Inclusion of CA-125 Does Not Improve Mathematical Models Developed to Distinguish Between Benign and Malignant Adnexal Tumors

2007 ◽  
Vol 25 (27) ◽  
pp. 4194-4200 ◽  
Author(s):  
Dirk Timmerman ◽  
Ben Van Calster ◽  
Davor Jurkovic ◽  
Lil Valentin ◽  
Antonia C. Testa ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Malignant Tumors ◽  
Color Doppler ◽  
Characteristic Curve ◽  
Premenopausal Women ◽  
Color Doppler Imaging ◽  
Doppler Imaging ◽  
Ca 125 ◽  
Benign Tumors ◽  
Adnexal Masses

Purpose To test the value of serum CA-125 measurements alone or as part of a multimodal strategy to distinguish between malignant and benign ovarian tumors before surgery based on a large prospective multicenter study (International Ovarian Tumor Analysis). Patients and Methods Patients with at least one persistent ovarian mass preoperatively underwent transvaginal ultrasonography using gray scale imaging to assess tumor morphology and color Doppler imaging to obtain indices of blood flow. Results Data from 809 patients recruited from nine centers were included in the analysis; 567 patients (70%) had benign tumors and 242 (30%) had malignant tumors—of these 152 were primary invasive (62.8%), 52 were borderline malignant (21.5%), and 38 were metastatic (15.7%). A logistic regression model including CA-125 (M2) resulted in an area under the receiver operating characteristic curve (AUC) of 0.934 and did not outperform a published (M1) without serum CA-125 information (AUC, 0.936). Specifically designed new models including CA-125 for premenopausal women (M3) and for postmenopausal women (M4) did not perform significantly better than the model without CA-125 (M1; AUC, 0.891 v AUC, 0.911 and AUC, 0.975 v AUC, 0.949, respectively). In postmenopausal patients, serum CA-125 alone (AUC, 0.920) and the risk of malignancy index (AUC, 0.924) performed very well. Results were very similar when the models were prospectively tested on a group of 345 new patients with adnexal masses of whom 126 had malignant tumors (37%). Conclusion Adding information on CA-125 to clinical information and ultrasound information does not improve discrimination of mathematical models between benign and malignant adnexal masses.

Mathematical Models to Discriminate Between Benign and Malignant Adnexal Masses: Potential Diagnostic Improvement Using Ovarian HistoScanning

2011 ◽  
Vol 21 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Evelien Vaes ◽  
Ranjit Manchanda ◽  
Rina Nir ◽  
Dror Nir ◽  
Harry Bleiberg ◽  
...  
Keyword(s):  
Mathematical Models ◽  
New Technology ◽  
Characteristic Curve ◽  
Model Performance ◽  
Diagnostic Value ◽  
Ca 125 ◽  
Transvaginal Sonography ◽  
Future Research ◽  
Initial Report ◽  
Adnexal Masses

Purpose:Accurate preoperative clinical assessment of adnexal masses can optimize outcomes by ensuring appropriate and timely surgery. This article addresses whether a new technology, ovarian HistoScanning, has an additional diagnostic value in mathematical models developed for the differential diagnosis of adnexal masses.Patients and Methods:Transvaginal sonography-based morphological variables were obtained through blinded analysis of archived images in 199 women enrolled in a prospective study to assess the performance of ovarian HistoScanning. Logistic regression (LR) and neural network (NN) models including these variables and clinical and patient data along with the HistoScanning score (HSS) (range, 0-125; based on mathematical algorithms) were developed in a learning set (60% patients). The remaining 40% patients (evaluation set) were used to assess model performance.Results:Of all morphological and clinical variables tested, serum CA-125, presence of a solid component, and HSS were most significant and used to develop the LR model. The NN model included all variables. The novel variable, HSS, offered significant improvement in the LR and NN models' performance. The LR and NN models in an independent evaluation set were found to have area under the receiver operating characteristic curve = 0.97 (95% confidence interval [CI], 94-99) and 0.93 (95% CI, 88-98), sensitivities = 83% (95% CI, 71%-91%) and 80% (95% CI, 67%-89%), and specificities = 98% (95% CI, 89%-99%) and 86% (95% CI, 72%-95%), respectively. In addition, these models showed an improved performance when compared with 3 other existing models (allP< 0.05).Conclusions:This initial report shows a clear benefit of including ovarian HistoScanning into mathematical models used for discriminating benign from malignant ovarian masses. These models may be specifically helpful to the less experienced examiner. Future research should assess performance of these models in prospective clinical trials in different populations.

scholarly journals Which Parameters could be Useful for Predicting Malignancy in Solid Adnexal Masses?

2009 ◽  
Vol 3 (1) ◽  
pp. 1-5
Author(s):  
Juan Luis Alcázar ◽  
Pedro Royo ◽  
Laura Pineda
Keyword(s):  
Blood Flow ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Malignant Tumors ◽  
Univariate Analysis ◽  
Menopausal Status ◽  
Ca 125 ◽  
Benign Tumors ◽  
Adnexal Masses

Abstract To determine which clinical, biochemical and other sonographic parameters could be useful to predict malignancy in sonographically solid adnexal masses. Methods Clinical (age, menopausal status, complaints and physical examination), biochemical (serum CA-125 levels) and other sonographic features (tumor volume, ascites, bilaterality, blood flow location and velocimetric pattern) from 163 women diagnosed as having a solid adnexal mass on B-mode gray-scale ultrasound were reviewed for this retrospective study. All patients had undergone surgery and mass removal. Definitive histologic diagnosis was available in all cases. All parameters were compared to final histological diagnosis (benign or malignant) in univariate statistical analysis. Then a stepwise forward logistic regression analysis was performed to identify those features that independently predict malignancy. Results A total of 173 masses were analyzed. Patients mean age was 52.4 years (range: 15 to 84 years) 117 masses were malignant and 56 were benign. After univariate analysis all parameters showed statistical differences between benign and malignant tumors. After logistic regression analysis only central blood flow (odd ratio: 64.2, 95% CI: 17.07 to 242.03) and presence of ascites (odd ratio: 32.77, 95% CI: 5.38 to 199.72) were identified as independent predictors of malignancy. The presence of one of these two features correlated to malignancy in 98.6% of cases. The absence of both was found in 82.1% of benign tumors. Conclusions The presence or absence of ascites or central blood flow may be helpful for discriminating benign from malignant solid adnexal masses.

Preoperative Evaluation of the ADNEX Model for the Prediction of the Ovarian Cancer Risk of Adnexal Masses at Siriraj Hospital

2021 ◽  
pp. 1-7
Author(s):  
Vitcha Poonyakanok ◽  
Prasong Tanmahasamut ◽  
Atthapon Jaishuen ◽  
Thanyarat Wongwananuruk ◽  
Chutimon Asumpinwong ◽  
...  
Keyword(s):  
Malignant Tumors ◽  
Characteristic Curve ◽  
Preoperative Evaluation ◽  
Survival Rates ◽  
Benign Tumors ◽  
Diagnostic Study ◽  
Ovarian Cancer Risk ◽  
Cutoff Value ◽  
Adnexal Masses ◽  
Siriraj Hospital

Introduction: Distinguishing benign adnexal masses from malignant tumors plays an important role in preoperative planning and improving patients’ survival rates. The International Ovarian Tumor Analysis (IOTA) group developed a model termed the Assessment of Different NEoplasias in the adneXa (ADNEX). Objective: Our objective was to evaluate the performance of the ADNEX model in distinguishing between benign and malignant tumors at a cutoff value of 10%. Methods: This was a prospective diagnostic study. 357 patients with an adnexal mass who were scheduled for surgery at Siriraj Hospital were included from May 1, 2018, to May 30, 2019. All patients were undergoing ultrasonography, and serum CA125 was measured. Data were calculated by the ADNEX model via an IOTA ADNEX calculator. Results: Of the 357 patients, 296 had benign tumors and 61 had malignant tumors. The area under the receiver operating characteristic curve for using the ADNEX model was 0.975 (95% confidence interval, 0.953–0.988). At a 10% cutoff, the sensitivity was 98.4% and specificity was 87.2%. The best cutoff value was at 16.6% in our population. Conclusions: The performance of the ADNEX model in differentiating benign and malignant tumors was excellent.

scholarly journals Multiple hepatic hemangiomas in a Nigerian man

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Abiodun Christopher Jemilohun ◽  
Taofeek Abiodun Ajadi ◽  
Modupeola Maria Bello
Keyword(s):  
Incidental Finding ◽  
Color Doppler ◽  
Color Doppler Imaging ◽  
Doppler Imaging ◽  
Medical Attention ◽  
Benign Tumors ◽  
Hepatic Hemangioma ◽  
Diagnostic Dilemma ◽  
Abdominal Ultrasonography ◽  
Hepatic Hemangiomas

Hepatic hemangiomas are benign tumors of the liver which are often found incidentally. We present a 34-years-old man with a two-month history of upper abdominal pain and incidental finding of multiple hepatic masses. The patient sought medical attention at several healthcare facilities where he posed a diagnostic dilemma before he was referred to us. Computed tomographic scan revealed four hypodense hepatic nodules of varying sizes. The nodules demonstrated peripheral enhancement with progressive centripetal filling till they were totally filled during the delayed phase. Abdominal ultrasonography confirmed the four hepatic lesions. The largest lesion was in the left lobe measuring 73×72 mm while the smallest was in the right lobe (24×20 mm). All the masses demonstrated increased vascularity on color Doppler imaging. The paucity of reported cases of hepatic hemangioma in Nigeria, the multiplicity of the tumor and the giant size of one of them make this case remarkable and reportable.

scholarly journals Multiparametric ultrasound in the diagnosis of ovarian focal lesions

2021 ◽  
pp. 29-35
Author(s):  
A. V. Pomortsev ◽  
M. I. Ambros ◽  
J. Yu. Dyachenko ◽  
M. A. Matosyan ◽  
M. A. Khuako
Keyword(s):  
Malignant Tumors ◽  
Color Doppler ◽  
Resistance Index ◽  
Reproductive Age ◽  
Doppler Imaging ◽  
Benign Tumors ◽  
Focal Lesion ◽  
Histological Structure ◽  
Focal Lesions ◽  
Diagnostic Significance

Objective Development of an ultrasound diagnostic matrix for predicting the severity of proliferative changes in the ovarian focal lesion.Material and Methods The research was conducted on the basis of the Clinical Oncology Center, Regional Clinical Hospital no. 2. Echography (B-mode), color Doppler mapping, energy Doppler mapping (pulsation index, resistance index) on GE Voluson E8 and Aloka SSD 3500 devices were used as research methods. Retrospectively, 81 patients of reproductive age from 18 to 45 years were examined. Depending on the histological structure of ovarian lesion, the results of surgical treatment, dynamic observation and the outcome of the disease, were divided into 4 clinical groups: I (n = 12; 14,8%) – controls with no changes in the structure of the ovaries; II (n = 20; 24,7%) – patients with retention ovarian lesions; III (n = 20; 24,7%) – with benign tumors; IV (n = 29; 35,8%) – with malignant tumors.Results A large number of diagnostic parameters does not always allow to formulate an instrumental diagnosis correctly because they have different diagnostic significance. That is why we made an attempt to create a diagnostic matrix. For each of the 18 parameters, three answers were offered. When analyzing the results of the study, there was an increase in the number of pathological parameters from II to IV clinical groups. Thus, in group III, the combination of 2 pathological signs was found in 65% of cases, and 3 signs – in 25% of the examined women. In group IV, the combination of 2 signs was determined in 82% of the subjects, and 3 signs in 65%.Conclusion Thus, we found out that in-depth ultrasound examination (color Doppler imaging, pulsed Doppler) allowed to identify the severity of the proliferative changes and to give the prognosis of the disease.

scholarly journals Diagnosis of portal vein thrombosis: value of color Doppler imaging.

1991 ◽  
Vol 157 (2) ◽  
pp. 293-296 ◽  
Author(s):  
F N Tessler ◽  
B J Gehring ◽  
A S Gomes ◽  
R R Perrella ◽  
N Ragavendra ◽  
...  
Keyword(s):  
Portal Vein ◽  
Portal Vein Thrombosis ◽  
Color Doppler ◽  
Color Doppler Imaging ◽  
Doppler Imaging ◽  
Vein Thrombosis
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