A prospective comparison of the diagnostic accuracies of ultrasound and magnetic resonance imaging in preoperative staging of endometrial cancer

Wong, Michael L.; Amin, T.; Thanatsis, Nikolaos; Naftalin, J.

doi:10.3802/jgo.2022.33.e22

Cited by 12 publications

(21 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Magnetic resonance imaging (MRI) has been extensively applied in endometrial cancer staging [ 2 , 3 , 4 , 5 ] and is usually the imaging modality of choice for assessment of deep myometrial invasion (DMI) [ 6 , 7 , 8 , 9 ]. Studies have shown that using MRI alone, endometrial cancer DMI prediction [ 10 ] accuracies were estimated to be 74% [ 11 ], 76% [ 12 ], and 89% [ 13 ]. However, these accuracies are subjective as it is dependent on the radiologist’s ability to detect subtle imaging textures on MR images.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Deep Myometrial Infiltration, Clinical Risk Category, Histological Type, and Lymphovascular Space Invasion in Women with Endometrial Cancer Based on Clinical and T2-Weighted MRI Radiomic Features

Dessi

Marcus

et al. 2023

Cancers

View full text Add to dashboard Cite

Purpose: To predict deep myometrial infiltration (DMI), clinical risk category, histological type, and lymphovascular space invasion (LVSI) in women with endometrial cancer using machine learning classification methods based on clinical and image signatures from T2-weighted MR images. Methods: A training dataset containing 413 patients and an independent testing dataset consisting of 82 cases were employed in this retrospective study. Manual segmentation of the whole tumor volume on sagittal T2-weighted MRI was performed. Clinical and radiomic features were extracted to predict: (i) DMI of endometrial cancer patients, (ii) endometrial cancer clinical high-risk level, (iii) histological subtype of tumor, and (iv) presence of LVSI. A classification model with different automatically selected hyperparameter values was created. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, F1 score, average recall, and average precision were calculated to evaluate different models. Results: Based on the independent external testing dataset, the AUCs for DMI, high-risk endometrial cancer, endometrial histological type, and LVSI classification were 0.79, 0.82, 0.91, and 0.85, respectively. The corresponding 95% confidence intervals (CI) of the AUCs were [0.69, 0.89], [0.75, 0.91], [0.83, 0.97], and [0.77, 0.93], respectively. Conclusion: It is possible to classify endometrial cancer DMI, risk, histology type, and LVSI using different machine learning methods.

show abstract

Section: Introductionmentioning

confidence: 99%

Prediction of Deep Myometrial Infiltration, Clinical Risk Category, Histological Type, and Lymphovascular Space Invasion in Women with Endometrial Cancer Based on Clinical and T2-Weighted MRI Radiomic Features

Dessi

Marcus

et al. 2023

Cancers

View full text Add to dashboard Cite

show abstract

“…Information regarding flow and timing domain was only available in two articles. 18,21 The study design was clearly defined as prospective in all the studies. Two papers were considered as high risk for patient selection because of patients unsatisfactory evaluated in the TVS exam were excluded.…”

Section: Resultsmentioning

confidence: 99%

“…Two papers were considered as high risk for patient selection because of patients unsatisfactory evaluated in the TVS exam were excluded. 18,21 Three studies 18,19,21 adequately described the method of index text (concerning TVS) as well as its implementation and interpretation. One was considered as high risk since TVS examiners had no previous experience in preoperative assessment of myometrial infiltration in endometrial cancer, even though they received a theoretical-practical training.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Transvaginal ultrasound versus magnetic resonance imaging for preoperative assessment of myometrial infiltration in patients with low‐grade endometrioid endometrial cancer: A systematic review and head‐to‐head meta‐analysis

Tameish

Flórez

Vidal

et al. 2023

J of Clinical Ultrasound

View full text Add to dashboard Cite

PurposeWe aimed to compare the diagnostic performance of magnetic resonance imaging (MRI) and transvaginal ultrasound (TVS) for detecting myometrial invasion (MI) in patients with low‐grade endometrioid endometrial carcinoma.MethodsA comprehensive search of MEDLINE (Pubmed), Web of Science, Embase and Scopus (from January 1990 to December 2022) was performed for articles comparing TVS and MRI in the evaluation of myometrial infiltration in low‐grade (grade 1 or 2) endometrioid endometrial carcinoma in the same group of patients. We used QUADAS‐2 tool for assessing the risk of bias of studies.ResultsWe found 104 citations in our extensive research. Four articles were ultimately included in the meta‐analysis, after excluding 100 reports. All articles were considered low risk of bias in most of the domains assessed in QUADAS‐2. We observed that pooled sensitivity and specificity for detecting deep MI were 65% (95% confidence interval [CI] = 54%–75%) and 85% (95% CI = 79%–89%) for MRI, and 71% (95% CI = 63%–78%) and 76% (95% CI = 67%–83%) for TVS, respectively. No statistical differences were found between both imaging techniques (p > 0.05). We observed low heterogeneity for sensitivity and high for specificity regarding TVS; and moderate for both sensitivity and specificity in case of MRI.ConclusionsThe diagnostic performance of TVS and MRI for the evaluation of deep MI in women with low‐grade endometrioid endometrial cancer is similar. However, further research is needed as the number of studies is scanty.

show abstract

“…From a diagnostic perspective, several non-invasive tools have been considered for endometrial cancer screening, including the qualitative assessment of the endometrium through a transvaginal ultrasound; measurement of bloodbased serum markers, such as cancer antigen 125 (CA125); and Pap smear (7)(8)(9). However, to date, the diagnosis of endometrial carcinoma or its precursors relies on the pathologic evaluation of the endometrium based on diagnostic curettage.…”

Section: Introductionmentioning

confidence: 99%

Feasibility and clinical applicability of genomic profiling based on cervical smear samples in patients with endometrial cancer

Kim

Lee

et al. 2022

Front. Oncol.

View full text Add to dashboard Cite

PurposeCervical smear samples are easily obtainable and may effectively reflect the tumor microenvironment in gynecological cancers. Therefore, we investigated the feasibility of genomic profiling based on tumor DNA analysis from cervical smear samples from endometrial cancer patients.Materials and methodsPreoperative cervical smear samples were obtained via vaginal sampling in 50 patients, including 39 with endometrial cancer and 11 with benign uterine disease. Matched blood samples were obtained simultaneously. Genomic DNA (gDNA) from cervical smear and/or cell-free DNA from whole blood were extracted and sequenced using the Pan100 panel covering 100 endometrial cancer-related genes.ResultsCervical swab-based gDNA analysis detected cancer with 67% sensitivity and 100% specificity, showing a superior performance compared to that of the matched blood or Pap smear tests. Cervical swab-based gDNA effectively identified patients with loss of MSH2 or MSH6 and aberrant p53 expression based on immunohistochemistry. Genomic landscape analysis of cervical swab-based gDNA identified PTEN, PIK3CA, TP53, and ARID1A as the most frequently altered genes. Furthermore, 26 endometrial cancer patients could be classified according to the Proactive Molecular Risk Classifier for Endometrial Cancer.ConclusionCervical swab-based gDNA test showed an improved detection potential and allowed the classification of patients, which has both predictive and prognostic implications.

show abstract

A prospective comparison of the diagnostic accuracies of ultrasound and magnetic resonance imaging in preoperative staging of endometrial cancer

Cited by 12 publications

References 38 publications

Prediction of Deep Myometrial Infiltration, Clinical Risk Category, Histological Type, and Lymphovascular Space Invasion in Women with Endometrial Cancer Based on Clinical and T2-Weighted MRI Radiomic Features

Prediction of Deep Myometrial Infiltration, Clinical Risk Category, Histological Type, and Lymphovascular Space Invasion in Women with Endometrial Cancer Based on Clinical and T2-Weighted MRI Radiomic Features

Transvaginal ultrasound versus magnetic resonance imaging for preoperative assessment of myometrial infiltration in patients with low‐grade endometrioid endometrial cancer: A systematic review and head‐to‐head meta‐analysis

Feasibility and clinical applicability of genomic profiling based on cervical smear samples in patients with endometrial cancer

Contact Info

Product

Resources

About