AbstractObjective To qualitatively analyze and auto-discriminate intrafraction prostate movement patterns based on transperineal ultrasound (TPUS) technique and linear discriminant analysis (LDA) method, which lays a solid foundation for individualized precise radiotherapy. Methods A total of 1265 intrafraction motion trajectories and millions of monitoring data were recorded by TPUS from 61 prostate cancer patients. Seven typical patterns were considered:stable at baseline, slight transient excursion, persistent excursion and continuous drift, as well as obvious transient excursion, persistent excursion and continuous drift. Motion trajectory diagrams associated with the displacement-time function were generated by MATLAB programming. Valuable features were selected and different patterns were identified. Discriminant accuracy and receiver operating characteristic (ROC) curve were utilized to evaluate the performance of LDA model. Results Four movement patterns were found per patient during the whole treatment process, and unstable type was occupied at (35.00±21.49)%. With the increase of treatment times, motion trajectories did not show an increasingly stable trend, and the appearance of different patterns was extremely irregular. After quantitative analysis, discriminant accuracy of LDA method was 90.4% for the training set and 89.5% for the testing set, with a sensitivity of 84.9% and a specificity of 91.1%. Conclusion Intrafraction movement patterns are characterized by diversity and randomness. The LDA method can be used to discriminate different movement patterns effectively, and the unknown samples can be identified by discriminant equations and centroid coordinates.
Fund:National Natural Science Foundation of China (81502651);Beijing Natural Science Foundation (7182164);Specific Project of Clinical Trials of Beijing Municipal Science and Technology Commission (Z161100000516041)
Gao Yan,Zhao Bo,Gao Xianshu et al. Auto-analysis intrafraction prostate movement patterns based on transperineal ultrasound real-time tracking system and linear discriminant model[J]. Chinese Journal of Radiation Oncology, 2020, 29(6): 455-460.
Gao Yan,Zhao Bo,Gao Xianshu et al. Auto-analysis intrafraction prostate movement patterns based on transperineal ultrasound real-time tracking system and linear discriminant model[J]. Chinese Journal of Radiation Oncology, 2020, 29(6): 455-460.
[1] Miralbell R, Roberts SA, Zubizarreta E, et al. Dose-fractionation sensitivity of prostate cancer deduced from radiotherapy outcomes of 5969 patients in seven international institutional datasets:alpha/beta= 1.4(0.9-2.2) Gy[J]. Int J Radiat Oncol Biol Phys, 2012, 82(1):e17-24. DOI:10.1016/j.ijrobp.2010.10.075. [2] Catton CN, Lukka H, Gu CS, et al. Randomized trial of a hypofractionated radiation regimen for the treatment of localized prostate cancer[J]. J Clin Oncol, 2017, 35(17):1884-1890. DOI:10.1200/jco.2016.71.7397. [3] Shaikh T, Li T, Handorf EA, et al. Long-term patient-reported outcomes from a phase 3 randomized prospective trial of conventional versus hypofractionated radiation therapy for localized prostate cancer[J]. Int J Radiat Oncol Biol Phys, 2017, 97(4):722-731. DOI:10.1016/j.ijrobp.2016.12.034. [4] King CR, Freeman D, Kaplan I, et al. Stereotactic body radiotherapy for localized prostate cancer:pooled analysis from a multi-institutional consortium of prospective phase Ⅱ trials[J]. Radiother Oncol, 2013, 109(2):217-221. DOI:10.1016/j.radonc.2013.08.030. [5] Sihono DSK, Ehmann M, Heitmann S, et al. Determination of intrafraction prostate motion during external beam radiation therapy with a transperineal 4-dimensional ultrasound real-time tracking system[J]. Int J Radiat Oncol Biol Phys, 2018, 101(1):136-143. DOI:10.1016/j.ijrobp.2018.01.040. [6] 亓昕, 赵波, 秦尚彬, 等. 经会阴实时超声图像引导技术在前列腺癌放疗中应用[J]. 中华放射肿瘤学杂志, 2018, 27(7):675-679. DOI:10.3760/cma.j.issn.1004-4221.2018.07.011. Qi X, Zhao B, Qin SB, et al. Application of real-time transperineal ultrasound in radiotherapy of prostate cancer-4D analysis of intra-fractional prostate motion[J]. Chin J Radiat Oncol, 2018, 27(7):675-679. DOI:10.3760/cma.j.issn.1004-4221.2018.07.011. [7] Li JS, Lin MH, Buyyounouski MK, et al. Reduction of prostate intrafractional motion from shortening the treatment time[J]. Phys Med Biol, 2013, 58(14):4921-4932. DOI:10.1088/0031-9155/58/14/4921. [8] Xie YQ, Djajaputra D, King CR, et al. Intrafractional motion of the prostate during hypofractionated radiotherapy[J]. Int J Radiat Oncol Biol Phys, 2008, 72(1):236-246. DOI:10.1016/j.ijrobp.2008.04.051. [9] Pommer T, Oh JH, Munck AF,et al. Simulating intrafraction prostate motion with a random walk model[J]. Adv Radiat Oncol, 2017, 2(3):429-436. DOI:10.1016/j.adro.2017.03.005. [10] Kupelian P, Willoughby T, Mahadevan A, et al. Multi-institutional clinical experience with the Calypso System in localization and continuous, real-time monitoring of the prostate gland during external radiotherapy[J]. Int J Radiat Oncol Biol Phys, 2007, 67(4):1088-1098. DOI:10.1016/j.ijrobp.2006.10.026. [11] Malinowski KT, Noel C, Roy M, et al. Efficient use of continuous, real-time prostate localization[J]. Phys Med Biol, 2008, 53(18):4959-4970. DOI:10.1088/0031-9155/53/18/007. [12] Keall PJ, Ng JA, Juneja P, et al. Real-time 3D image guidance using a standard LINAC:measured motion, accuracy, and precision of the first prospective clinical trial of kilovoltage intrafraction monitoring-guided gating for prostate cancer radiation therapy[J]. Int J Radiat Oncol Biol Phys, 2016, 94(5):1015-1021. DOI:10.1016/j.ijrobp.2015.10.009. [13] da Silva CA, Silva AC, Netto SMB, et al. Lung nodules classification in CT images using Simpson′s index, geometrical measures and one-class SVM[M]. Heidelberg:Springer Berlin Heidelberg, 2009:810-822. [14] Shams R, Xiao Y, Hebert F, et al. Assessment of rigid registration quality measures in ultrasound-guided radiotherapy[J]. IEEE Trans Med Imaging, 2018, 37(2):428-437. DOI:10.1109/tmi.2017.2755695. [15] Jani SS, Low DA, Lamb JM. Automatic detection of patient identification and positioning errors in radiation therapy treatment using 3-dimensional setup images[J]. Pract Radiat Oncol, 2015, 5(5):304-311. DOI:10.1016/j.prro.2015.06.004. [16] Liao S, Jain AK, Li SZ. Partial face recognition:alignment-free approach[J]. IEEE Trans Pattern Anal Mach Intell, 2013, 35(5):1193-1205. DOI:10.1109/tpami.2012.191. [17] Ballhausen H, Li M, Hegemann NS, et al. Intra-fraction motion of the prostate is a random walk[J]. Phys Med Biol, 2015, 60(2):549-563. DOI:10.1088/0031-9155/60/2/549.
2020, Vol. 29 
