Exploring the Correlation Between MRI Image Characteristics and Diagnosis, Pathology and Prognosis in Patients With Prostate Lesions

Globally, prostate cancer is the second most common malignant tumor and the fifth leading cause of cancer-related death in men. In China, there will be more than 125,000 new cases of prostate cancer in 2022, ranking sixth in the incidence of male cancers, causing about 56,000 deaths, ranking tenth among male malignancies. The gold standard for the diagnosis of prostate cancer is prostate biopsy. In the past, whether to initiate a biopsy procedure depended on the screening results of abnormal prostate cancer, namely, elevated serum PSA levels (\>4.0 ng/mL) and abnormal digital rectal examination (DRE), but the low accuracy led to a large number of negative biopsy results, overdiagnosis and overtreatment of indolent tumors, causing many patients to undergo unnecessary biopsies, resulting in a large social burden. Magnetic resonance imaging (MRI) has been widely used in clinical practice due to its advantages of high soft tissue resolution, multi-plane, multi-sequence, multi-parameter imaging and no ionizing radiation. Studies have shown that multiparametric MRI (mpMRI), including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast enhancement (DCE), can help select patients for initial biopsy and improve the detection rate of biopsy. MRI plays a vital role in the clinical diagnosis and treatment of prostate lesions. However, prostate MRI examinations often show "same disease, different images" and "different diseases, same images". Benign prostate lesions can simulate the characteristics of malignant lesions to interfere with the image and the judgment of clinicians, resulting in misdiagnosis and mistreatment. For example, inflammation in the peripheral zone of the prostate, like tumors, appears as low signal on T2WI, and hyperplastic nodules in the transition zone may also appear as restricted diffusion on DWI like tumors. Therefore, the complementary addition of different parameter sequences and the comprehensive judgment of qualitative and quantitative characteristics are very important for accurate diagnosis. With the development of magnetic resonance technology, new imaging sequences continue to emerge, which can not only show the anatomical decomposition of the prostate more clearly, but also reflect the characteristics of the lesions from the pathological and physiological perspectives such as function, metabolism, and blood perfusion, and can better characterize prostate lesions. The purpose of this study is to study the routine and functional MR imaging data of patients with prostate lesions in our institution, use pathology as the gold standard, and use image processing software to conduct qualitative and quantitative analysis of body composition, imaging characteristics, peritumoral tissue characteristics, and lymph node characteristics, so as to achieve benign and malignant differentiation, pathological feature prediction, and prognosis evaluation, in order to better perform accurate diagnosis, clinical decision-making, and prognosis evaluation in patients with prostate lesions.

Globally, prostate cancer is the second most common malignant tumor and the fifth leading cause of cancer-related death in men. In China, there will be more than 125,000 new cases of prostate cancer in 2022, ranking sixth among male cancers and causing about 56,000 deaths, ranking tenth among male malignancies. Currently recognized risk factors for prostate cancer include increasing age, race (black), genetic factors, insulin-like growth factor (IGF), and family history of malignant tumors. The gold standard for the diagnosis of prostate cancer is prostate biopsy. In the past, whether to initiate a biopsy procedure depended on the screening results of abnormal prostate cancer, namely, elevated serum PSA levels (\>4.0 ng/mL) and abnormal digital rectal examination (DRE). However, the low accuracy led to a large number of negative biopsy results, overdiagnosis and overtreatment of indolent tumors, causing many patients to undergo unnecessary biopsies, resulting in a large social burden. Magnetic resonance imaging (MRI) has been widely used in clinical practice due to its advantages of high soft tissue resolution, multi-plane, multi-sequence, multi-parameter imaging, and no ionizing radiation. Studies have shown that multiparametric MRI (mpMRI), including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast enhancement (DCE), can help select patients for initial biopsy and improve the detection rate of biopsy . The National Comprehensive Cancer Network (NCCN), the American Urological Association (AUA), the European Association of Urology (EAU), and the Chinese Prostate Cancer Diagnosis and Treatment Guidelines all recommend that mpMRI be considered for men with biopsy indications (such as elevated PSA) to reduce the number of men undergoing biopsy and improve the detection rate of clinically significant prostate cancer. In addition to guiding prostate puncture biopsy strategies, the clinical application of mpMRI in prostate cancer also includes the following aspects. First, mpMRI can be combined with transrectal ultrasound (TRUS) (MR-TRUS fusion) for targeted prostate cancer puncture, thereby improving the detection rate of high-grade lesions. Secondly, mpMRI plays a role in the initial staging of intermediate-risk and high-risk patients by detecting extracapsular extension of the prostate, seminal vesicle infiltration, and lymph node involvement. In addition, mpMRI plays an important role in active surveillance of prostate cancer, post-treatment evaluation, and detection of local recurrence after radical prostatectomy. It can be seen that MRI plays a vital role in the clinical diagnosis and treatment of prostate lesions. However, prostate MRI examinations often show "same disease, different images" and "different diseases, same images". Benign prostate lesions can simulate the characteristics of malignant lesions to interfere with the judgment of images and clinicians, thereby causing misdiagnosis and mistreatment. For example, inflammation in the peripheral zone of the prostate, like a tumor, appears as a low signal on T2WI, while hyperplastic nodules in the transition zone may also appear as diffusion restricted on DWI, like a tumor. Therefore, the complementary addition of different parameter sequences and the comprehensive judgment of qualitative and quantitative characteristics are very important for accurate diagnosis. With the development of magnetic resonance imaging technology, new imaging sequences continue to emerge, which can not only show the anatomical decomposition of the prostate more clearly, but also reflect the characteristics of the lesions from the perspectives of function, metabolism, blood perfusion and other pathological and physiological aspects, and can better characterize prostate lesions. For example, time-dependent DWI (td-DWI), as an advanced DWI technology, can not only qualitatively describe the diffusion state of water molecules in tissues through complex pulse sequence design and scientific mathematical modeling calculations, but also provide quantitative information such as cell diameter, intracellular volume fraction and cell density, thereby non-invasively reflecting the microstructural changes of tissues. In addition, the chemical exchange saturation transfer (CEST) sequence saturates the hydrogen protons (hydroxyl (-OH), amide (-NH) and amine (-NH2) groups) in specific metabolites in the body by applying frequency-selective saturation pulses, and uses the chemical exchange phenomenon between saturated hydrogen protons and free water to achieve non-invasive reflection of metabolic information in the human body, which has great application potential. These functional MRI imaging sequences can provide rich information and are still in the clinical trial stage. Once they are proven to be valuable for the detection of prostate cancer, they are expected to improve the current shortcomings of mpMRI in the clinical evaluation of prostate cancer. This is a prospective study. By studying the routine and functional MR imaging data of patients with prostate lesions in this institution, taking pathology as the gold standard, and using image processing software to conduct qualitative and quantitative analysis of body composition, imaging characteristics, tumor surrounding tissue characteristics and lymph node characteristics, the aim is to achieve benign and malignant differentiation, pathological feature prediction, and prognosis evaluation, in order to better perform accurate diagnosis, clinical decision-making and prognosis evaluation of patients with prostate lesions. The total sample size is expected to be 500 cases. The main research steps are: 1. Collection of imaging data: patients with the above criteria are included, and informed consent is signed after communication with them. Recommend the attending physician to prescribe an MR examination, sort out the patient's imaging data information after the examination, and record the image ID, examination item type and other information 2. Image data processing: Through the PACS system, use the image workstation to copy the DICOM format image data, use the image processing software to perform qualitative and quantitative analysis, and record the relevant parameter values 3. Clinical data collection: query the included patient list through the Radiology Information System (RIS) of the Radiology Department of Tongji Hospital, collect clinical data, postoperative pathology and imaging examination item types, including age, height, weight, blood pressure, past medical history, etc., laboratory examination data including blood routine, blood biochemistry, PSA, etc., pathological data including Gleason score, TNM stage, immunohistochemical characteristics, etc., treatment conditions including surgery, radiotherapy, chemotherapy and other information, track follow-up cases, and achieve prognosis evaluation 4. Classify factors such as pathological typing, pathological grading, immunohistochemical characteristics, and clinical prognosis through laboratory examination data and pathological data, aiming to find the correlation between imaging characteristics and the above clinical related characteristics, so as to achieve image prediction of pathology, clinical prognosis and other information, and thus better make clinical decision choices. The data mainly include the data obtained from the processing and analysis of imaging data, pathological immunohistochemistry, and laboratory test results. After the data are sorted out, SPSS, R language and Python are used for data processing and analysis.