Zhang Yanjun, Liu Peng, Fang Chenyun, Xi Yarui, Qiao Zhiwei
School of Computer and Information Technology, Shanxi University, Taiyuan, China.
Department of Big Data and Intelligent Engineering, Shanxi Institute of Technology, Yangquan, China.
Quant Imaging Med Surg. 2025 Sep 1;15(9):8471-8490. doi: 10.21037/qims-2025-8. Epub 2025 Aug 15.
Electron paramagnetic resonance imaging (EPRI)-based oxygen imaging technology enables adaptive radiation therapy, thereby improving tumor control rates. However, the long scanning time limits the development of EPRI. In this study, we endeavored to reduce the scanning time. The general method is sparse reconstruction; if it can be collected in limited-angle range under sparse conditions, the scanning time can be further shortened.
Based on the abovementioned theory, we performed sparse acquisition based on limited-angle range to further accelerate scanning. Moreover, high-order constraints were introduced into the directional total variation (DTV) algorithm to suppress staircase artifacts, and we proposed a high-order DTV (HDTV) model and derived the Chambolle-Pock (CP) solving algorithm. We aimed to realize three-dimensional (3D) sparse and limited-angle EPRI with high precision and thus accelerate the scanning time.
The correctness of the HDTV-CP algorithm was validated on simulation data and the limited-angle and sparse reconstruction ability was investigated using real data. The results indicate that the HDTV method effectively suppresses limited-angle artifacts, sparse artifacts, and staircase artifacts while preserving the edge and texture features. Our method showed significant improvements compared to the classic TV method. The normalized root mean square error (nRMSE) decreased from 0.34 to 0.16, and the Pearson correlation coefficient (PCC) increased from 0.93 to 0.98 based on 50 views within half the angular range.
For the first time, we combined the limited-angle and sparse problems. The HDTV method may realize 16 times acceleration while ensuring the imaging quality in certain situations. The findings of this study can also extend to the field of limited-angle computed tomography (CT) image reconstruction.
基于电子顺磁共振成像（EPRI）的氧成像技术可实现自适应放射治疗，从而提高肿瘤控制率。然而，较长的扫描时间限制了EPRI的发展。在本研究中，我们致力于缩短扫描时间。一般方法是稀疏重建；如果能在稀疏条件下于有限角度范围内进行采集，则可进一步缩短扫描时间。
基于上述理论，我们进行了基于有限角度范围的稀疏采集以进一步加速扫描。此外，将高阶约束引入方向总变分（DTV）算法以抑制阶梯状伪影，我们提出了高阶DTV（HDTV）模型并推导了Chambolle-Pock（CP）求解算法。我们旨在高精度地实现三维（3D）稀疏和有限角度EPRI，从而加快扫描时间。
HDTV-CP算法的正确性在模拟数据上得到验证，并使用真实数据研究了有限角度和稀疏重建能力。结果表明，HDTV方法在保留边缘和纹理特征的同时，有效抑制了有限角度伪影、稀疏伪影和阶梯状伪影。与经典TV方法相比，我们的方法有显著改进。基于在半个角度范围内的50个视图，归一化均方根误差（nRMSE）从0.34降至0.16，皮尔逊相关系数（PCC）从0.93增至0.98。
我们首次将有限角度和稀疏问题结合起来。HDTV方法在某些情况下可在确保成像质量的同时实现16倍加速。本研究结果也可扩展到有限角度计算机断层扫描（CT）图像重建领域。
