The patients with locally advanced rectal cancer diagnosed in Peking University Third Hospital and undergoing neoadjuvant chemoradiotherapy were collected. The basic information of patients (including age, sex, BMI, TNM stage of rectal cancer (T2, T3 stage)) was collected. The blood routine was collected before radiotherapy, 1 week, 2 weeks and 90 days after radiotherapy. MRI including T1WI, DWI sequence and IDEAL-IQ sequence before radiotherapy, 1-2 weeks after radiotherapy and 90 days after radiotherapy were performed, and the corresponding parameters were obtained. The white blood cell values and quantitative parameters of magnetic resonance (including T1WI, DWI signal intensity (b = 1000) and proton density fat fraction (PDFF) of sacrilium and proximal femur were collected. Patients were divided into acute myelosuppression group and non-acute myelosuppression group according to blood routine results 14 days after radiotherapy, and chronic myelosuppression group and non-chronic myelosuppression group according to blood routine results 90 days after radiotherapy. The magnetic resonance parameters difference between 1-2 weeks after radiotherapy and before radiotherapy, and the magnetic resonance parameters difference between 90 days after radiotherapy and before radiotherapy were calculated. By comparing the differences of clinical risk factors and quantitative parameters of MRI between the two groups, the meaningful variables were screened out, and the risk identification model of acute and chronic myelosuppression was established.
Rectal cancer patients who received neoadjuvant chemoradiotherapy in Peking University Third Hospital in 2021 are divided into acute myelosuppression group, chronic myelosuppression group and normal group. The differences of magnetic resonance parameters between the groups were compared. The risk identification model of acute and chronic myelosuppression after neoadjuvant chemoradiotherapy was established by clinical risk factors and quantitative parameters of magnetic resonance imaging, and the prediction efficiency of the model was evaluated.