Impact of incorporating visual biofeedback in 4D MRI.

Precise radiation therapy (RT) for abdominal lesions is complicated by respiratory motion and suboptimal soft tissue contrast in 4D CT. 4D MRI offers improved con-trast although long scan times and irregular breathing patterns can be limiting. To address this, visual biofeedback (VBF) was introduced into 4D MRI. Ten volunteers were consented to an IRB-approved protocol. Prospective respiratory-triggered, T2-weighted, coronal 4D MRIs were acquired on an open 1.0T MR-SIM. VBF was integrated using an MR-compatible interactive breath-hold control system. Subjects visually monitored their breathing patterns to stay within predetermined tolerances. 4D MRIs were acquired with and without VBF for 2- and 8-phase acquisitions. Normalized respiratory waveforms were evaluated for scan time, duty cycle (programmed/acquisition time), breathing period, and breathing regularity (end-inhale coefficient of variation, EI-COV). Three reviewers performed image quality assessment to compare artifacts with and without VBF. Respiration-induced liver motion was calculated via centroid difference analysis of end-exhale (EE) and EI liver contours. Incorporating VBF reduced 2-phase acquisition time (4.7 ± 1.0 and 5.4 ± 1.5 min with and without VBF, respectively) while reducing EI-COV by 43.8% ± 16.6%. For 8-phase acquisitions, VBF reduced acquisition time by 1.9 ± 1.6 min and EI-COVs by 38.8% ± 25.7% despite breathing rate remaining similar (11.1 ± 3.8 breaths/min with vs. 10.5 ± 2.9 without). Using VBF yielded higher duty cycles than unguided free breathing (34.4% ± 5.8% vs. 28.1% ± 6.6%, respectively). Image grading showed that out of 40 paired evaluations, 20 cases had equivalent and 17 had improved image quality scores with VBF, particularly for mid-exhale and EI. Increased liver excursion was observed with VBF, where superior-inferior, anterior-posterior, and left-right EE-EI displacements were 14.1± 5.8, 4.9 ± 2.1, and 1.5 ± 1.0 mm, respectively, with VBF compared to 11.9 ± 4.5, 3.7 ± 2.1, and 1.2 ± 1.4 mm without. Incorporating VBF into 4D MRI substantially reduced acquisition time, breathing irregularity, and image artifacts. However, differences in excursion were observed, thus implementation will be required throughout the RT workflow.

Technology for Innovation in Radiation Oncology.

Radiation therapy is an effective, personalized cancer treatment that has benefited from technological advances associated with the growing ability to identify and target tumors with accuracy and precision. Given that these advances have played a central role in the success of radiation therapy as a major component of comprehensive cancer care, the American Society for Radiation Oncology (ASTRO), the American Association of Physicists in Medicine (AAPM), and the National Cancer Institute (NCI) sponsored a workshop entitled "Technology for Innovation in Radiation Oncology," which took place at the National Institutes of Health (NIH) in Bethesda, Maryland, on June 13 and 14, 2013. The purpose of this workshop was to discuss emerging technology for the field and to recognize areas for greater research investment. Expert clinicians and scientists discussed innovative technology in radiation oncology, in particular as to how these technologies are being developed and translated to clinical practice in the face of current and future challenges and opportunities. Technologies encompassed topics in functional imaging, treatment devices, nanotechnology, and information technology. The technical, quality, and safety performance of these technologies were also considered. A major theme of the workshop was the growing importance of innovation in the domain of process automation and oncology informatics. The technologically advanced nature of radiation therapy treatments predisposes radiation oncology research teams to take on informatics research initiatives. In addition, the discussion on technology development was balanced with a parallel conversation regarding the need for evidence of efficacy and effectiveness. The linkage between the need for evidence and the efforts in informatics research was clearly identified as synergistic.