including epithelial cell tumors, carcinosarcoma, teratomas, and secondary ovarian malignancies. An elevated level of CA 19-9 is associated with clear cell tumors, teratomas, and secondary malignancies. CEA is most commonly associated with mucinous ovarian cancers. Finally, HE4 is being increasingly used to identify certain subtypes of epithelial ovarian cancers, particularly serous and endometrioid tumors. Diagnosis of ovarian cancers relies on a combination of CA-125 levels and US findings, which include a large adnexal mass or high-risk features, including septa and increased vascularity. CT is preferred for staging and is used along with PET and STM monitoring for surveillance. Increasingly, MRI is being used to characterize ovarian lesions that are indeterminate at US or CT. The future of STM testing involves development of "liquid biopsies," in which plasma samples are analyzed for evidence of tumors, including circulating tumor DNA or tumor cells and tumor micro-RNA. When combined with traditional imaging techniques, liquid biopsies may lead to earlier diagnosis and improved survival. An invited commentary by Shinagare is available online. ^©RSNA, 2021.

Diffusion-weighted MRI and PET/CT reproducibility in epithelial ovarian cancers during neoadjuvant chemotherapy

PURPOSE

To investigate the reproducibility of diffusion-weighted (DW) MRI and ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG)-Positron emission tomography/CT (PET/CT) in monitoring response to neoadjuvant chemotherapy in epithelial ovarian cancer.

MATERIALS AND METHODS

Ten women (median age, 67 years; range: 41.8-77.3 years) with stage IIIC-IV epithelial ovarian cancers were included in this prospective trial (NCT02792959) between 2014 and 2016. All underwent initial laparoscopic staging, four cycles of carboplatine-paclitaxel-based chemotherapy and interval debulking surgery. PET/CT and DW-MRI were performed at baseline (C0), after one cycle (C1) and before surgery (C4). Two nuclear physicians and two radiologists assessed five anatomic sites for the presence of ≥1 lesion. Target lesions in each site were defined and their apparent diffusion coefficient (ADC), maximal standardized uptake value (SUV-max), SUV-mean, SUL-peak, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were monitored (i.e., 10 patients ×5 sites ×3 time-points). Their relative early and late changes were calculated. Intra/inter-observer reproducibilities of qualitative and quantitative analysis were estimated with Kappa and intra-class correlation coefficients (ICCs).

RESULTS

For both modalities, inter- and intra-observer agreement percentages were excellent for initial staging but declined later for DW-MRI, leading to lower Kappa values for inter- and intra-observer variability (0.949 and 1 at C0, vs. 0.633 and 0.643 at C4, respectively) while Kappa values remained>0.8 for PET/CT. Inter- and intra-observer ICCs were>0.75 for SUV-max, SUL-peak, SUV-mean and their change regardless the time-point. ADC showed lower ICCs (range: 0.013-0.811). ANOVA found significant influences of the evaluation time, the measurement used (ADC, SUV-max, SUV-mean, SUV-max, SUL-peak, MTV or TLG) and their interaction on ICC values (P=0.0023, P<0.0001 and P =0.0028, respectively).

CONCLUSION

While both modalities demonstrated high reproducibility at baseline, only SUV-max, SUL-peak, SUV-mean and their changes maintained high reproducibility during chemotherapy.

Noninvasive prediction of residual disease for advanced high-grade serous ovarian carcinoma by MRI-based radiomic-clinical nomogram

OBJECTIVES

To develop a preoperative MRI-based radiomic-clinical nomogram for prediction of residual disease (RD) in patients with advanced high-grade serous ovarian carcinoma (HGSOC).

METHODS

In total, 217 patients with advanced HGSOC were enrolled from January 2014 to June 2019 and randomly divided into a training set (n = 160) and a validation set (n = 57). Finally, 841 radiomic features were extracted from each tumor on T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) sequence, respectively. We used two fusion methods, the maximal volume of interest (MV) and the maximal feature value (MF), to fuse the radiomic features of bilateral tumors, so that patients with bilateral tumors have the same kind of radiomic features as patients with unilateral tumors. The radiomic signatures were constructed by using mRMR method and LASSO classifier. Multivariable logistic regression analysis was used to develop a radiomic-clinical nomogram incorporating radiomic signature and conventional clinico-radiological features. The performance of the nomogram was evaluated on the validation set.

RESULTS

In total, 342 tumors from 217 patients were analyzed in this study. The MF-based radiomic signature showed significantly better prediction performance than the MV-based radiomic signature (AUC = 0.744 vs. 0.650, p = 0.047). By incorporating clinico-radiological features and MF-based radiomic signature, radiomic-clinical nomogram showed favorable prediction ability with an AUC of 0.803 in the validation set, which was significantly higher than that of clinico-radiological signature and MF-based radiomic signature (AUC = 0.623, 0.744, respectively).

CONCLUSIONS

The proposed MRI-based radiomic-clinical nomogram provides a promising way to noninvasively predict the RD status.

KEY POINTS

• MRI-based radiomic-clinical nomogram is feasible to noninvasively predict residual disease in patients with advanced HGSOC. • The radiomic signature based on MF showed significantly better prediction performance than that based on MV. • The radiomic-clinical nomogram showed a favorable prediction ability with an AUC of 0.803.

Assessment of peritoneal metastases with DW-MRI, CT, and FDG PET/CT before cytoreductive surgery for advanced stage epithelial ovarian cancer

BACKGROUND

Preoperative assessment of peritoneal metastases is an important factor for treatment planning and selection of candidates for cytoreductive surgery (CRS) in primary advanced stage (FIGO stages III-IV) epithelial ovarian cancer (EOC). The primary aim was to evaluate the efficacy of DW-MRI, CT, and FDG PET/CT used for preoperative assessment of peritoneal cancer index (PCI).

MATERIAL AND METHODS

In this prospective observational cohort study, 50 advanced stage EOC patients were examined with DW-MRI and FDG PET/CT with contrast enhanced CT as part of the diagnostic program. All patients were deemed amenable for upfront CRS. Imaging PCI was determined for DW-MRI, CT, and FDG PET/CT by separate readers blinded to the surgical findings. The primary outcome was agreement between the imaging PCI and PCI determined at surgical exploration (the reference standard) evaluated with Bland-Altman statistics.

RESULTS

The median surgical PCI was 18 (range: 3-32). For all three imaging modalities, the imaging PCI most often underestimated the surgical PCI. The mean differences between the surgical PCI and the imaging PCI were 4.2 (95% CI: 2.6-5.8) for CT, 4.4 (95% CI: 2.9-5.8) for DW-MRI, and 5.3 (95% CI: 3.6-7.0) for FDG PET/CT, and no overall statistically significant differences were found between the imaging modalities (DW-MRI - CT, p = 0.83; DW-MRI - FDG PET/CT, p = 0.24; CT - FDG PET/CT, p = 0.06).

CONCLUSION

Neither DW-MRI nor CT nor FDG PET/CT was superior in preoperative assessment of the surgical PCI in patients scheduled for upfront CRS for advanced stage EOC.