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.

Development and validation of radiomics nomogram for metastatic status of epithelial ovarian cancer.

To develop and validate an enhanced CT-based radiomics nomogram for evaluating preoperative metastasis risk of epithelial ovarian cancer (EOC). One hundred and nine patients with histologically confirmed EOC were retrospectively enrolled. The volume of interest (VOI) was delineated in preoperative enhanced CT images, and 851 radiomics features were extracted. The radiomics features were selected by the least absolute shrinkage and selection operator (LASSO), and the rad-score was calculated using the formula of the radiomics label. A clinical model, radiomics model, and combined model were constructed using the logistic regression classification algorithm. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the diagnostic performance of the models. Seventy-five patients (68.8%) were histologically confirmed to have metastasis. Eleven optimal radiomics features were retained by the LASSO algorithm to develop the radiomic model. The combined model for evaluating metastasis of EOC achieved area under the curve (AUC) values of 0.929 (95% CI 0.8593-0.9996) in the training cohort and 0.909 (95% CI 0.7921-1.0000) in the test cohort. To facilitate clinical use, a radiomic nomogram was built by combining the clinical characteristics with rad-score. The DCA indicated that the nomogram had the most significant net benefit when the threshold probability exceeded 15%, surpassing the benefits of both the treat-all and treat-none strategies. Compared with clinical model and radiomics model, the radiomics nomogram has the best diagnostic performance in evaluating EOC metastasis. The nomogram is a useful and convenient tool for clinical doctors to develop personalized treatment plans for EOC patients.

Challenges in Pharmacokinetic Modelling of [18F]fluoro-PEG-folate PET/CT Imaging in Epithelial Ovarian Cancer Patients.

PURPOSE: To describe the pharmacokinetic properties of the [18F]fluoro-polyethylene glycol(PEG)-folate radiotracer in PET/CT imaging of patients with advanced stage epithelial ovarian cancer (EOC). PROCEDURES: In five patients with advanced EOC (FIGO stage IIIB/IIIC, Fédération Internationale de Gynécologie et d'Obstétrique), a 90-min dynamic PET acquisition of the pelvis was performed directly after i.v. administration of 185 MBq [18F]fluoro-PEG6-folate. Arterial blood samples collected at nineteen timepoints were used to determine the plasma input function. A static volume of interest (VOI) for included tumor lesions was drawn manually on the PET images. Modelling was performed using PMOD software. Three different models (a 1-tissue compartment model (1T2k) and two 2-tissue compartment models, irreversible (2T3k) and reversible (2T4k)) were compared in goodness of fit with the time activity curves by means of the Akaike information criterion. RESULTS: The pharmacokinetic analysis in the pelvic area has proven to be much more challenging than expected. Only four out of 22 tumor lesions in five patients were considered suitable to perform modelling on. The remaining tumor lesions were inapt due to either low tracer uptake, small size, proximity to other [18F]fluoro-PEG6-folate -avid structures and/or displacement by abdominal organ motion in the dynamic scan. Data from the four analyzed tumor lesions suggest that the irreversible 2T3k may best describe the pharmacokinetics. All 22 lesions were immunohistochemically stained positive for the folate receptor alpha (FRα) after resection. CONCLUSION: Performing pharmacokinetic analysis in the abdominal pelvic region is very challenging. This brief article describes the challenges and pitfalls in pharmacokinetic analysis of a tracer with high physiological accumulation in the intestines, in case of lesions of limited size in the abdominal pelvic area.

Contrast-enhanced CT radiomics for preoperative prediction of stage in epithelial ovarian cancer: a multicenter study.

BACKGROUND: Preoperative prediction of International Federation of Gynecology and Obstetrics (FIGO) stage in patients with epithelial ovarian cancer (EOC) is crucial for determining appropriate treatment strategy. This study aimed to explore the value of contrast-enhanced CT (CECT) radiomics in predicting preoperative FIGO staging of EOC, and to validate the stability of the model through an independent external dataset. METHODS: A total of 201 EOC patients from three centers, divided into a training cohort (n = 106), internal (n = 46) and external (n = 49) validation cohorts. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used for screening radiomics features. Five machine learning algorithms, namely logistic regression, support vector machine, random forest, light gradient boosting machine (LightGBM), and decision tree, were utilized in developing the radiomics model. The optimal performing algorithm was selected to establish the radiomics model, clinical model, and the combined model. The diagnostic performances of the models were evaluated through receiver operating characteristic analysis, and the comparison of the area under curves (AUCs) were conducted using the Delong test or F-test. RESULTS: Seven optimal radiomics features were retained by the LASSO algorithm. The five radiomics models demonstrate that the LightGBM model exhibits notable prediction efficiency and robustness, as evidenced by AUCs of 0.83 in the training cohort, 0.80 in the internal validation cohort, and 0.68 in the external validation cohort. The multivariate logistic regression analysis indicated that carcinoma antigen 125 and tumor location were identified as independent predictors for the FIGO staging of EOC. The combined model exhibited best diagnostic efficiency, with AUCs of 0.95 in the training cohort, 0.83 in the internal validation cohort, and 0.79 in the external validation cohort. The F-test indicated that the combined model exhibited a significantly superior AUC value compared to the radiomics model in the training cohort (P < 0.001). CONCLUSIONS: The combined model integrating clinical characteristics and radiomics features shows potential as a non-invasive adjunctive diagnostic modality for preoperative evaluation of the FIGO staging status of EOC, thereby facilitating clinical decision-making and enhancing patient outcomes.

Association between the quantitative characteristics of dual-energy spectral CT and cytoreduction surgery outcome in patients with advanced epithelial ovarian cancers: A prospective observational study.

This study aimed to explore the association between the quantitative characteristics of dual-energy spectral CT and cytoreduction surgery outcome in patients with advanced epithelial ovarian carcinoma (EOC). In this prospective observational study, patients with advanced EOC (federation of gynecology and obstetrics stage III-IV) treated in the Department of Gynecological Oncology at our Hospital between June 2021 and March 2022 were enrolled. All participants underwent dual-energy spectral computed tomography (DECT) scanning 2 weeks before cytoreductive surgery. The quantitative data included peritoneal cancer index (PCI) determined by DECT, CT value at 70 keV, normalized iodine concentration, normalized water concentration, effective atomic number (effective-Z), and slopes of the spectral attenuation curves (slope λ Hounsfield unit). Fifty-five participants were included. The patients were 57.2 ±â€…9.8 years of age, and 72.7% were menopausal. The maximal diameter of tumors was 8.6 (range, 2.9-19.7) cm, and 76.4% were high-grade serous carcinomas. Optimal cytoreduction was achieved in 43 patients (78.2%). Compared with the optimal cytoreductive group, the suboptimal cytoreductive group showed a higher PCI (median, 21 vs 6, P < .001), higher 70 keV CT value (69.5 ±â€…16.6 vs 57.1 ±â€…13.0, P = .008), and higher slope λ Hounsfield unit (1.89 ±â€…0.66 vs 1.39 ±â€…0.60, P = .015). The multivariable analysis showed that the PCI (OR = 1.74, 95%CI: 1.24-2.44, P = .001) and 70 keV CT value (OR = 1.07, 95%CI: 1.01-1.13, P = .023) were independently associated with a suboptimal cytoreductive surgery. The area under the receiver operating characteristics curve of PCI and 70 keV CT value was 0.903 (95%CI: 0.805-1.000, P = .000) and 0.740 (95%CI: 0.581-0.899, P = .012), respectively. High PCI and 70 keV CT value are independently associated with suboptimal cytoreductive surgery in patients with advanced EOC. The PCI determined by DECT might be a better predictor for suboptimal cytoreduction.

Associating Peritoneal Metastasis With T2-Weighted MRI Images in Epithelial Ovarian Cancer Using Deep Learning and Radiomics: A Multicenter Study.

BACKGROUND: The preoperative diagnosis of peritoneal metastasis (PM) in epithelial ovarian cancer (EOC) is challenging and can impact clinical decision-making. PURPOSE: To investigate the performance of T2 -weighted (T2W) MRI-based deep learning (DL) and radiomics methods for PM evaluation in EOC patients. STUDY TYPE: Retrospective. POPULATION: Four hundred seventy-nine patients from five centers, including one training set (N = 297 [mean, 54.87 years]), one internal validation set (N = 75 [mean, 56.67 years]), and two external validation sets (N = 53 [mean, 55.58 years] and N = 54 [mean, 58.22 years]). FIELD STRENGTH/SEQUENCE: 1.5 or 3 T/fat-suppression T2W fast or turbo spin-echo sequence. ASSESSMENT: ResNet-50 was used as the architecture of DL. The largest orthogonal slices of the tumor area, radiomics features, and clinical characteristics were used to construct the DL, radiomics, and clinical models, respectively. The three models were combined using decision-level fusion to create an ensemble model. Diagnostic performances of radiologists and radiology residents with and without model assistance were evaluated. STATISTICAL TESTS: Receiver operating characteristic analysis was used to assess the performances of models. The McNemar test was used to compare sensitivity and specificity. A two-tailed P < 0.05 was considered significant. RESULTS: The ensemble model had the best AUCs, outperforming the DL model (0.844 vs. 0.743, internal validation set; 0.859 vs. 0.737, external validation set I) and clinical model (0.872 vs. 0.730, external validation set II). After model assistance, all readers had significantly improved sensitivity, especially for those with less experience (junior radiologist1, from 0.639 to 0.820; junior radiologist2, from 0.689 to 0.803; resident1, from 0.623 to 0.803; resident2, from 0.541 to 0.738). One resident also had significantly improved specificity (from 0.633 to 0.789). DATA CONCLUSIONS: T2W MRI-based DL and radiomics approaches have the potential to preoperatively predict PM in EOC patients and assist in clinical decision-making. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Cáncer de Ovario: Tamizaje y diagnóstico imagenológico / Ovarian Cancer: Screening and imaging diagnosis

Resumen El cáncer de ovario se ha caracterizado por ser la neoplasia ginecológica de peor pronóstico. Lo anterior es consecuencia del curso silente de la enfermedad que ocasiona que la mayoría de las veces el diagnóstico se realice en etapas avanzadas. La información recolectada señala que los avances terapéuticos no han demostrado ser efectivos en mejorar la sobrevida de las pacientes con cáncer de ovario, lo cual orienta a la búsqueda constante de un método (o conjunto de éstos), que permita llevar a cabo el tamizaje y la detección temprana de dicha patología. Sin embargo, debido a que actualmente no se ha logrado identificar un método que sea costo-efectivo para el tamizaje, el mismo no se aplica a la población general y se reserva para casos específicos, como mujeres con antecedentes familiares de la enfermedad o que presentan síndromes hereditarios. Esta revisión incluye además información sobre las diferentes técnicas de imagen utilizadas tanto para el estudio y caracterización de masas anexiales, como para el estadiaje y pronóstico del cáncer de ovario. De las técnicas estudiadas, el ultrasonido (US) demostró ser la mejor opción para el abordaje inicial de masas anexiales; sin embargo, a la hora de realizar el estadiaje resultó ser inferior a la tomografía computarizada (TC) y la resonancia magnética (RM).

Abstract Ovarian cancer is the gynecological malignancy with the worst prognosis. Due to the silent course of the disease the diagnosis is made mainly in advanced stages. The literature reviewed showed that the therapeutic advances have not shown any major improvement in patient´s survival with ovarian cancer, therefore there is a constant research for a technique (or a set of them) that allows a proper screening and early detection of the disease. However, a cost effective method has not been found for screening, therefore it is not recommended for general population and it is reserved for specific cases, such as women with family history of ovarian cancer and with hereditary syndromes. This review also includes information about the different imaging techniques available not only for the study and characterization of neoplasms, but also for staging and prognosis of ovarian cancer. The ultrasound proved to be the best option for the initial approach of adnexal masses, however it has shown to be inferior for staging than CT-Scan and MRI.

Carcinoma de ovario en paciente con mutación del gen BRCA1. Diagnóstico tras biopsia de adenopatía cervical, en el contexto de un síndrome paraneoplásico cutáneo / Ovarian carcinoma in a patient with a BRCA1 gene mutation. Diagnosis after biopsy of cervical adenopathy, in the context of a cutaneous paraneoplastic syndrome

RESUMEN El cáncer epitelial de ovario representa uno de los tumores ginecológicos más letales ya que más del 75% de las pacientes son diagnosticadas en estadío avanzado. Aún no se ha demostrado que la realización de pruebas y exámenes pélvicos rutinarios haya reducido la mortalidad, no existiendo actualmente, un cribado eficaz para su diagnóstico precoz. Aunque la sintomatología metastásica extraperitoneal más común es el derrame pleural, las linfadenopatías neoplásicas a nivel supraclavicular aparecen hasta en el 4% de casos, generalmente asociándose a un mal pronóstico. La identificación de una adenopatía supraclavicular se relaciona hasta en un 58-83% de los casos, con el hallazgo de una tumoración maligna. Por otro lado, la dermatomiositis del adulto puede tener un origen paraneoplásico en un 15-25% de las ocasiones, siendo el cáncer de mama y de ovario la etiología más frecuente en la población femenina. Las pacientes portadoras de mutaciones en los genes BRCA 1 y 2 tienen un aumento del riesgo de padecer neoplasias de mama y ovario. En aquellas afectas de un cáncer de ovario y portadoras de una mutación en los genes BRCA, no se debería plantear una cirugía profiláctica de rutina sobre la mama, al menos en los primeros 5 años tras el diagnóstico de la neoplasia ovárica. Presentamos el caso de una paciente portadora de una mutación germinal del gen BRCA 1, que debuta con un cáncer de ovario, tras el estudio de una adenopatía neoplásica de cuello, biopsiada en el contexto de un síndrome paraneoplásico cutáneo.

ABSTRACT Epithelial ovarian cancer represents one of the most lethal gynecological tumors, since more than 75% of affected women are diagnosed at an advanced stage. However, studies have not demonstrated yet that performing routine pelvic exams and tests had reduced mortality in ovarian cancer, and currently there is no effective screening for early diagnosis. The most common extraperitoneal metastatic symptomatology of ovarian cancer is pleural effusion, but there are other, like neoplastic lymphadenopathies at supraclavicular level, described in up to 4% of cases and generally related to a poor prognosis. The identification of a supraclavicular adenopathy is associated with the finding of a malignant tumor in 58-83% of the cases. On the other hand, adult dermatomyositis can have a paraneoplastic origin in 15-25% of patients, being breast and ovarian cancer the most frequent etiology in the female population. Patients with BRCA 1 and 2 genes mutations have an increased risk of breast and ovarian malignancies. In those affected by an ovarian cancer and carriers of a mutation in the BRCA genes, routine prophylactic surgery should not be considered on the breast, at least in the first 5 years after the diagnosis of ovarian neoplasia. We present the case of a patient with a germinal mutation of the BRCA 1 gene, who debuts with an ovarian cancer, after the study of a neoplastic adenopathy of neck, biopsied in the context of a cutaneous paraneoplastic syndrome.