A Predictor of Tumor Recurrence in Patients With Endometrial Carcinoma After Complete Resection of the Tumor: The Role of Pretreatment Apparent Diffusion Coefficient

Apparent Diffusion Coefficient on Diffusion-Weighted Magnetic Resonance Imaging to Predict the Prognosis of Patients with Endometrial Cancer: A Meta-Analysis

Apparent diffusion coefficient (ADC) derived from diffusion-weighted magnetic resonance imaging (DWI) may help diagnose endometrial cancer (EC). However, the association between ADC and the recurrence and survival of EC remains unknown. We performed a systematic review and meta-analysis to investigate whether pretreatment ADC on DWI could predict the prognosis of women with EC. PubMed, Embase, and Cochrane's Library were searched for relevant cohort studies comparing the clinical outcomes between women with EC having low versus high ADC on pretreatment DWI. Two authors independently conducted data collection, literature searching, and statistical analysis. Using a heterogeneity-incorporating random-effects model, we analyzed the results. In the meta-analysis, 1358 women with EC were included from eight cohort studies and followed for a median duration of 40 months. Pooled results showed that a low pretreatment ADC on DWI was associated with poor disease-free survival (DFS, hazard ratio [HR]: 3.29, 95% CI: 2.04 to 5.31, p < 0.001; I2 = 41%). Subgroup analysis according to study design, tumor stage, MRI Tesla strength, ADC cutoff, follow-up duration, and study quality score showed consistent results (p for subgroup analysis all > 0.05). The predictive value of low ADC for poor DFS in women with EC decreased in multivariate studies compared to univariate studies (HR: 2.59 versus 32.57, p = 0.002). Further studies showed that a low ADC was also associated with poor overall survival (HR: 3.36, 95% CI: 1.33 to 8.50, p = 0.01, I2 = 0). In conclusion, a low ADC on pretreatment DWI examination may predict disease recurrence and survival in women with EC.

Endometrial cancer risk stratification using MRI radiomics: corroborating with choline metabolism

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.

Clinical Utility of Diffusion-Weighted Imaging in Gynecological Imaging: Revisited

ABSTRACT

Diffusion-weighted imaging (DWI) is an increasingly valuable sequence in daily clinical practice, providing both functional and morphological information. The use of DWI can help quantify diffusion using the apparent diffusion coefficient, which reflects the physiological features of the tissue and tumor microcirculation. This knowledge is crucial for understanding and interpreting gynecological imaging. This article reviews the clinical utility of DWI for gynecological imaging, highlighting its ability to aid in the detection of endometrial and cervical cancers, as well as tumor extension and metastasis. In addition, DWI can easily detect the solid components of ovarian cancer (including dissemination), assist in the diagnosis of adnexal torsion, and potentially show bone marrow status. Apparent diffusion coefficient measurement is useful for differentiating between endometrial lesions, uterine leiomyomas, and sarcomas, and may provide important information for predicting the prognosis of gynecological cancers.

Volumetric apparent diffusion coefficient (ADC) histogram metrics as imaging biomarkers for pretreatment predicting response to fertility-sparing treatment in patients with endometrial cancer

OBJECTIVES

To investigate the feasibility of volumetric apparent diffusion coefficient (ADC) histogram analysis for prediction of fertility-sparing treatment (FST) response in patients with endometrial cancer (EC).

METHODS

Pretreatment data of 54 EC patients with FST were retrospectively analyzed. Treatment response at each follow-up was pathologically evaluated. The associations of ADC histogram metrics (volume, minADC, maxADC, meanADC; 10th, 25th, 50th, 75th and 90th ADC percentiles; skewness; kurtosis) and baseline clinical characteristics with complete response (CR) at the second and third follow-ups, two-consecutive CR, and recurrence at the final follow-up were evaluated by uni- and multivariable logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was used for diagnostic performance evaluation.

RESULTS

Compared with non-CR patients, CR patients had significantly higher minADC and 10th and 25th ADC percentiles at the second follow-up (P = 0.008, 0.039, and 0.034, respectively) and higher minADC, older age, lower HE4 level, and higher overweight rate at the third follow-up (P = 0.001, 0.040, 0.021, and 0.004, respectively). Patients with two-consecutive CR had a significantly higher minADC than those without (P = 0.018). There was no association between ADC metrics or clinical characteristics and recurrence (all P > 0.05). MinADC yielded the largest AUC in predicting CR (0.688 and 0.735 at the second and third follow-up, respectively) and the presence of two-consecutive CR (0.753). When combined with patient age and HE4 level, the prediction of CR could be further improved at the third follow-up, with an AUC of 0.786.

CONCLUSION

Pretreatment minADC could be a potential imaging biomarker for predicting FST response. Clinical characteristics may have incremental value to minADC in predicting CR.

The prominent value of apparent diffusion coefficient in assessing high-risk factors and prognosis for patients with endometrial carcinoma before treatment

BACKGROUND

To date, there are no consensus methods to evaluate the high-risk factors and prognosis for managing the personalized treatment schedule of patients with endometrial carcinoma (EC) before treatment. Apparent diffusion coefficient (ADC) is regarded as a kind of technique to assess heterogeneity of malignant tumor.

PURPOSE

To explore the role of ADC value in assessing the high-risk factors and prognosis of EC.

MATERIAL AND METHODS

A retrospective analysis was made on 185 patients with EC who underwent 1.5-T magnetic resonance imaging (MRI). Mean ADC (mADC), minimum ADC (minADC), and maximum ADC (maxADC) were measured and compared in different groups.

RESULTS

Among the 185 patients with EC, the mADC and maxADC values in those with high-risk factors (type 2, deep myometrial invasion, and lymph node metastasis) were significantly lower than in those without. According to receiver operating characteristic (ROC) curve analysis, the areas under the curve (AUC) were significant for mADC, minADC, and maxADC predicting high-risk factors. Furthermore, the AUCs were significant for mADC and maxADC predicting lymph node metastasis but were not significant for minADC. Patients with lower mADC were associated with worse overall survival and disease-free survival; the opposite was true for patients with higher mADC.

CONCLUSION

Our study showed that ADC values could be applied to assess the high-risk factors of EC before treatment and might significantly relate to the prognosis of EC. It might contribute to managing initial individualized treatment schedule and improve outcome in patients with EC.

Endometrial Cancer, the Current International Federation of Gynecology and Obstetrics Staging System, and the Role of Imaging

Imaging plays a crucial role in the diagnosis, staging, and follow-up of endometrial cancer. Endometrial cancer is staged surgically using the International Federation of Gynecology and Obstetrics (FIGO) staging system. Preoperative imaging can complement surgical staging but is not yet considered a required component in the current FIGO staging system. Preoperative imaging can help identify some tumor characteristics and tumor spread, both locally and distally. More accurate assessment of endometrial cancers optimizes management and treatment plan, including degree of surgical intervention. In this article, we review the epidemiology, FIGO staging system, and the importance of imaging in the staging of endometrial cancer.

Apparent diffusion coefficients for predicting primary cholesteatoma risk of recurrence after surgical clearance

PURPOSE

Beside the well-known accuracy of non-EPI DWI techniques and relative ADC maps in detecting cholesteatomatous tissue, ADC can also represent a useful tool for stratifying cholesteatoma risk of recurrence. Aim of this study is to test the role of ADC in determining risk of recurrence for primary middle ear cholesteatoma, proposing stratification based on pre-operative mean (mADC) and normalized (nADC) ADC values.

METHODS

In this prospective study, 60 patients with primary unilateral middle ear cholesteatoma underwent a three-years-long follow-up to assess the presence of recurrent disease after macroscopically complete excisional surgery. Baseline MRI examination mADC and nADC values in the group with early evidence of recurrent cholesteatoma were compared to the group with no evidence of recurrence by using T statistics.

RESULTS

ADC values on pre-operative MRI examination were lower in cholesteatomas with early evidence of recurrence, and statistical significance was slightly higher for nADC compared to mADC measurements. We also determined a cut-off between the two groups, proposing stratification in high-risk of recurrence cholesteatomas (mADC≤ 1000 or nADC< 1.3) and low-risk cholesteatomas (mADC>1000 or nADC≥1.3).

CONCLUSIONS

ADC values resulted discriminating in identifying cholesteatomas with higher risk of early recurrence, both for mean and normalized ADC, with optimized tissue characterization and outcome prediction.

Endometrial Carcinoma: Texture Analysis of Apparent Diffusion Coefficient Maps and Its Correlation with Histopathologic Findings and Prognosis

PURPOSE

To determine the feasibility of texture analysis (TA) of apparent diffusion coefficient (ADC) maps for predicting histologic grade (HG) and recurrence-free survival (RFS) in patients with endometrial carcinoma (EMC).

MATERIALS AND METHODS

One hundred twenty-one patients with EMC were examined by using a 1.5-T MRI system and diffusion-weighted imaging (DWI) with b values of 0 and 1000 sec/mm². Software with volumes of interest on ADC maps was used to extract 45 texture features including higher-order texture features. Receiver operating characteristic analysis was performed to compare the diagnostic performance of the random forest (RF) model and ADC values for HG and recurrence.

RESULTS

Area under the curve (AUC) for predicting high-grade EMCs was significantly larger for RF model than for ADC values (0.967 vs 0.898; P = .0336). AUC for predicting recurrence was larger for the RF model than for ADC values (0.890 vs 0.875; P = .7248), although the difference was not significant. Mean RFS was significantly shorter for high-grade EMCs than for low-grade EMCs (P = .0002; hazard ratio, 4.9) and for ADC values less than or equal to 0.802 × 10^-3 mm²/sec than for ADC values greater than 0.802 × 10^-3 mm²/sec (P < .0001; hazard ratio, 32.9). RF model showed that the mean RFS was significantly shorter for the presence of recurrence than for its absence (P < .0001; hazard ratio, 94.7).

CONCLUSION

TA of ADC maps had significantly higher diagnostic performance than did ADC values for predicting HG and was a more useful indicator than HG and ADC values for predicting RFS in patients with EMC.Keywords: Comparative Studies, Genital/Reproductive, MR-Diffusion Weighted Imaging, MR-Imaging, Neoplasms-Primary, Pathology, Pelvis, Tissue Characterization, Uterus© RSNA, 2019.

Utility of the relative apparent diffusion coefficient for preoperative assessment of low risk endometrial carcinoma

OBJECTIVES

Lymphadenectomy is not recommended for low risk stage I endometrial carcinoma (EC) patients. This study was to investigate the predictive value of apparent diffusion coefficient (ADC) values in predicting patients with low risk EC, and to identify an optimum ADC measurement for preoperative assessment.

MATERIALS AND METHODS

Eighty-one patients with stage I EC who underwent diffusion-weighted imaging (DWI) at 1.5T were included and divided into low group and intermediate-high risk group based on the ESMO-ESGO-ESTRO classification. Clinical indexes, conventional MRI parameters, minimum ADC values (minADC), mean ADC values (meanADC) and relative ADC values (rADC) were compared between those two groups. rADC was calculated using the equation ADC (cancer)/ADC (reference) with the obturator internus muscle as reference. The optimal ADC measurement and cut-off ADC value for low risk EC were calculated using the receiver operating characteristic (ROC) curve.

RESULTS

The low risk group had significantly higher meanADC, minADC, and rADC values than did the intermediate-high risk group (1.095 vs. 0.902 × 10^-3 mm²/s, 0.755 vs. 0.657 × 10^-3 mm²/s, 0.754 vs. 0.603, respectively). In assessments of low risk EC patients, the area under the curve (AUC) values for meanADC, minADC, and rADC were 0.840 (95%CI, 0.749,0.931), 0.681 (95% CI: 0.561,0.800), and 0.876(95% CI: 0.798,0.954), respectively. The optimal cut-off rADC value for prediction was 0.669, the maximum Youden index, sensitivity, specificity, and accuracy values were 0.683, 81.8%, 86.5%, and 84.0%, respectively.

CONCLUSIONS

rADC is superior to minADC and meanADC for predicting patients with low risk EC, and could potentially aid to the surgical management of these patients in avoiding unnecessary lymphadenectomy.