Preliminary MRI Study of Extracellular Volume Fraction for Identification of Lymphovascular Space Invasion of Cervical Cancer

Predicting the status of lymphovascular space invasion using quantitative parameters from synthetic MRI in cervical squamous cell carcinoma without lymphatic metastasis

Purpose

To investigate the value of quantitative longitudinal relaxation time (T1), transverse relaxation time (T2), and proton density (PD) maps derived from synthetic magnetic resonance imaging (MRI) for evaluating the status of lymphovascular space invasion (LVSI) in cervical squamous cell carcinoma (CSCC) without lymph node metastasis (LNM).

Material and methods

Patients with suspected cervical cancer who visited our hospital from May 2020 to March 2023 were collected. All patients underwent preoperative MRI, including routine sequences and synthetic MRI. Patients with pathologically confirmed CSCC without lymphatic metastasis were included in this study. The subjects were divided into negative- and positive-LVSI groups based on the status of LVSI. Quantitative parameters of T1, T2, and PD values derived from synthetic MRI were compared between the two groups using independent samples t-test. Receiver operating characteristic curves were used to determine the diagnostic efficacy of the parameters.

Results

59 patients were enrolled in this study and were classified as positive (n = 32) and negative LVSI groups (n = 27). T1 and T2 values showed significant differences in differentiating negative-LVSI from positive-LVSI CSCC (1307.39 ± 122.02 vs. 1193.03 ± 107.86, P<0.0001; 88.42 ± 7.24 vs. 80.99 ± 5.50, P<0.0001, respectively). The area under the curve (AUC) for T1, T2 values and a combination of T1 and T2 values were 0.756, 0.799, 0.834 respectively, and there is no statistically significant difference in the diagnostic efficacy between individual and combined diagnosis of each parameter.

Conclusions

Quantitative parameters derived from synthetic MRI can be used to evaluate the LVSI status in patients with CSCC without LNM.

T1 mapping as a quantitative imaging biomarker for diagnosing cervical cancer: a comparison with diffusion kurtosis imaging

BACKGROUND

T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. This study was conducted to explore the ability of T1 mapping in distinguishing cervical cancer type, grade, and stage and compare the diagnostic performance of T1 mapping with diffusion kurtosis imaging (DKI).

METHODS

One hundred fifty-seven patients with pathologically confirmed cervical cancer were enrolled in this prospectively study. T1 mapping and DKI were performed. The native T1, difference between native and postcontrast T1 (T1diff), mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were calculated. Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAC), low- and high-grade carcinomas, and early- and advanced-stage groups were compared using area under the receiver operating characteristic (AUROC) curves.

RESULTS

The native T1 and MK were higher, and the MD and ADC were lower for CSCC than for CAC (all p < 0.05). Compared with low-grade CSCC, high-grade CSCC had decreased T1diff, MD, ADC, and increased MK (p < 0.05). Compared with low-grade CAC, high-grade CAC had decreased T1diff and increased MK (p < 0.05). Native T1 was significantly higher in the advanced-stage group than in the early-stage group (p < 0.05). The AUROC curves of native T1, MK, ADC and MD were 0,772, 0.731, 0.715, and 0.627, respectively, for distinguishing CSCC from CAC. The AUROC values were 0.762 between high- and low-grade CSCC and 0.835 between high- and low-grade CAC, with T1diff and MK showing the best discriminative values, respectively. For distinguishing between advanced-stage and early-stage cervical cancer, only the AUROC of native T1 was statistically significant (AUROC = 0.651, p = 0.002).

CONCLUSIONS

Compared with DKI-derived parameters, native T1 exhibits better efficacy for identifying cervical cancer subtype and stage, and T1diff exhibits comparable discriminative value for cervical cancer grade.

A Multicenter Study on Preoperative Assessment of Lymphovascular Space Invasion in Early-Stage Cervical Cancer Based on Multimodal MR Radiomics

BACKGROUND

As lymphovascular space invasion (LVSI) was closely related to lymph node metastasis and prognosis, the preoperative assessment of LVSI in early-stage cervical cancer is crucial for patients.

PURPOSE

To develop and validate nomogram based on multimodal MR radiomics to assess LVSI status in cervical cancer patients.

STUDY TYPE

Retrospective.

POPULATION

The study included 168 cervical cancer patients, of whom 129 cases (age 51.36 ± 9.99 years) from institution 1 were included as the training cohort and 39 cases (age 52.59 ± 10.23 years) from institution 2 were included as the external test cohort.

FIELD STRENGTH/SEQUENCE

There were 1.5 T and 3.0 T MRI scans (T1-weighted imaging [T1WI], fat-saturated T2-weighted imaging [FS-T2WI], and contrast-enhanced [CE]).

ASSESSMENT

Six machine learning models were built and selected to construct the radiomics signature. The nomogram model was constructed by combining the radiomics signature with the clinical signature, which was then validated for discrimination, calibration, and clinical usefulness.

STATISTICAL TESTS

The clinical characteristics were compared using t-tests, Mann-Whitney U tests, or chi-square tests. The Spearman and LASSO methods were used to select radiomics features. The receiver operating characteristic (ROC) analysis was performed, and the area under the curve (AUC), accuracy, sensitivity, and specificity were calculated.

RESULTS

The logistic regression (LR) model performed best in each sequence. The AUC of CE-T1-T2WI-combined was the highest in the LR model, with an AUC of 0.775 (95% CI: 0.570-0.979) in external test cohort. The nomogram showed high predictive performance in the training (AUC: 0.883 [95% CI: 0.823-0.943]) and test cohort (AUC: 0.830 [95% CI: 0.657-1.000]) for predicting LVSI. Decision curve analysis demonstrated that the nomogram was clinically useful.

DATA CONCLUSION

Our findings suggest that the proposed nomogram model based on multimodal MRI of CE T1WI-T2WI-combined could be used to assess LVSI status in early cervical cancer.

EVIDENCE LEVEL

4.

TECHNICAL EFFICACY

Stage 2.

The use of quantitative T1-mapping to identify cells and collagen fibers in rectal cancer

Aim

This study aimed to explore the value of T1 mapping in assessing the grade and stage of rectal adenocarcinoma and its correlation with tumor tissue composition.

Methods

Informed consent was obtained from all rectal cancer patients after approval by the institutional review board. Twenty-four patients (14 women and 10 men; mean age, 64.46 years; range, 35 - 82 years) were enrolled in this prospective study. MRI examinations were performed using 3.0T MR scanner before surgery. HE, immunohistochemical, and masson trichrome-staining was performed on the surgically resected tumors to assess the degree of differentiation, stage, and invasion. Two radiologists independently analyzed native T1 and postcontrast T1 for each lesion, and calculated the extracellular volume (ECV) was calculated from T1 values. Intraclass correlation coefficient (ICC) and Bland-Altman plots were applied to analyze the interobserver agreement of native T1 values and postcontrast T1 values. Student's t-test and one-way analysis of variance (ANOVA) were used to test the differences between T1 mapping parameters and differentiation types, T and N stages, and venous and neural invasion. Pearson correlation coefficients were used to analyze the correlation of T1 mapping extraction parameters with caudal type homeobox 2 (CDX-2), Ki-67 index, and collagen expression.

Results

Both the native and postcontrast T1 values had an excellent interobserver agreement (ICC 0.945 and 0.942, respectively). Postcontrast T1 values indicated significant differences in venous invasion (t=2.497, p=0.021) and neural invasion (t=2.254, p=0.034). Pearson's correlation analysis showed a significant positive correlation between native T1 values and Ki-67 (r=-0.407, p=0.049). There was a significant positive correlation between ECV and collagen expression (r=0.811, p=.000) and a significant negative correlation between ECV and CDX-2 (r=-0.465, p=0.022) and Ki-67 (r=-0.549, p=0.005).

Conclusion

Postcontrast T1 value can be used to assess venous and neural invasion in rectal cancer. ECV measurements based on T1 mapping can be used to identify cells and collagen fibers in rectal cancer.

The Utility of Contrast-Enhanced Magnetic Resonance Imaging in Uterine Cervical Cancer: A Systematic Review

Correct staging of cervical cancer is essential to establish the best therapeutic procedure and prognosis for the patient. MRI is the best imaging modality for local staging and follow-up. According to the latest ESUR guidelines, T2WI and DWI-MR sequences are fundamental in these settings, and CE-MRI remains optional. This systematic review, according to the PRISMA 2020 checklist, aims to give an overview of the literature regarding the use of contrast in MRI in cervical cancer and provide more specific indications of when it may be helpful. Systematic searches on PubMed and Web Of Science (WOS) were performed, and 97 papers were included; 1 paper was added considering the references of included articles. From our literature review, it emerged that many papers about the use of contrast in cervical cancer are dated, especially about staging and detection of tumor recurrence. We did not find strong evidence suggesting that CE-MRI is helpful in any clinical setting for cervical cancer staging and detection of tumor recurrence. There is growing evidence that perfusion parameters and perfusion-derived radiomics models might have a role as prognostic and predictive biomarkers, but the lack of standardization and validation limits their use in a research setting.

T1 mapping and extracellular volume fraction measurement to evaluate the poor-prognosis factors in patients with cervical squamous cell carcinoma

PURPOSE

To evaluate the clinical feasibility of T₁ mapping and extracellular volume fraction (ECV) measurement in assessing prognostic factors in patients with cervical squamous cell carcinoma (CSCC).

MATERIALS AND METHODS

A total of 117 CSCC patients and 59 healthy volunteers underwent T₁ mapping and diffusion-weighted imaging (DWI) on a 3 T system. Native T₁ , contrast-enhanced T₁ , ECV, and apparent diffusion coefficient (ADC) were calculated and compared based on surgico-pathologically verified deep stromal infiltration, parametrial invasion (PMI), lymphovascular space invasion (LVSI), lymph node metastasis, stage, histologic grade, and the Ki-67 labeling index (LI).

RESULTS

Native T₁ , contrast-enhanced T₁ , ECV, and ADC values were significantly different between CSCC and the normal cervix (all p < 0.05). No significant differences were observed in any parameters of CSCC when the tumors were grouped by stromal infiltration or lymph node status, respectively (all p > 0.05). In subgroups of the tumor stage and PMI, native T₁ was significantly higher for advanced-stage (p = 0.032) and PMI-positive CSCC (p = 0.001). In subgroups of the grade and Ki-67 LI, contrast-enhanced T₁ was significantly higher for high-grade (p = 0.012) and Ki-67 LI ≥ 50% tumors (p = 0.027). ECV was significantly higher in LVSI-positive CSCC than in LVSI-negative CSCC (p < 0.001). ADC values showed a significant difference for the grade (p < 0.001) but none for the other subgroups.

CONCLUSION

Both T₁ mapping and DWI could stratify the CSCC histologic grade. In addition, T₁ mapping and ECV measurement might provide more quantitative metrics for noninvasively predicting poor prognostic factors and aiding in preoperative risk assessment in CSCC patients.