Literature DB >> 28546700

Advanced Primary Epithelial Ovarian and Peritoneal Carcinoma-Does Diagnostic Accuracy of Preoperative CT Scan for Detection of Peritoneal Metastatic Sites Reflect into Prediction of Suboptimal Debulking? A Prospective Study.

Kiran Bagul1, D K Vijaykumar1, Anupama Rajanbabu1, Mitchelle Aline Antony1, Venkatesan Ranganathan1.   

Abstract

Ovarian cancer is the seventh most common cancer in females worldwide. Optimal debulking is the standard treatment but possible only in 30-85% of advanced stages. Knowing exactly the disease extent preoperatively may predict suboptimal debulking. We analyzed diagnostic accuracy of preoperative CT scan in disease mapping and prediction of suboptimal debulking in a prospective observational study from March 2013 to May 2015 in a tertiary hospital. Adults below the age of 75 years with ECOG PS-0, 1, 2, clinically/radiologically newly diagnosed stage IIIc epithelial ovarian (EOC), and primary peritoneal carcinoma (PPC) were included. Neoadjuvant chemotherapy recipients were excluded. Preoperative multidetector CT (MDCT) scan showing deposits at 19 predetermined abdominopelvic sites were compared with the same sites seen at laparotomy and corresponding accuracies of CT scan calculated. Primary debulking surgery was done to achieve debulking to nil or less than 1-cm residual disease. Stepwise logistic regression models were used to determine the frequent suboptimal debulking sites and the predictive performance of the clinical and CT scan findings. A total of 36 patients were enrolled. The optimal debulking rate was 50%. The CT scan could detect the disease-bearing sites with overall sensitivity of 68.29%, specificity of 89%, accuracy of 78.07%, and positive and negative predictive values of 99 and 50.1%, respectively. Upon multivariate analysis, bowel mesentery (p 0.011) and omental extension (p 0.025) were associated with suboptimal debulking. CT scan accuracy at these sites (predictive performance) was 86.1%. We identified small bowel mesentery and omental extension (to spleen/stomach/colon) as sites associated with suboptimal debulking. MDCT accurately depicts peritoneal metastases, although sensitivity is reduced in certain areas of significance for optimal debulking. Further validation with more number of patients is warranted.

Entities:  

Keywords:  Computed tomography; Debulking surgical procedures; Diagnostic accuracy; Ovarian cancer

Year:  2017        PMID: 28546700      PMCID: PMC5427033          DOI: 10.1007/s13193-016-0601-6

Source DB:  PubMed          Journal:  Indian J Surg Oncol        ISSN: 0975-7651


  31 in total

1.  Pre-operative evaluation of peritoneal deposits using multidetector computed tomography in ovarian cancer.

Authors:  S H Chandrashekhara; S Thulkar; D N Srivastava; L Kumar; R Hariprasad; S Kumar; M C Sharma
Journal:  Br J Radiol       Date:  2010-09-21       Impact factor: 3.039

2.  Complete cytoreductive surgery is feasible and maximizes survival in patients with advanced epithelial ovarian cancer: a prospective study.

Authors:  S M Eisenkop; R L Friedman; H J Wang
Journal:  Gynecol Oncol       Date:  1998-05       Impact factor: 5.482

3.  Maximal cytoreductive effort in epithelial ovarian cancer surgery.

Authors:  Karin K Shih; Dennis S Chi
Journal:  J Gynecol Oncol       Date:  2010-06-30       Impact factor: 4.401

4.  Multi-institutional reciprocal validation study of computed tomography predictors of suboptimal primary cytoreduction in patients with advanced ovarian cancer.

Authors:  Allison E Axtell; Margaret H Lee; Robert E Bristow; Sean C Dowdy; William A Cliby; Steven Raman; John P Weaver; Mojan Gabbay; Michael Ngo; Scott Lentz; Ilana Cass; Andrew J Li; Beth Y Karlan; Christine H Holschneider
Journal:  J Clin Oncol       Date:  2007-02-01       Impact factor: 44.544

5.  A model for predicting surgical outcome in patients with advanced ovarian carcinoma using computed tomography.

Authors:  R E Bristow; L R Duska; N C Lambrou; E K Fishman; M J O'Neill; E L Trimble; F J Montz
Journal:  Cancer       Date:  2000-10-01       Impact factor: 6.860

6.  Identification and quantification of peritoneal metastases in patients with ovarian cancer with multidetector computed tomography: correlation with surgery and surgical outcome.

Authors:  Ur Metser; Colin Jones; Lindsay M Jacks; Marcus Q Bernardini; Sarah Ferguson
Journal:  Int J Gynecol Cancer       Date:  2011-11       Impact factor: 3.437

7.  The utility of computed tomography scans in predicting suboptimal cytoreductive surgery in women with advanced ovarian carcinoma.

Authors:  Sean C Dowdy; Sally A Mullany; Kathy R Brandt; Bonnie J Huppert; William A Cliby
Journal:  Cancer       Date:  2004-07-15       Impact factor: 6.860

8.  Tumor residual after surgical cytoreduction in prediction of clinical outcome in stage IV epithelial ovarian cancer: a Gynecologic Oncology Group Study.

Authors:  William E Winter; G Larry Maxwell; Chunqiao Tian; Michael J Sundborg; G Scott Rose; Peter G Rose; Stephen C Rubin; Franco Muggia; William P McGuire
Journal:  J Clin Oncol       Date:  2007-11-19       Impact factor: 44.544

9.  A multicenter prospective trial evaluating the ability of preoperative computed tomography scan and serum CA-125 to predict suboptimal cytoreduction at primary debulking surgery for advanced ovarian, fallopian tube, and peritoneal cancer.

Authors:  Rudy S Suidan; Pedro T Ramirez; Debra M Sarasohn; Jerrold B Teitcher; Svetlana Mironov; Revathy B Iyer; Qin Zhou; Alexia Iasonos; Harold Paul; Masayoshi Hosaka; Carol A Aghajanian; Mario M Leitao; Ginger J Gardner; Nadeem R Abu-Rustum; Yukio Sonoda; Douglas A Levine; Hedvig Hricak; Dennis S Chi
Journal:  Gynecol Oncol       Date:  2014-07-11       Impact factor: 5.482

10.  Prognostic factors for stage III epithelial ovarian cancer: a Gynecologic Oncology Group Study.

Authors:  William E Winter; G Larry Maxwell; Chunqiao Tian; Jay W Carlson; Robert F Ozols; Peter G Rose; Maurie Markman; Deborah K Armstrong; Franco Muggia; William P McGuire
Journal:  J Clin Oncol       Date:  2007-08-20       Impact factor: 44.544

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  1 in total

1.  Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

Authors:  Huanchun Yao; Xinglong Zhang
Journal:  Biomed Res Int       Date:  2022-10-11       Impact factor: 3.246

  1 in total

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