Advancement and Validation of Prostate Diffusion and Spectroscopic MRI

前列腺扩散和能谱 MRI 的进展和验证

• 批准号: 8299893
• 负责人: Stephan E Maier
• 金额: $ 40.87万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2017-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8299893
• 关键词: Address; Aftercare; Agreement; Anatomy; Biopsy; Cancer Patient; Cell membrane; Choline; Citrates; Clinical; Collection; Complement; Core Biopsy; Creatine; Data; Data Set; Detection; Development; Diagnostic; Diffusion; Diffusion Magnetic Resonance Imaging; Diffusion weighted imaging; Disease; Exhibits; Gland; Gleason Grade for Prostate Cancer; Histology; Image; Individual; Lesion; Lipids; Local Therapy; Location; MRI Scans; Magnetic Resonance; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Malignant Neoplasms; Malignant neoplasm of prostate; Maps; Metabolic Marker; Methods; Microscopy; Monitor; Morphologic artifacts; Motion; Nature; Normal tissue morphology; PSA level; Patient Monitoring; Patients; Pelvis; Phase; Physiologic pulse; Play; Predisposition; Procedures; Prostate; Protocols documentation; Radical Prostatectomy; Resolution; Role; Scanning; Services; Shapes; Signal Transduction; Staging; System; Techniques; Testing; Time; Tissues; Transrectal Ultrasound; Tumor Tissue; Validation; Weight; abstracting; base; cancer site; follow-up; image registration; improved; novel; novel strategies; reconstruction; spectroscopic imaging; treatment effect; tumor; tumor growth; water diffusion

Project Summary/Abstract More reliable and accurate diagnostic estimation of tumor locations, volumes, and malignancy grade with MR would provide an invaluable service towards staging prostate cancer, particularly in cases with negative transrectal ultrasound (TRUS) biopsy. MR, due to the non-invasive nature, is a promising method for repeated exams in patients under active surveillance (AS) and for monitoring treatment effects. More detailed localization is also valuable for emerging targeted local therapies. The current collection of MR methods, which includes T2-weighted MRI, dynamic contrast-enhanced (DCE) MRI, diffusion-weighted MRI (DWI) and 3D-MR spectroscopic imaging (MRSI) appears to be very useful for staging of prostate cancer, particularly if used in combination. However, the potentially most sensitive and specific of these methods, namely DWI and MRSI, exhibit several deficiencies, which will be addressed by the technical developments contemplated for this project. Moreover, a novel contrast based on the separation of the fast and slow water diffusion components present in tissues, will be explored for improved detection of prostate cancer. The specific aims are as follows: 1) To advance whole-gland MRSI by reducing scan duration to a clinically acceptable time, while improving spatial resolution and eliminating the problem of lipid contamination of spectra due to truncation artifacts. 2) To advance spatial resolution and geometric fidelity of prostate DWI with reduced field-of-view and segmented multi-shot imaging. 3) To perform MRI scans in prostate cancer patients with standard sequences and new MRSI and diffusion imaging sequences. Moreover, to attain a separation of diffusion components, which have the potential to be more sensitive and specific to tumor growth related tissue aberrations at the cellular level, it is planned to employ biexponential analysis of DWI data collected over a wider range of diffusion encoding strength (b-factor). Quantitative parameter maps will be generated from MRSI, DWI, and DCE MRI data. 4) To obtain MRI-guided biopsy data or whole-gland step section histology during clinically indicated follow-up procedures in order to validate that the improved techniques and the novel contrast permit superior detection of prostate cancer. Pre-procedural parameter maps will be co-registered to the biopsy or histology coordinate system. Gleason scores of individual biopsy cores and tumor outlines on microscopy images will be compared with findings on parameter maps. The utility of each parameter and combined parameters to differentiate tumor from normal tissue will be analyzed statistically.

项目总结/文摘