Preoperative magnetic resonance imaging criteria for predicting lymph node metastasis in patients with stage IB1-IIA2 cervical cancer

A Hybrid Model-Based Clinicopathological Features and Radiomics Based on Conventional MRI for Predicting Lymph Node Metastasis and DFS in Cervical Cancer

This study aimed to improve the accuracy of the diagnosis of lymph node metastasis (LNM) and prediction of patient prognosis in cervical cancer patients using a hybrid model based on MRI and clinical aspects. We retrospectively analyzed routine MR data from 485 patients with pathologically confirmed cervical cancer from January 2014 to June 2021. The data were divided into a training cohort (N = 261), internal cohort (N = 113), and external validation cohort (n = 111). A total of 2194 features were extracted from each ROI from T2WI and CE-T1WI. The clinical model (M1) was built with clinicopathological features including squamous cell carcinoma antigen, MRI-reported LNM, maximal tumor diameter (MTD). The radiomics model (M2) was built with four radiomics features. The hybrid model (M3) was constructed with squamous cell carcinoma antigen, MRI-reported LNM, MTD which consists of M1 and four radiomics features which consist of M2. GBDT algorithms were used to create the scores of M1 (clinical-score, C-score), M2 (radiomic score, R-score), and M3 (hybrid-score, H-score). M3 showed good performance in the training cohort (AUCs, M3 vs. M1 vs. M2, 0.917 vs. 0.830 vs. 0.788), internal validation cohorts (AUCs, M3 vs. M1 vs. M2, 0.872 vs. 0.750 vs. 0.739), and external validation cohort (AUCs, M3 vs. M1 vs. M2, 0.907 vs. 0.811 vs. 0.785). In addition, higher scores were significantly associated with worse disease-free survival (DFS) in the training cohort and the internal validation cohort (C-score, P = 0.001; R-score, P = 0.002; H-score, P = 0.006). Radiomics models can accurately predict LNM status in patients with cervical cancer. The hybrid model, which incorporates clinical and radiomics features, is a novel way to enhance diagnostic performance and predict the prognosis of cervical cancer.

Endovaginal coil for pelvic high-resolution magnetic resonance imaging of cervical cancer: a preliminary parameter optimization study

Background

The diagnosis of early-stage cervical cancer through conventional magnetic resonance imaging (MRI) remains challenging, highlighting a greater need for pelvic high-resolution MRI (HR MRI). This study used our research team's endovaginal coil imaging to optimize scanning parameters and aimed to achieve HR MRI of the pelvis and determine its clinical value.

Methods

Fifty participants were recruited prospectively for this cross-sectional study conducted at the First Affiliated Hospital of Chongqing Medical University from January 2023 to November 2023. Initially, 10 volunteers requiring pelvic imaging diagnosis underwent pelvic MRI with the endovaginal coil combined with a conventional external array coil to test and optimize the scanning parameters. Subsequently, 40 patients who were highly suspected or diagnosed with cervical cancer were randomly assigned to undergo an initial pelvic scan with an external array coil with subsequent examinations of both the conventional coil and the endovaginal coil. Two experienced radiologists performed quantitative analyses, measuring signals and calculating the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and contrast (C). They also conducted qualitative analyses, evaluating imaging artifacts, anatomical structures, and overall image quality. The paired sample t-test and Wilcoxon rank-sum test were conducted to compare the statistical differences between the two sets of images, while the intraclass correlation coefficient (ICC) and Kappa consistency tests were used to assess the measurement and scoring consistency between the two radiologists.

Results

The optimized endovaginal images had higher mean SNR, CNR, and C values (18.62±7.85, 16.04±7.72, and 0.73±0.11, respectively) compared to the conventional images (6.77±2.36, 4.47±2.05, and 0.47±0.12, respectively). Additionally, the ratings for imaging artifacts, anatomical structures, and overall quality of the endovaginal images were all 4 [interquartile range (IQR) 4, 4]; meanwhile, the conventional images scored lower with ratings of 4 (IQR 3, 4), 3 (IQR 3, 3), and 3 (IQR 3, 3) for SNR, CNR, and C, respectively. All analysis results underwent paired-sample t-tests or Wilcoxon rank-sum tests between the two groups, yielding a P value <0.001. The optimized endovaginal images also showed improved resolution with a reconstructed voxel size of 0.11 mm3, and HR MRI was successfully achieved. The ICC values for the measurements were 0.914, 0.947, and 0.912, respectively, and for the ratings, the measurement was 0.923, indicating excellent consistency between the two physicians (ICC/Kappa value between 0.85 and 1.00).

Conclusions

Endovaginal technology, which provides precise clinical information for the diagnosis of cervical cancer, provides straightforward operation and exceptional imaging quality, making it highly suitable for expanded clinical use.

A nomogram-based optimized Radscore for preoperative prediction of lymph node metastasis in patients with cervical cancer after neoadjuvant chemotherapy

Purpose

To construct a superior single-sequence radiomics signature to assess lymphatic metastasis in patients with cervical cancer after neoadjuvant chemotherapy (NACT).

Methods

The first half of the study was retrospectively conducted in our hospital between October 2012 and December 2021. Based on the history of NACT before surgery, all pathologies were divided into the NACT and surgery groups. The incidence rate of lymphatic metastasis in the two groups was determined based on the results of pathological examination following lymphadenectomy. Patients from the primary and secondary centers who received NACT were enrolled for radiomics analysis in the second half of the study. The patient cohorts from the primary center were randomly divided into training and test cohorts at a ratio of 7:3. All patients underwent magnetic resonance imaging after NACT. Segmentation was performed on T1-weighted imaging (T1WI), T2-weighted imaging, contrast-enhanced T1WI (CET1WI), and diffusion-weighted imaging.

Results

The rate of lymphatic metastasis in the NACT group (33.2%) was significantly lower than that in the surgery group (58.7%, P=0.007). The area under the receiver operating characteristic curve values of Radscore_CET1WI for predicting lymph node metastasis and non-lymphatic metastasis were 0.800 and 0.797 in the training and test cohorts, respectively, exhibiting superior diagnostic performance. After combining the clinical variables, the tumor diameter on magnetic resonance imaging was incorporated into the Rad_clin model constructed using Radscore_CET1WI. The Hosmer-Lemeshow test of the Rad_clin model revealed no significant differences in the goodness of fit in the training (P=0.594) or test cohort (P=0.748).

Conclusions

The Radscore provided by CET1WI may achieve a higher diagnostic performance in predicting lymph node metastasis. Superior performance was observed with the Rad_clin model.

Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis for Assessing Normal-Sized Lymph Node Metastasis in Cervical Cancer: Comparison Between Readout-Segmented and Single-Shot Echo-Planar Diffusion-Weighted Imaging

OBJECTIVE

To compare the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis derived from readout-segmented echo-planar imaging (RS-EPI) and single-shot echo-planar imaging (SS-EPI) diffusion-weighted imaging (DWI) in evaluating normal-sized lymph node metastasis (LNM) in cervical cancer.

METHODS

Seventy-six pathologically confirmed cervical cancer patients (stages IB and IIA) were enrolled, including 61 patients with non-LNM (group A) and 15 patients with normal-sized LNM (group B). The recorded tumor volume on T2-weighted imaging was the reference against which both DWIs were evaluated. Each ADC histogram parameter (including ADCmax, ADC90, ADCmedian, ADCmean, ADC10, ADCmin, ADCskewness, ADCkurtosis, and ADCentropy) was compared between SS-EPI and RS-EPI and between the 2 groups.

RESULTS

There was no significant difference in tumor volume between the 2 DWIs and T2-weighted imaging (both P > 0.05). Higher ADCmax and ADCentropy but lower ADC10, ADCmin and ADCskewness were found in SS-EPI than those in RS-EPI (all P < 0.05). For SS-EPI, lower ADC90 and higher ADCkurtosis were found in group B than those in group A (both P < 0.05). For RS-EPI, lower ADC90 and higher ADCkurtosis and ADCentropy were found in group B than those in group A (all P < 0.05). Readout-segmented echo-planar imaging ADCkurtosis showed the highest area under the curve of 0.792 in the differentiation of the 2 groups (sensitivity, 80%; specificity, 73.77%).

CONCLUSIONS

Compared with SS-EPI, the ADC histogram parameters derived from RS-EPI were more accurate, and ADCkurtosis held great potential in differentiating normal-sized LNM in cervical cancer.

Preoperative magnetic resonance imaging criteria for predicting lymph node metastasis in patients with stage IB1-IIA2 cervical cancer

Objective

This study aimed to identify patients with stage IB1‐IIA2 cervical cancer at low risk for lymph node metastasis (LNM) using preoperative magnetic resonance imaging (MRI) parameters.

Methods

Clinical and MRI data of patients with stage IB1‐IIA2 cervical cancer who underwent radical surgery between 2010 and 2015 were retrospectively reviewed. Clinical stage IB1‐IIA2 cervical cancer was diagnosed according to the 2009 International Federation of Gynecology and Obstetrics staging system. The low‐risk criteria for LNM were identified using logistic regression analysis. The performance of the logistic regression analysis was estimated through receiver operating characteristic curve analysis.

Results

Of 453 patients, 105 (23.2%) exhibited pathological LNM (p‐LNM). The maximal tumor diameter (adjusted odds ratio [aOR], 1.586; 95% confidence interval [CI], 1.312–1.916; p < 0.001) and LNM (aOR, 2.384; 95% CI, 1.418–4.007; p = 0.001) on preoperative MRI (m‐LNM) were identified as independent risk factors for p‐LNM using a multivariate logistic analysis. The p‐LNM rate was 4.0% for low‐risk patients (n = 124) identified using the current criteria (maximal tumor diameter <3.0 cm and no sign of m‐LNM). The 5‐year disease‐free survival rate of low‐risk patients was significantly greater than the rate of patients with a maximal tumor diameter ˃3.0 cm and/or signs of m‐LNM (90.4% vs. 82.1%; p = 0.033).

Conclusions

The low‐risk criteria for p‐LNM were a maximal tumor diameter <3.0 cm and no sign of m‐LNM. Patients with stage IB1‐IIA2 cervical cancer at low risk for m‐LNM could be candidates for radical surgery; hence, they have a lesser need for adjuvant chemoradiotherapy, thus avoiding the severe comorbidities it causes.