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

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.

CT-based deep learning model: a novel approach to the preoperative staging in patients with peritoneal metastasis

Peritoneal metastasis (PM) is a frequent manifestation of advanced abdominal malignancies. Accurately assessing the extent of PM before surgery is essential for patients to receive optimal treatment. Therefore, we propose to construct a deep learning (DL) model based on enhanced computed tomography (CT) images to stage PM preoperatively in patients. All 168 patients with PM underwent contrast-enhanced abdominal CT before either open surgery or laparoscopic exploration, and peritoneal cancer index (PCI) was used to evaluate patients during the surgical procedure. DL features were extracted from portal venous-phase abdominal CT scans and subjected to feature selection using the Spearman correlation coefficient and LASSO. The performance of models for preoperative staging was assessed in the validation cohort and compared against models based on clinical and radiomics (Rad) signature. The DenseNet121-SVM model demonstrated strong patient discrimination in both the training and validation cohorts, achieving AUC was 0.996 in training and 0.951 validation cohort, which were both higher than those of the Clinic model and Rad model. Decision curve analysis (DCA) showed that patients could potentially benefit more from treatment using the DL-SVM model, and calibration curves demonstrated good agreement with actual outcomes. The DL model based on portal venous-phase abdominal CT accurately predicts the extent of PM in patients before surgery, which can help maximize the benefits of treatment and optimize the patient's treatment plan.

Systematic review of diagnostic tools for peritoneal metastasis in gastric cancer-staging laparoscopy and its alternatives

BACKGROUND

Gastric cancer is one of the leading causes of cancer burden and mortality, often resulting in peritoneal metastasis in advanced stages with negative survival outcomes. Staging laparoscopy has become standard practice for suspected cases before a definitive gastrectomy or palliation. This systematic review aims to compare the efficacy of other diagnostic modalities instead of staging laparoscopy as the alternatives are able to reduce cost and invasive staging procedures. Recently, a radiomic model based on computed tomography and positron emission tomography (PET) has also emerged as another method to predict peritoneal metastasis.

AIM

To determine if the efficacy of computed tomography, magnetic resonance imaging and PET is comparable with staging laparoscopy.

METHODS

Articles comparing computed tomography, PET, magnetic resonance imaging, and radiomic models based on computed tomography and PET to staging laparoscopies were filtered out from the Cochrane Library, EMBASE, PubMed, Web of Science, and Reference Citations Analysis (https://www.referencecitationanalysis.com/). In the search for studies comparing computed tomography (CT) to staging laparoscopy, five retrospective studies and three prospective studies were found. Similarly, five retrospective studies and two prospective studies were also included for papers comparing CT to PET scans. Only one retrospective study and one prospective study were found to be suitable for papers comparing CT to magnetic resonance imaging scans.

RESULTS

Staging laparoscopy outperformed computed tomography in all measured aspects, namely sensitivity, specificity, positive predictive value and negative predictive value. Magnetic resonance imaging and PET produced mixed results, with the former shown to be only marginally better than computed tomography. CT performed slightly better than PET in most measured domains, except in specificity and true negative rates. We speculate that this may be due to the limited F-fluorodeoxyglucose uptake in small peritoneal metastases and in linitis plastica. Radiomic modelling, in its current state, shows promise as an alternative for predicting peritoneal metastases. With further research, deep learning and radiomic modelling can be refined and potentially applied as a preoperative diagnostic tool to reduce the need for invasive staging laparoscopy.

CONCLUSION

Staging laparoscopy was superior in all measured aspects. However, associated risks and costs must be considered. Refinements in radiomic modelling are necessary to establish it as a reliable screening technique.

Construction of a nomogram model for predicting peritoneal metastasis in gastric cancer: focused on cardiophrenic angle lymph node features

BACKGROUND

A different treatment was used when peritoneal metastases (PM) occurred in patients with gastric cancer (GC). Certain cancers' peritoneal metastasis could be predicted by the cardiophrenic angle lymph node (CALN). This study aimed to establish a predictive model for PM of gastric cancer based on the CALN.

METHODS

Our center retrospectively analyzed all GC patients between January 2017 and October 2019. Pre-surgery computed tomography (CT) scans were performed on all patients. The clinicopathological and CALN features were recorded. PM risk factors were identified via univariate and multivariate logistic regression analyses. The receiver operator characteristic (ROC) curves were generated using these CALN values. Using the calibration plot, the model fit was assessed. A decision curve analysis (DCA) was conducted to assess the clinical utility.

RESULTS

126 of 483 (26.1%) patients were confirmed as having peritoneal metastasis. These relevant factors were associated with PM: age, sex, T stage, N stage, enlarged retroperitoneal lymph nodes (ERLN), CALN, the long diameter of the largest CALN (LD of LCALN), the short diameter of the largest CALN (SD of LCALN), and the number of CALNs (N of CALNs). The multivariate analysis illustrated that the LD of LCALN (OR = 2.752, p < 0.001) was PM's independent risk factor in GC patients. The area under the curve (AUC) of the model was 0.907 (95% CI 0.872-0.941), demonstrating good performance in the predictive value of PM. There is excellent calibration evident from the calibration plot, which is close to the diagonal. The DCA was presented for the nomogram.

CONCLUSION

CALN could predict gastric cancer peritoneal metastasis. The model in this study provided a powerful predictive tool for determining PM in GC patients and helping clinicians allocate treatment.

CT characteristics for predicting prognosis of gastric cancer with synchronous peritoneal metastasis

Introduction

To explore the CT characteristics for the prediction of long term survival in gastric cancer patients with synchronous peritoneal metastasis (PM).

Materials and methods

Sixty-six patients diagnosed as gastric cancer with synchronous peritoneum metastasis were enrolled in this retrospective study. Ten anatomic peritoneal regions were evaluated to check for the signs of PM on CT. One positive area equaled one score. The CT characteristic-based PM score (CT-PMS) was the sum of the total points assigned to all 10 regions, with a range of 0-10. The triple tract dilatation (TTD) sign caused by peritoneal metastasis, the presence of extensive lymph node metastasis (ELM), and the grade of ascites were recorded. The overall survival (OS) was used as the prognostic indicator. The performance of the CT characteristics was assessed by the Kaplan-Meier analysis and Cox proportional hazards model, while its reproducibility was evaluated by Kappa statistic and weighted Kappa statistic.

Results

Patients with a CT-PMS of 3-10 had significantly poorer OS (P = .02). Patients with either the presence of TTD sign, or ELM had a trend toward unfavorable OS (both P = .07), and when CT-PMS of 3-10 was detected simultaneously, the survival was further reduced (P = .00 for TTD sign; P = .01 for ELM). The grade of ascites failed to show a significant correlation with OS. The interobserver reproducibility for assessing the CT-PMS, the presence of TTD sign, the presence of ELM, and the grade of ascites had a substantial to almost perfect agreement.

Conclusion

The prognosis of gastric cancer patients with PM has a correlation with the extent of metastasis dissemination on baseline CT. A CT-PMS of 3-10 is associated with a worse prognosis than that of 0-2. The presence of TTD sign and ELM may help further select patients with extraordinarily poor prognoses.

Evaluation of serum CA125-Tn glycoform in peritoneal dissemination and surgical completeness of high-grade serous ovarian cancer

BACKGROUND

Peritoneal dissemination is the predominant feature of malignant progression in ovarian cancer and is a major cause of poor surgical outcomes and clinical prognoses. Abnormal glycosylation of carbohydrate antigen 125 (CA125) may be involved in peritoneal implantation and metastasis. Here, we evaluated the clinical relevance of CA125-Tn glycoform in the assessment of high-grade serous ovarian cancer (HGSOC).

METHODS

A total of 72 patients diagnosed with HGSOC were included. Pre-treatment serum CA125-Tn levels were measured using an antibody-lectin enzyme-linked immunosorbent assay. The association of CA125-Tn with clinical factors was analyzed in all cases, whereas its association with peritoneal dissemination, residual disease, and progression-free survival was analyzed in stage III-IV cases.

RESULTS

Pre-treatment serum CA125-Tn levels were significantly higher in advanced-stage HGSOC patients than in early-stage patients (P = 0.029). In advanced-stage patients, the pre-treatment CA125-Tn level increased with an increase in Fagotti's score (P = 0.004) and with the extension of peritoneal dissemination (P = 0.011). The pre-treatment CA125-Tn level increased with the volume of residual disease (P = 0.005). The association between CA125-Tn level and suboptimal surgery remained significant even after adjustment for treatment type and stage. Pre-treatment CA125-Tn levels were also related to disease recurrence.

CONCLUSION

Serum CA125-Tn level could be a novel biomarker for peritoneal dissemination and a promising predictor of surgical completeness in ovarian cancer. Patients with lower CA125-Tn levels were more likely to have no residual disease. CA125-Tn could help surgeons to adopt optimized treatment strategies for patients with advanced ovarian cancer as a pre-treatment evaluator.

Role and usefulness of mr imaging in the assessment of peritoneal carcinomatosis

BACKGROUND

For many years, peritoneal carcinomatosis (PC) entitled poor prognosis until the development of the cytoreductive surgery technique associated with hyperthermic intraperitoneal chemotherapy. Imaging of peritoneal carcinomatosis plays an essential role in the diagnosis and management of the patients being considered for cytoreductive surgery (CRS) and heated intraperitoneal chemotherapy (HIPEC).

MAIN BODY

The key role of imaging in patients with peritoneal malignancy is to aid surgical decision making. A standardized peritoneal magnetic resonance (MR) imaging protocol, including T2-weighted fat suppressed, diffusion-weighted and gadolinium-enhanced sequences, allows to detect small peritoneal tumours that are often missed on other imaging. A systematic approach to MR imaging and a close collaboration between the radiologist and the oncologic surgeon are key elements for an accurate evaluation of candidate patients for CRS and HIPEC.

CONCLUSION

MR imaging provides a powerful tool for accurate preoperative imaging in patients considered for curative surgery and assists the surgeon in evaluating patients for CRS and HIPEC.

Spectral CT in peritoneal carcinomatosis from ovarian cancer: a tool for differential diagnosis of small nodules?

The detection of peritoneal carcinomatosis in patients with ovarian cancer is crucial to establish the correct therapeutic planning (debulking surgery versus neoadjuvant chemotherapy).

Often, however, the nodules of peritoneal carcinomatosis are very small in size or have a reticular appearance that can mimic the fat stranding that is typical of acute inflammation conditions. Our hypothesis is that the use of dual-layer spectral computed tomography with its applications, such as virtual monoenergetic imaging and Z-effective imaging, might improve the detection and the characterisation of peritoneal nodules, increasing sensitivity and diagnostic accuracy, as recently described for other oncological diseases.

Imaging of Gastric Carcinomatosis

Diagnosing the absence or presence of peritoneal carcinomatosis in patients with gastric cancer, including its extent and distribution, is an essential step in patients' therapeutic management. Such diagnosis still remains a radiological challenge. In this article, we review the strengths and weaknesses of the different imaging techniques for the diagnosis of peritoneal carcinomatosis of gastric origin as well as the techniques' imaging features. We also discuss the assessment of response to treatment and present recommendations for the follow-up of patients with complete surgical resection according to the presence of risk factors of recurrence, as well as discussing future directions for imaging improvement.