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ORIGINAL RESEARCH

Analysis of the Value of Quantitative Features in Multimodal MRI Images to Construct a Radio-Omics Model for Breast Cancer Diagnosis

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Pages 305-318 | Received 08 Feb 2024, Accepted 24 May 2024, Published online: 11 Jun 2024

Figures & data

Figure 1 The selection process of general information.

Figure 1 The selection process of general information.

Figure 2 MRI images of the training and validation group.

Note: (A and B) was the training group, and (C and D) was the validation group.
Figure 2 MRI images of the training and validation group.

Table 1 Analysis of the Proportion of Disease Types (Cases, %)

Table 2 Comparison of General Information ()

Table 3 Comparative Analysis of MRI Examination Results and Pathological Results (Cases, %)

Table 4 Comparison of General Information Between Two Groups ()

Table 5 Radio-Omics Parameters Related to Lesions

Table 6 The Value of a Single MRI in the Diagnosis of Breast Cancer

Figure 3 ROC curve was used to analyze the diagnostic value of radiomics indicators of T1WI, T2WI, DWI, ADC and DCE in breast cancer.

Figure 3 ROC curve was used to analyze the diagnostic value of radiomics indicators of T1WI, T2WI, DWI, ADC and DCE in breast cancer.

Table 7 Value of Combined MRI in Diagnosis of Breast Cancer

Figure 4 ROC curve was used to analyze the value of multimodal MRI in the diagnosis of breast cancer.

Figure 4 ROC curve was used to analyze the value of multimodal MRI in the diagnosis of breast cancer.

Data Sharing Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.