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Background and Purpose: Radiomics offers little explainability. This study aims to develop a radiomics model (Rad-Score) using diffusion-weighted imaging (DWI) to predict high-risk patients for nodal metastasis or recurrence in endometrial cancer (EC) and corroborate with choline metabolism., Materials and Methods: From August 2015 to July 2018, 356 EC patients were enrolled. Rad-Score was developed using LASSO regression in a training cohort (n = 287) and validated in an independent test cohort (n = 69). MR spectroscopy (MRS) was also used in 230 patients. Nuclear MRS measured choline metabolites in 70 tissue samples. The performance was compared against European Society for Medical Oncology (ESMO) risk groups. A P < .05 denoted statistical significance., Results: Rad-Score achieved 71.1% accuracy in the training and 71.0% in the testing cohorts. Incorporating clinical parameters of age, tumor type, size, and grade, Rad-Signature reached accuracies of 73.2% in training and 75.4% in testing cohorts, closely matching the performance to the post-operatively based ESMO's 70.7% and 78.3%. Rad-Score was significantly associated with increased total choline levels on MRS (P = .034) and tissue levels (P = .019)., Conclusions: Development of a preoperative radiomics risk score, comparable to ESMO clinical standard and associated with altered choline metabolism, shows translational relevance for radiomics in high-risk EC patients., Trial Registration: This study was registered in ClinicalTrials.gov on 2015-08-01 with Identifier NCT02528864., (© 2024. The Author(s).) more...

Introduction: Endometrial cancer (EC) is one of the most common gynecologic neoplasms in developed countries but lacks screening biomarkers., Objectives: We aim to identify and validate metabolomic biomarkers in cervicovaginal fluid (CVF) for detecting EC through nuclear magnetic resonance (NMR) spectroscopy., Methods: We screened 100 women with suspicion of EC and benign gynecological conditions, and randomized them into the training and independent testing datasets using a 5:1 study design. CVF samples were analyzed using a 600-MHz NMR spectrometer equipped with a cryoprobe. Four machine learning algorithms-support vector machine (SVM), partial least squares discriminant analysis (PLS-DA), random forest (RF), and logistic regression (LR), were applied to develop the model for identifying metabolomic biomarkers in cervicovaginal fluid for EC detection., Results: A total of 54 women were eligible for the final analysis, with 21 EC and 33 non-EC. From 29 identified metabolites in cervicovaginal fluid samples, the top-ranking metabolites chosen through SVM, RF and PLS-DA which existed in independent metabolic pathways, i.e. phosphocholine, malate, and asparagine, were selected to build the prediction model. The SVM, PLS-DA, RF, and LR methods all yielded area under the curve values between 0.88 and 0.92 in the training dataset. In the testing dataset, the SVM and RF methods yielded the highest accuracy of 0.78 and the specificity of 0.75 and 0.80, respectively., Conclusion: Phosphocholine, asparagine, and malate from cervicovaginal fluid, which were identified and independently validated through models built using machine learning algorithms, are promising metabolomic biomarkers for the detection of EC using NMR spectroscopy. more...

Background: Endometrial stromal sarcoma (ESS) is a rare uterine malignancy that features different prognoses for its high- and low-grade subtypes. We investigated the diagnostic accuracy of magnetic resonance (MR) imaging in diagnosing and differentiating between high- and low-grade ESS., Methods: We retrospectively reviewed the preoperative pelvic MR images of consecutive patients who received histologically confirmed diagnoses of high-grade ESS (n = 11) and low-grade ESS (n = 9) and T2-hyperintense leiomyoma (n = 16). Two radiologists independently evaluated imaging features in T1-, T2-, and diffusion-weighted and contrast-enhanced MR images. Statistical analysis included Mann-Whitney tests and Fisher's exact test, with sensitivity, specificity and diagnostic accuracy of imaging features., Results: High-grade ESS was associated with significantly more extensive necrosis and hemorrhage and distinct feather-like enhancement compared with low-grade ESS (P < .05 for all). The feather-like enhancement pattern yielded a diagnostic accuracy of 95%, sensitivity of 91%, and specificity of 100% in differentiating high-grade from low-grade ESS. This imaging characteristic was significantly superior to the necrosis (80%, P = .033) or hemorrhage (75%, P = .007). Both high- and low-grade ESS demonstrated T2 hypointense bands, marginal nodules, intratumoral nodules, and worm-like intra-myometrial nodules, and their tumor apparent diffusion coefficient (ADC) values were significantly lower than those of T2-hyperintense leiomyomas (P < .001)., Conclusions: Diffusion-weighted MR imaging is useful in diagnosing ESS against T2-hyperintense leiomyomas, and contrast enhancement aids in further differentiating between high- and low-grade ESS. more...

Background: A triage test to assist clinical decision-making on choosing primary chemoradiation for cervical carcinomas or primary surgery for endometrial carcinomas is important., Purpose or Hypothesis: To develop and validate a multiparametric prediction model based on MR imaging and spectroscopy in distinguishing adenocarcinomas of uterine cervical or endometrial origin., Study Type: Prospective diagnostic accuracy study., Population: Eighty-seven women: 25 cervical and 62 endometrial adenocarcinomas divided into training (n = 43; cervical/endometrial adenocarcinomas = 11/32) and validation (n = 44; 14/30) datasets., Field Strength/sequence: The 3T diffusion-weighted (DW) MR imaging and MR spectroscopy., Assessment: Morphology, volumetric DW MR imaging and spectroscopy (MDS) scoring system with total points 0-5, based on presence of the following MR features assessed independently by two radiologists: (a) epicenter at the cervix, (b) rim enhancement, (c) disrupted cervical stromal integrity, (d) mean volumetric apparent diffusion coefficient values (ADCmean) higher than 0.98 × 10-3 mm 2 /s, (e) fatty acyl δ 1.3 ppm more than 161.92 mM. Histopathology as gold standard., Statistical Tests: Logistic regression and receiver operator characteristic (ROC) curves analysis., Results: For both the training and validation datasets, the MDS score achieved an accuracy of 93.0% and 84.1%, significantly higher than that of morphology (88.4% and 79.5%), ADC value (74.4% and 68.2%), and spectroscopy (81.4% and 68.2%; P < 0.05 for all). The performances of the scoring were superior to the morphology in the training dataset (areas under the receiver operating characteristics curve [AUC] = 0.95 vs. 0.89; P = 0.046), but not in the validation dataset (AUC = 0.90 vs. 0.85; P = 0.289)., Data Conclusion: MDS score has potentials to improve distinguishing adenocarcinomas of cervical or endometrial origin, and warrants large-scale studies for further validation., Level of Evidence: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1654-1666., (© 2017 International Society for Magnetic Resonance in Medicine.) more...

Objectives: To compare the diagnostic accuracy of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging for detecting cervical stromal invasion in endometrial cancer., Methods: Eighty-three consecutive women with endometrial cancer underwent preoperative evaluation in a 3-T unit, including T2-weighted, DW (b = 0 and 1000 s/mm 2 ), and DCE MR imaging. Two radiologists independently assessed presence of cervical stromal invasion, with histopathological reference as gold standard., Results: For assessing cervical stromal invasion, the diagnostic accuracy, sensitivity, and specificity, respectively for Reader 1/Reader 2, were as follows: DW MR imaging- 95.2 %/91.6 %, 91.7 %/100 %, and 95.8 %/90.1 %; DCE MR imaging- 91.6 %/88 %, 58.3 %/50 %, and 97.2 %/94.4 %. The diagnostic performance of DW MR imaging (Reader 1: areas under the receiver operating characteristic curve (AUC) = 0.98; Reader 2: AUC = 0.97) was significantly higher than that of DCE MR imaging (p = 0.009 for Reader 2) or T2-weighted MR imaging (Reader 1: p = 0.006; Reader 2: p = 0.013). Patients with cervical stromal invasion showed a significantly greater canal width (p < 0.0001) and myometrial invasion extent (p = 0.006)., Conclusions: DW MR imaging has superior diagnostic performance compared with DCE MR imaging in the detection of cervical stromal invasion., Key Points: • DWI demonstrates a higher accuracy than DCE in detecting cervical stromal invasion. • Tumour ADC values are similar between patients without or with cervical invasion. • Canal widening causes false-negativity on DCE and T2W but not on DWI. more...