## 4 Discussion
(mean DC: 0.80/0.80) [30]. Differences in imaging modality (MRI vs. computed tomography (CT)) and contouring image dimensions (2D vs. 3D) may account for this discrepancy. For- liver patients, our agreements (mean DC: 0.78/0.69) are lower than those reported by [PERSON] et al. (mean DC: 0.85/0.79) [46]. This difference can be attributed to variations in imaging planes (sagittal vs. axial) and the use of contrast enhancement (without vs. with enhancement). In addition, the relatively low manual intra-/inter-observer agreements found for the liver patients in this study may be due to the low tumor contrast and the fact that the contouring of GTV was based on what the radiation oncologists could visibly see on the images, taking into account their clinical judgment. Furthermore, upon comparing the Automatic vs. Manual SESS metrics, our agreements for lung patients (mean DC: 0.89 (0.05), HD: 2.6 (0.9) mm) were similar to those reported by [PERSON] et al. (mean DC: 0.90 (0.03), HD: 3.8 (1.6) mm) [32]. The algorithm used by [PERSON] et al. [32] does not work for liver and prostate patients. Due to the substantive differences in the study protocols, any direct comparison between our results and those in the previous studies is not warranted. To summarize, this work allows one to evaluate whether a given tumor-autocontouring algorithm can be as accurate as human experts' contouring for different tumor sites and, thereby, determine whether it can be used clinically. With the fast contouring ability (54 ms/contour) compared to that of experts (~9 s/contour in this study), along with the similar contouring accuracy, the presented algorithm fulfills the crucial criteria for realizing nifteRT, which enables a treatment margin reduction without compromising tumor coverage. nifteRT has the potential to make a significant clinical impact in the treatment of abdominothoracic cancer patients who are unable to tolerate conventional motion management techniques, such as breath-hold or abdominal compression, yet still require tight treatment margins to avoid serious complications. For prostate cancer, nifteRT may offer real-time surveillance during radiation delivery, helping to reduce the risk of substantial geometric misses that could lead to severe bladder or rectal toxicities. Most importantly, nifteRT accomplishes this without the need for invasive surgical procedures. By allowing for both dose escalation to improve tumor control probability and margin reduction to minimize the risk of normal tissue complications, nifteRT could meaningfully enhance the therapeutic ratio and expand treatment options for patients with mobile or deformable tumors who currently have limited alternatives. One limitation of this study is that the patients were imaged on a 3 T MRI system, although a linac-MR system typically operates at a lower field strength (e.g., 0.5 T for Alberta Linac-MR, 1.5 T for Elekta, 0.35 T for ViewRay) [5; 6; 7; 8; 47]. Hence, depending on the system used, the image quality (e.g., contrast-to-noise ratio (CNR), signal-to-noise ratio) will be different. However, regardless of the field strength used for imaging, the CNR will undoubtedly have an effect on contouring accuracy for both the experts and the algorithm alike. Rather than quantifying the results at a specific field strength, future work could investigate contouring accuracy with respect to the CNR, which could be useful for real-time tracking on all imaging sequences and field strengths. The algorithm's performance with 0.5 T linac-MR images, as well as noise-added 3 T images, is currently being investigated. For the Alberta Linac-MR system, patient treatments and MR imaging are being performed in clinical trials. Another limitation noted by one of the radiation oncologists is that during manual contouring, the pixels could not always conform to the tumor image, especially for small tumors.