Development of survival predictors for high-grade serous ovarian cancer based on stable radiomic features from computed tomography images.
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ABSTRACT:
SUBMITTER: Hu J
PROVIDER: S-EPMC9254345 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:High-grade serous ovarian cancer (HGSOC) is an aggressive disease with different clinical outcomes and poor prognosis. This could be due to tumor heterogeneity. The 18F-FDG PET radiomic parameters permit addressing tumor heterogeneity. Nevertheless, this has been not well studied in ovarian cancer. The aim of our work was to assess the prognostic value of pretreatment 18F-FDG PET radiomic features in patients with HGSOC. A review of 36 patients diagnosed with advanced HGSOC between 2016 and 2020 in our center was performed. Radiomic features were obtained from pretreatment 18F-FDGPET. Disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with receiver operating characteristic curve/median values were used. A correlation between radiomic features and DFS/OS was made. The mean DFS was 19.6 months and OS was 37.1 months. Total Lesion Glycolysis (TLG), GLSZM_ Zone Size Non-Uniformity (GLSZM_ZSNU), and GLRLM_Run Length Non-Uniformity (GLRLM_RLNU) were significantly associated with DFS. The survival-curves analysis showed a significant difference of DSF in patients with GLRLM_RLNU > 7388.3 versus patients with lower values (19.7 months vs. 31.7 months, p = 0.035), maintaining signification in the multivariate analysis (p = 0.048). Moreover, Intensity-based Kurtosis was associated with OS (p = 0.027). Pretreatment 18F-FDG PET radiomic features GLRLM_RLNU, GLSZM_ZSNU, and Kurtosis may have prognostic value in patients with advanced HGSOC.
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Project description:Variability in the x-ray tube current used in computed tomography may affect quantitative features extracted from the images. To investigate these effects, we scanned the Credence Cartridge Radiomics phantom 12 times, varying the tube current from 25 to 300?mA?s while keeping the other acquisition parameters constant. For each of the scans, we extracted 48 radiomic features from the categories of intensity histogram (n?=?10), gray-level run length matrix (n?=?11), gray-level co-occurrence matrix (n?=?22), and neighborhood gray tone difference matrix (n?=?5). To gauge the size of the tube current effects, we scaled the features by the coefficient of variation of the corresponding features extracted from images of non-small cell lung cancer tumors. Variations in the tube current had more effect on features extracted from homogeneous materials (acrylic, sycamore wood) than from materials with more tissue-like textures (cork, rubber particles). Thirty-eight of the 48 features extracted from acrylic were affected by current reductions compared with only 2 of the 48 features extracted from rubber particles. These results indicate that variable x-ray tube current is unlikely to have a large effect on radiomic features extracted from computed tomography images of textured objects such as tumors.
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Project description:The present study aimed to describe the computed tomography (CT) imaging features of ovarian Brenner tumor for diagnostic accuracy and disease understanding. The CT imaging features of 9 cases of ovarian Brenner tumor confirmed by surgery and pathology were retrospectively analyzed and compared. Of the 9 cases of ovarian Brenner tumor, 3 were right located and 6 were left located with clear borders; 7 with round or oval shapes, while 2 were with irregular and lobulated morphology; 5 solid lesions presented with multiple scattered calcification shadows inside with moderate enhancement, while 3 cystic lesions were presented with mixed solid and cystic composition, and significant enhancement was identified in the solid component, but not in the cystic component. Furthermore, papillary projections inside and mild nodular enhancement were observed in one case of cystic lesion. The pathological analysis demonstrated that an epithelium nest composed the tumors with urothelial like cells and fibrous matrix. Of the 9 cases, 5 epithelial nests exhibited adeno-like cystic lumen without cell mitosis phase. All cases were diagnosed with benign ovarian Brenner tumor. Specific CT imaging features of ovarian Brenner tumor can be identified and pathological examinations are required for diagnosis confirmation.
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Project description:BACKGROUND:Relatively little is known about factors associated with long-term survival (LTS) following a diagnosis of ovarian cancer. METHODS:We conducted a retrospective study of high-grade serous ovarian cancer (HGSOC) to explore predictors of LTS (defined as ?7 years of survival) using electronic medical record data from a network of integrated health care systems. Multivariable logistic regression with forward selection was used to compare characteristics of women who survived ?7 years after diagnosis (n = 148) to those who died within 7 years of diagnosis (n = 494). RESULTS:Our final model included study site, age, stage at diagnosis, CA-125, comorbidity score, receipt of chemotherapy, BMI, and four separate comorbid conditions: weight loss, depression, hypothyroidism, and liver disease. Of these, only younger age, lower stage, and depression were statistically significantly associated with LTS. CONCLUSIONS:We did not identify any new characteristics associated with HGSOC survival. IMPACT:Prognosis of ovarian cancer generally remains poor. Large, pooled studies of ovarian cancer are needed to identify characteristics that may improve survival.
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Project description:ObjectivesThis study aims to evaluate the diagnostic performance of machine-learning-based contrast-enhanced CT radiomic analysis for categorizing benign and malignant ovarian tumors.MethodsA total of 1,329 patients with ovarian tumors were randomly divided into a training cohort (N=930) and a validation cohort (N=399). All tumors were resected, and pathological findings were confirmed. Radiomic features were extracted from the portal venous phase images of contrast-enhanced CT. The clinical predictors included age, CA-125, HE-4, ascites, and margin of tumor. Both radiomics model (including selected radiomic features) and mixed model (incorporating selected radiomic features and clinical predictors) were constructed respectively. Six classifiers [k-nearest neighbor (KNN), support vector machines (SVM), random forest (RF), logistic regression (LR), multi-layer perceptron (MLP), and eXtreme Gradient Boosting (XGBoost)] were used for each model. The mean relative standard deviation (RSD) and area under the receiver operating characteristic curve (AUC) were applied to evaluate and select the best classifiers. Then, the performances of the two models with selected classifiers were assessed in the validation cohort.ResultsThe MLP classifier with the least RSD (1.21 and 0.53, respectively) was selected as the best classifier in both radiomics and mixed models. The two models with MLP classifier performed well in the validation cohort, with the AUCs of 0.91 and 0.96 and with accuracies (ACCs) of 0.83 and 0.87, respectively. The Delong test showed that the AUC of mixed model was statistically different from that of radiomics model (p<0.001).ConclusionsMachine-learning-based CT radiomic analysis could categorize ovarian tumors with good performance preoperatively. The mixed model with MLP classifier may be a potential tool in clinical applications.
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Project description:Quantitative analysis of computed tomography (CT) radiomic features is an indirect measure of tumor heterogeneity, which has been associated with prognosis in human lung carcinoma. Canine lung tumors share similar features to human lung tumors and serve as a model in which to investigate the utility of radiomic features in differentiating tumor type and prognostication. The purpose of this study was to correlate first-order radiomic features from canine pulmonary tumors to histopathologic characteristics and outcome. Disease-free survival, overall survival time and tumor-specific survival were calculated as days from the date of CT scan. Sixty-seven tumors from 65 dogs were evaluated. Fifty-six tumors were classified as primary pulmonary adenocarcinomas and 11 were non-adenocarcinomas. All dogs were treated with surgical resection; 14 dogs received adjuvant chemotherapy. Second opinion histopathology in 63 tumors confirmed the histologic diagnosis in all dogs and further characterized 53 adenocarcinomas. The median overall survival time was longer (p = 0.004) for adenocarcinomas (339d) compared to non-adenocarcinomas (55d). There was wide variation in first-order radiomic statistics across tumors. Mean Hounsfield units (HU) ratio (p = 0.042) and median mean HU ratio (p = 0.042) were higher in adenocarcinomas than in non-adenocarcinomas. For dogs with adenocarcinoma, completeness of excision was associated with overall survival (p<0.001) while higher mitotic index (p = 0.007) and histologic score (p = 0.037) were associated with shorter disease-free survival. CT-derived tumor variables prognostic for outcome included volume, maximum axial diameter, and four radiomic features: integral total, integral total mean ratio, total HU, and max mean HU ratio. Tumor volume was also significantly associated with tumor invasion (p = 0.044). Further study of radiomic features in canine lung tumors is warranted as a method to non-invasively interrogate CT images for potential predictive and prognostic utility.
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Project description:High-grade serous ovarian cancer (HGSOC) likely originates from the fallopian tube (FT) epithelium. Here, we established 15 organoid lines from HGSOC primary tumor deposits that closely match the mutational profile and phenotype of the parental tumor. We found that Wnt pathway activation leads to growth arrest of these cancer organoids. Moreover, active BMP signaling is almost always required for generation of HGSOC organoids, while healthy fallopian tube organoids depend on BMP suppression by Noggin. Fallopian tube organoids modified by stable shRNA knockdown of p53, PTEN, and retinoblastoma protein (RB), also require a low-Wnt environment for long-term growth, while fallopian tube organoid medium triggers growth arrest. Thus, early changes in the stem cell niche environment are needed to support outgrowth of these genetically-altered cells. Indeed, comparative analysis of gene expression pattern and phenotypes of normal vs. loss-of-function organoids confirmed that depletion of tumor suppressors triggers changes in the regulation of stemness and differentiation.
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Project description:In the early 2000s a two-tier grading system was introduced for serous ovarian cancer. Since then, we have increasingly come to accept that low-grade serous ovarian carcinoma (LGSOC) is a separate entity with a unique mutational landscape and clinical behaviour. As less than 10% of serous carcinomas of the ovary are low-grade, they are present in only a small number of patients in clinical trials for ovarian cancer. Therefore the current treatment of LGSOC is based on smaller trials, retrospective series, and subgroup analysis of large clinical trials on ovarian cancer. Surgery plays a major role in the treatment of patients with LGSOC. In the systemic treatment of LGSOC, hormonal treatment and targeted therapies seem to play an important role.
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Project description:The aim of the present study was to investigate the imaging characteristics of ovarian fibrothecoma. The cases of 25 female patients with pathologically confirmed ovarian fibrothecomas were retrospectively reviewed. Tumor location, size, density, signal intensity, cystic degeneration, calcification, enhancement pattern and ascites were assessed by computed tomography (CT) (n=20) and magnetic resonance imaging (MRI) (n=5). Clinical and histological features were also evaluated. The results revealed that 23 (92.0%) patients were postmenopausal, with a mean age ± standard deviation (SD) of 60.7±10.8 years old. All 25 tumors were unilateral and a thickened endometrium was observed in 7 (28.0%) patients. In total, 24 (96.0%) tumors appeared to have well-defined boundaries, with 1 (4%) tumor exhibiting an obscure boundary. Tumors had a mean size of 9.8±5.3 cm. Solid and predominantly solid masses were found in 16 cases (64.0%), and cystic and predominantly cystic masses were found in 9 patients (36.0%). Solid regions of masses exhibited hypodensity or isodensity in 24 patients (96.0%), with 1 patient (4.0%) exhibiting hyperdensity. The mean CT value (± SD) was 44.2±12.8 HU (range, 31-79HU) in unenhanced images. All masses exhibited isointensity or slight hypointensity on T1-weighted imaging, and tumor parenchyma also exhibited slight hypointensity or isointensity on T2-weighted imaging compared with the myometrium, with or without areas of patchy hyperintensity. Contrast-enhanced CT or MRI scans were performed on 19 patients, and the solid components (94.7%) exhibited mild to moderate enhancement in 18 patients and 1 patient (5.3%) exhibited intense enhancement. Tumor size was positively correlated with the tumor cystic degeneration (r=0.77, P<0.001) and ascites (r=0.41, P<0.001). Therefore, ovarian fibrothecoma typically presents as solid or predominant solid masses with clear boundaries; the parenchyma of the tumor exhibits isodensity on CT scans, slight hypointensity or isointensity on MRI and mild enhancement following contrast-medium injection. The thickened endometrium observed in postmenopausal woman may also be a valuable imaging feature.
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