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Utility of Clinical Parameters and Multiparametric MRI as Predictive Factors for Differentiating Uterine Sarcoma From Atypical Leiomyoma

Posted Jul 31, 2018 Updated Apr 10, 2023
By Qiu Bi MD , Zhibo Xiao PhD , Fajin Lv PhD , Yao Liu MD , Chunxia Zou MD , Yiqing Shen MD
13 min read

Objectives

The objective of this study was to find clinical parameters and qualitative and quantitative magnetic resonance imaging (MRI) features for differentiating uterine sarcoma from atypical leiomyoma (ALM) preoperatively and to calculate predictive values for uterine sarcoma.

Materials and Methods

Data from 60 patients with uterine sarcoma and 88 patients with ALM confirmed by surgery and pathology were collected. Clinical parameters, qualitative MRI features, diffusion-weighted imaging with apparent diffusion coefficient values, and quantitative parameters of dynamic contrast-enhanced MRI of these two tumor types were compared. Predictive values for uterine sarcoma were calculated using multivariable logistic regression.

Results

Patient clinical manifestations, tumor locations, margins, T2-weighted imaging signals, mean apparent diffusion coefficient values, minimum apparent diffusion coefficient values, and time-signal intensity curves of solid tumor components were obvious significant parameters for distinguishing between uterine sarcoma and ALM (all P < .001). Abnormal vaginal bleeding, tumors located mainly in the uterine cavity, ill-defined tumor margins, and mean apparent diffusion coefficient values of <1.272 × 10 −3 mm 2 /s were significant preoperative predictors of uterine sarcoma. When the overall scores of these four predictors were greater than or equal to 7 points, the sensitivity, the specificity, the accuracy, and the positive and negative predictive values were 88.9%, 99.9%, 95.7%, 97.0%, and 95.1%, respectively.

Conclusions

The use of clinical parameters and multiparametric MRI as predictive factors was beneficial for diagnosing uterine sarcoma preoperatively. These findings could be helpful for guiding treatment decisions.

Introduction

Uterine sarcoma is a rare tumor characterized by high malignancy and very poor prognosis . The most common entities are leiomyosarcoma (LMS), endometrial stromal sarcoma (ESS), and carcinosarcoma . However, according to the Federation of Gynecology and Obstetrics (FIGO) staging system revised in 2009, carcinosarcoma is regarded as a subset of endometrial carcinoma because of the similarity in biological behavior . The standard surgical excision of uterine sarcoma consists of hysterectomy and bilateral salpingo-oophorectomy . Uterine leiomyoma (LM) is the most common benign smooth muscle tumor of the uterus and can be treated with nonsurgical options, such as drugs , high-intensity focused ultrasound , and artery embolization . Uterine sarcoma is often misdiagnosed as LM because of their similar clinical presentations ; thus, it is very important to distinguish them to avoid delaying hysterectomy in women with presumed symptomatic fibroids who, in fact, have a uterine sarcoma.

Previous studies have reported that uterine sarcoma differed from benign uterine tumors in patient age, serum lactate dehydrogenase (LDH) levels, and endometrial cytology findings , whereas there are many overlaps between uterine sarcoma and LM in age and LDH levels, and endometrial cytology is negative when the tumor is located in the myometrium only. Therefore, it is difficult to differentiate uterine sarcoma from LM by relying only on clinical parameters. Imaging examinations are necessary to identify them precisely.

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Materials and Methods

Study Subjects

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Clinical Parameters

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MRI Protocol

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Table 1

Details of Imaging Protocols for All Magnetic Resonance Imaging Sequences

Parameters T2WI T1WI DWI Contrast-enhanced T1WI Axial Sagittal Axial Axial Axial Sagittal TR (ms) 4400 3040 175 4375 4 3.9 TE (ms) 106.6 107.5 1.8 65.6 1.9 1.8 FOV (cm) 28 × 22.4 28 × 22.4 40 × 28 36 × 27 40 × 32 35 × 28 Matrix 288 × 224 320 × 224 320 × 224 128 × 128 320 × 224 288 × 224 Slice thickness (mm) 5 6 5 5 4 4 Slice gap (mm) 1.5 1 1 1.5 0 0 NEX 1 1 1 5 0.72 0.71

DWI, diffusion-weighted imaging; FOV, field of view; NEX, number of excitation; TE, echo time; TR, repetition time; T1WI, T1-weighted imaging; T2WI, T2-weighted imaging.

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MRI Analysis

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Statistical Analyses

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Results

Pathologic Diagnoses

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Figure 1, Diagram of the distribution of pathologic results. ALM, atypical leiomyoma; ESS, endometrial stromal sarcoma; LM, leiomyoma; LMS, leiomyosarcoma; MRI, magnetic resonance imaging.

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Clinical Parameters

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Table 2

Univariate Analysis of Clinical Parameters for the Uterine Sarcoma and Atypical Leiomyoma Groups

Uterine Sarcoma ( n = 60) Atypical Leiomyoma ( n = 88)P Age (y), range 46 ± 12, 20–76 42 ± 9, 21–77 .019 BMI (kg/m 2 ) 20.93 ± 3.84 22.71 ± 2.89 .961 Childbearing history Nulliparity 7 15 .366 Abortion 45 74 .171 Clinical manifestation Abnormal vaginal bleeding 23 4<.001 Menstrual changes \* 19 22 .374 Abdominal pain 9 11 .662 Pelvic mass 5 9 .699 Urinary symptoms 2 3 1.000 Physical examinations 2 39 <.001 CA125 ↑ (>35 U/mL) † 14 14 .128 LDH ↑ (>245 U/L) ‡ 8 4 .020 Serum albumin ↓ (<40 g/L) § 30 31 .064 FIGO stage Stage I 54 — — Stage II 6 — —

BMI, body mass index; CA125, cancer antigen 125; FIGO, Federation of Gynecology and Obstetrics; LDH, lactate dehydrogenase.

Continuous variables were expressed as arithmetic means and standard deviations, and categorical variables were described with frequencies.

P , comparing data between uterine sarcoma and atypical leiomyoma by the Student t test, the Mann-Whitney U test, the Pearson χ 2 test, or the Fisher exact test.

Boldfaced value indicates obvious significant difference parameters in which the frequency of uterine sarcoma was greater than that of atypical leiomyoma with a value of P < .001.

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MRI Parameters

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Table 3

Univariate Analysis of MRI Parameters for the Uterine Sarcoma and Atypical Leiomyoma Groups

Uterine Sarcoma

( n = 36) Atypical Leiomyoma

( n = 79)P Main location Myometrium 8 44 .001 Uterine cavity 17 4<.001 Subserosa 2 23 .004 Cervical canal 3 1 .090 Extrauterine 6 7 .220 Shape Massive 26 51 .418 Round 4 24 .034 Nodular 0 3 .551 Polypoid 3 0 .029 Irregular shape 3 1 .090 Maximum tumor diameters (mm) 67.2 ± 30.3 83.3 ± 49.4 .156 Ill-defined margin on T2WI 29 3<.001 Solid components on T2WI Slight hyperintensity 16 20 .040 Isointensity 0 10 .030 Slight hypointensity 1 31 <.001 Mixed signal 19 18 .001 Mean ADC 1.015 ± 0.192 1.441 ± 0.270<.001 Minimum ADC 0.806 ± 0.167 1.167 ± 0.261<.001 TIC I 10 17 .532 II 7 47 <.001 III 19 15<.001 MCER 2.62 ± 1.61 2.00 ± 0.77 .008 EER 1.65 ± 1.48 0.93 ± 0.99 .005

ADC, apparent diffusion coefficient; EER, early enhancement ratio; MCER, maximum contrast enhancement ratio; T2WI, T2-weighted imaging; TIC, time signal-intensity curves.

Continuous variables were expressed as arithmetic means and standard deviations, and categorical variables were described with frequencies.

P , comparing data between uterine sarcoma and atypical leiomyoma by the Student t test, the Mann-Whitney U test, the Pearson χ 2 test, or the Fisher exact test.

Boldfaced values indicate obvious significant difference parameters in which the frequency of uterine sarcoma was greater than that of atypical leiomyoma with a value of P < .001.

Figure 2, ROC curve of the mean ADC values and the minimum ADC values (a) and of the predictive values (b) . The areas under the curve were 0.930, 0.903, and 0.971, respectively. Additionally, the optimal thresholds for distinguishing between the two groups were 1.272 × 10 −3 mm 2s, 0.951 × 10 −3 mm 2s, and 7 points, respectively. When the overall scores of the four predictors were greater than or equal to 7 points, the sensitivity, the specificity, the accuracy, and the positive and negative predictive values were 88.9%, 99.9%, 95.7%, 97.0%, and 95.1%, respectively. ADC, apparent diffusion coefficient; ROC, receiver operating characteristic.

Figure 3, A 45-year-old woman with leiomyosarcoma whose main clinical complication was menostaxis for 2 months. (a, b) Sagittal and axial T2-weighted imaging revealed a mixed-signal mass, located mainly in the uterine cavity (3 points), with an ill-defined margin (4 points). (c) The solid component of the tumor showed isointensity on axial T1-weighted imaging. (d) On axial contrast-enhanced imaging, the solid parts of the tumor displayed marked enhancement. (e) On axial diffusion-weighted imaging, the lesion appeared to have heterogeneous hyperintensity. (f) The axial apparent diffusion coefficient map revealed that the solid component of leiomyosarcoma showed restricted diffusion, and the mean apparent diffusion coefficient values were 0.658 × 10 −3 mm 2s (5 points). The overall predictive values were 12 points, and the mass was correctly diagnosed as uterine sarcoma. The circle represents the region of interest in the solid component of the tumor.

Figure 4, A 23-year-old woman with endometrial stromal sarcoma whose main clinical complication was abnormal vaginal bleeding for 1 month (3 points). (a, b) Sagittal and axial T2-weighted imaging revealed a mixed-signal mass, located mainly in the uterine cavity (3 points), with an ill-defined margin (4 points). (c) The solid component of the tumor showed isointensity on axial T1-weighted imaging. (d) On axial contrast-enhanced imaging, the solid parts of the tumor displayed similar enhancement as the myometrium. (e) On axial diffusion-weighted imaging, the lesion appeared to have heterogeneous hyperintensity. (f) The axial apparent diffusion coefficient map revealed that the solid component of endometrial stromal sarcoma showed restricted diffusion, and the mean apparent diffusion coefficient values were 1.170 × 10 −3 mm 2s (5 points). The overall predictive values were 15 points, and the mass was correctly diagnosed as uterine sarcoma. The circle represents the region of interest in the solid component of the tumor.

Figure 5, A 32-year-old woman who was confirmed to have leiomyoma with hyaline degeneration and had been hospitalized for leiomyoma found by medical examination. (a, b) Sagittal and axial T2-weighted imaging indicated the lesion was located mainly in the subserosa with a well-defined margin, and the solid parts of the lesion exhibited isointensity. (c) The solid component of the tumor showed isointensity on axial T1-weighted imaging. (d) On axial contrast-enhanced imaging, the solid parts of the tumor displayed marked enhancement. (e) On axial diffusion-weighted imaging, the lesion showed isointensity. (f) The axial apparent diffusion coefficient map revealed the solid component of the leiomyoma showed unrestricted diffusion, and the mean apparent diffusion coefficient values were 1.280 × 10 −3 mm 2s. The overall predictive values were 0 points, and the mass was not diagnosed with uterine sarcoma. The circle represents the region of interest in the solid component of the tumor.

Figure 6, A 44-year-old woman confirmed to have cellular leiomyoma, whose main clinical complication was menostaxis for 17 days. (a, b) Sagittal and axial T2-weighted imaging indicated the lesion was located mainly in the myometrium with a well-defined margin, and the solid parts of the lesion appeared to have slight hyperintensity. (c) The solid component of the tumor showed isointensity on axial T1-weighted imaging. (d) On axial contrast-enhanced imaging, the solid parts of the tumor displayed marked enhancement. (e) On axial diffusion-weighted imaging, the lesion showed hyperintensity. (f) The axial apparent diffusion coefficient map revealed the solid component of leiomyoma showed unrestricted diffusion, and the mean apparent diffusion coefficient values were 1.13 × 10 −3 mm 2s (5 points). The overall predictive values were 5 points, and the mass was not diagnosed with uterine sarcoma. The circle represents the region of interest in the solid component of the tumor.

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Predictors and Predictive Values

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Table 4

Predictive Values of Each Predictive Factor

Odds Ratio_P_ Parameter Estimates Predictive Values (Points) Abnormal vaginal bleeding 13.054 .000 2.569 3 Located in the uterine cavity 26.159 .040 3.264 3 Ill-defined margin on T2WI 81.206 .000 4.397 4 Mean ADC < 1.272 × 10 −3 mm 2 /s 99.371 .001 4.599 5 Type III of the TICs of the lesions 1.149 .888 0.139 —

ADC, apparent diffusion coefficient; T2WI, T2-weighted imaging; TIC, time signal-intensity curves.

P , obtaining predictive factors by multivariable logistic regression analysis with a value of P < .05.

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Discussion

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Academic Radiology, Volume 25, Issue 8
Journals General Radiology
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