Staging MRI of uterine malignant mixed Müllerian tumors versus endometrial carcinomas with emphasis on dynamic enhancement characteristics.


Journal

Abdominal radiology (New York)
ISSN: 2366-0058
Titre abrégé: Abdom Radiol (NY)
Pays: United States
ID NLM: 101674571

Informations de publication

Date de publication:
04 2020
Historique:
pubmed: 14 6 2019
medline: 11 2 2021
entrez: 14 6 2019
Statut: ppublish

Résumé

To determine whether staging pelvic magnetic resonance imaging (MRI) can distinguish malignant mixed Müllerian tumor (MMMT) from EC. Thirty-seven treatment-naïve patients with histologically proven uterine MMMT and 42 treatment-naïve patients with EC, treated at our institution, were included in our retrospective study. Staging pelvic MRI scans were reviewed for tumor size, prolapse through cervical os, and other features. Time-intensity curves for tumor and surrounding myometrium regions of interest were generated, and positive enhancement integral (PEI), maximum slope of increase (MSI), and signal enhancement ratio (SER) were measured. The Fisher's exact test or Wilcoxon rank-sum test was used to compare characteristics between disease groups. Multivariate and univariate logistic regression models were used to distinguish MMMT from EC. Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate prediction ability. MMMTs were larger than ECs with higher rate of tumor prolapse and more heterogeneous tumor enhancement compared to ECs. During the late phase of contrast enhancement, 100% of ECs, but only 84% of MMMTs, had lower signal intensity than the myometrium. Threshold PEI ratio ≥ 0.67 predict MMMT with 76% sensitivity, 84%, specificity and 0.83 AUC. Threshold SER ≤ 125 predict MMMT with 90% sensitivity, 50% specificity, and 0.72 AUC. MMMTs may show more frequent tumor prolapse, more heterogeneous enhancement, delayed iso- or hyper-enhancement, higher PEI ratios, and lower tumor SERs compared with EC. MRI can be used as a biomarker to distinguish MMMT from EC based on the enhancement pattern.

Identifiants

pubmed: 31190089
doi: 10.1007/s00261-019-02096-y
pii: 10.1007/s00261-019-02096-y
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1141-1154

Auteurs

Alheli Garza (A)

Radiology Associates of North Texas, Dallas, TX, USA.

Sherif B Elsherif (SB)

The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA. sherif.b.elsherif@gmail.com.

Silvana C Faria (SC)

The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA.

Tara Sagebiel (T)

The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA.

Jia Sun (J)

The Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.

Jingfei Ma (J)

The Department of Imaging Physics, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.

Priya R Bhosale (PR)

The Department of Diagnostic Radiology, The University of Texas M. D. Anderson Cancer Center, 1400 Pressler St., Houston, TX, 77030, USA.

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Classifications MeSH