McCullum Lucas, Mulder Samuel L, West Natalie A, Aghoghovbia Robert, Ali Alaa Mohamed Shawky, Scott Hayden, Salzillo Travis C, Ding Yao, Dresner Alex, Subashi Ergys, Ma Dan, Stafford R Jason, Hwang Ken-Pin, Fuller Clifton D
UTHealth Houston Graduate School of Biomedical Sciences, UT MD Anderson Cancer Center, Houston, USA.
Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
J Appl Clin Med Phys. 2025 Jul;26(7):e70134. doi: 10.1002/acm2.70134. Epub 2025 Jul 11.
SyntheticMR has the capability of generating quantitative relaxometry maps and synthetic contrast-weighted MRI images in rapid acquisition times. Recently, it has gained attention in the diagnostic community, however, no studies have investigated its feasibility on the MR-Simulation or MR-Linac systems, especially as part of the head and neck adaptive radiation oncology workflow.
Demonstrating its feasibility will facilitate rapid quantitative biomarker extraction, which can be leveraged to guide adaptive radiation therapy decision making.
Two phantoms, two healthy volunteers, and one patient were scanned using SyntheticMR on the MR-Simulation and MR-Linac devices with scan times between 4 to 6 min. The correlation between measured and reference quantitative T1, T2, and PD values were determined across clinical ranges in the phantom. Distortion was also studied. Contours of head and neck organs-at-risk (OAR) were drawn and applied to extract T1, T2, and PD. These values were plotted against each other, clusters were computed, and their separability significance was determined to evaluate SyntheticMR for differentiating tumor and normal tissue.
The Lin's Concordance Correlation Coefficient between the measured and phantom reference values was above 0.97 for both the MR-Sim and MR-Linac. No significant levels of distortion were measured. The mean bias between the measured and phantom reference values across repeated scans was below 6% for T1, 11% for T2, and 6% for PD for both the MR-Sim and MR-Linac. For T1 versus T2 and T1 versus PD, the GTV contour exhibited perfect purity against neighboring OARs, while being 0.7 for T2 versus PD. All cluster significance levels between the GTV and the nearest OAR, the tongue, using the SigClust method was p < 0.001.
The technical feasibility of SyntheticMR was confirmed. Application of this technique to the head and neck adaptive radiation therapy workflow can enrich the current quantitative biomarker landscape.
合成磁共振成像（SyntheticMR）能够在短时间内采集生成定量弛豫测量图和合成对比加权磁共振成像（MRI）图像。近年来，它在诊断领域受到了关注，然而，尚无研究探讨其在磁共振模拟（MR-Simulation）或磁共振直线加速器（MR-Linac）系统上的可行性，特别是作为头颈部自适应放射肿瘤学工作流程的一部分。
证明其可行性将有助于快速提取定量生物标志物，从而用于指导自适应放射治疗决策。
使用SyntheticMR在MR-Simulation和MR-Linac设备上对两个体模、两名健康志愿者和一名患者进行扫描，扫描时间在4至6分钟之间。在体模的临床范围内确定测量的与参考定量T1、T2和质子密度（PD）值之间的相关性。还研究了图像畸变情况。绘制头颈部危及器官（OAR）的轮廓，并用于提取T1、T2和PD值。将这些值相互绘制，计算聚类，并确定其可分离性的显著性，以评估SyntheticMR区分肿瘤组织和正常组织的能力。
对于MR-Sim和MR-Linac，测量值与体模参考值之间的林氏一致性相关系数均高于0.97。未测量到显著的图像畸变水平。对于MR-Sim和MR-Linac，在重复扫描中，测量值与体模参考值之间的平均偏差对于T1低于6%，对于T2为11%，对于PD为6%。对于T1与T2以及T1与PD，大体肿瘤体积（GTV）轮廓相对于相邻OAR显示出完美的纯度，而对于T2与PD则为0.7。使用SigClust方法，GTV与最接近的OAR（舌头）之间的所有聚类显著性水平均为p < 0.001。
证实了SyntheticMR的技术可行性。将该技术应用于头颈部自适应放射治疗工作流程可丰富当前的定量生物标志物情况。
