MRI-based radiomics features for the non-invasive prediction of FIGO stage in cervical carcinoma: A multi-center study.

PURPOSE: To develop and validate a model based on MRI radiomics modals for predicting surgical high FIGO(IB3 and ≥ IIA2) and low FIGO(IB1, IB2, and IIA1) stages in patients with cervical carcinoma (CC) . METHODS: A total of 296 early-stage patients with CC (preoperative FIGO stages IB-IIA) confirmed by surgery and pathology were included in this retrospective study from two institutions For each patient,we extracted radiomics features from spectral attenuated inversion-recovery T2-weighted (SPAIR-T2W) and contrast-enhanced T1-weighted (CE-T1W) images.Manual segmentation was performed using the 3D Slicer software, while radiomics features were extracted, screened using the R software. A 2-stage feature extraction strategy involving univariate analysis and the Least Absolute Shrinkage Selection Operator technique was performed. A support vector machine-based model was eventually constructed. Predictive accuracy of the training and validation datasets was assessed in terms of area under the ROC curve (AUC). RESULTS: A total of 1130 features were extracted from SPAIR-T2WI and CET1WI images respectively, in which 8 and 7 features significantly were associated with FIGO staging. AUCs of the SPAIR-T2W and CE-T1W models were were 0.803 and 0.790, respectively, in the internal validation group. In the external validation group, the AUCs were 0.767 and 0.749, respectively, which increased to 0.771 in the combined model. CONCLUSION: Our study demonstrated the feasibility of radiomics features from SPAIR-T2W and CE-T1W images for the prediction of surgical FIGO stage in CC. Our proposed model thereby carries the potential as a non-invasive tool for the staging and treatment planning of this disease. ADVANCES IN KNOWLEDGE: A radiomics model provide a non-invasive and objective method for the detection of FIGO staging in patients with cervical cancer before surgery, thus providing a reference for the selection of treatment options for patients.

MRI-based radiomics analysis to evaluate the clinicopathological characteristics of cervical carcinoma: a multicenter study.

BACKGROUND: Preoperative prediction of clinical pathological indicators of cervical cancer (CC) is of great significance to the formulation of personalized treatment plans for CC. PURPOSE: To investigate magnetic resonance imaging (MRI) radiomics analysis for the evaluation of pathological types, tumor grade, FIGO stage, and lymph node metastasis (LNM) of CC. MATERIAL AND METHODS: A total of 235 patients with CC from three institutes were enrolled in the study. All patients underwent T2/SPAIR and contrast-enhanced T1-weighted (CE-T1WI) imaging scans before radical hysterectomy by pelvic lymph node dissection surgery. Radiomics features extracted from T2/SPAIR and CE-T1WI imaging were selected by the least absolute shrinkage and selection operator (LASSO) methods for further radiomics signature calculation. These radiomic features were used to construct regression and decision tree models to evaluate the performance of radiomic features in distinguishing clinicopathological indicators. RESULTS: The area under the curve (AUC) of T2/SPAIR and CE-T1WI imaging were 0.777 and 0.750, respectively, for differentiating between adenocarcinoma and squamous cell carcinoma. From the two sequences, the AUC of the verification group that distinguished low FIGO stage from high FIGO stage was 0.716 and 0.676, respectively. The AUC for moderately well and poorly differentiated tumors were 0.729 on T2/SPAIR and 0.749 on CE-T1WI imaging. The AUC of the verification groups for LNM was 0.730 and 0.618 on T2/SPAIR and CE-T1WI imaging, respectively. CONCLUSION: MRI radiomics features can be used as a non-invasive method to evaluate the clinicopathological indexes of CC and provide an important auxiliary examination method for patients to determine individualized treatment plans before operation.

Diffusion tensor imaging in the cervical spinal cord.

There are discrepancy between MR findings and clinical presentations. The compressed cervical cord in patients of the spondylotic myelopathy may be normal on conventional MRI when it is at the earlier stage or even if patients had severe symptoms. Therefore, it is necessary to take a developed MR technique--diffusion tensor imaging (DTI)--to detect the intramedullary lesions. Prospective MR and DTI were performed in 53 patients with cervical compressive myelopathy and twenty healthy volunteers. DTI was performed along six non-collinear directions with single-shot spin echo echo-planar imaging (EPI) sequence. Intramedullary apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured in four segments (C2/3, C3/4, C4/5, C5/6) for volunteers, in lesions (or the compressed cord) and normal cord for patients. DTI original images were processed to produce color DTI maps. In the volunteers' group, cervical cord exhibited blue on the color DTI map. FA values between four segments had a significant difference (P < 0.01), with the highest FA value (0.85 ± 0.03) at C2/3 level. However, ADC value between them had no significant difference (P > 0.05). For patients, only 24 cases showed hyperintense on T2-weighted image, while 39 cases shown patchy green signal on color DTI maps. ADC and FA values between lesions or the compressed cord and normal spinal cord of patients had a significant difference (both P < 0.01). FA value at C2/3 cord is the highest of other segments and it gradually decreases towards the caudal direction. Using single-shot spin echo EPI sequence and six non-collinear diffusion directions with b value of 400 s mm(-2), DTI can clearly show the intramedullary microstructure and more lesions than conventional MRI.