William Beasley1, Maria Thor2, Alan McWilliam3, Andrew Green4, Ranald Mackay3, Nick Slevin5, Caroline Olsson6, Niclas Pettersson6, Caterina Finizia7, Cherry Estilo8, Nadeem Riaz9, Nancy Y Lee9, Joseph O Deasy2, Marcel van Herk4. 1. Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom; Christie Medical Physics and Engineering, Christie NHS Foundation Trust, Manchester, United Kingdom. Electronic address: william.beasley@christie.nhs.uk. 2. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York. 3. Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom; Christie Medical Physics and Engineering, Christie NHS Foundation Trust, Manchester, United Kingdom. 4. Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom. 5. Department of Clinical Oncology, Christie NHS Foundation Trust, Manchester, United Kingdom. 6. Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden. 7. Department of Otorhinolaryngology, Institute of Clinical Sciences, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden. 8. Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York. 9. Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York.
Abstract
PURPOSE: To identify imaged regions in which dose is associated with radiation-induced trismus after head and neck cancer radiation therapy (HNRT) using a novel image-based data mining (IBDM) framework. METHODS AND MATERIALS: A cohort of 86 HNRT patients were analyzed for region identification. Trismus was characterized as a continuous variable by the maximum incisor-to-incisor opening distance (MID) at 6 months after radiation therapy. Patient anatomies and dose distributions were spatially normalized to a common frame of reference using deformable image registration. IBDM was used to identify clusters of voxels associated with MID (P ≤ .05 based on permutation testing). The result was externally tested on a cohort of 35 patients with head and neck cancer. Internally, we also performed a dose-volume histogram-based analysis by comparing the magnitude of the correlation between MID and the mean dose for the IBDM-identified cluster in comparison with 5 delineated masticatory structures. RESULTS: A single cluster was identified with the IBDM approach (P < .01), partially overlapping with the ipsilateral masseter. The dose-volume histogram-based analysis confirmed that the IBDM cluster had the strongest association with MID, followed by the ipsilateral masseter and the ipsilateral medial pterygoid (Spearman's rank correlation coefficients: Rs = -0.36, -0.35, -0.32; P = .001, .001, .002, respectively). External validation confirmed an association between mean dose to the IBDM cluster and MID (Rs = -0.45; P = .007). CONCLUSIONS: IBDM bypasses the common assumption that dose patterns within structures are unimportant. Our novel IBDM approach for continuous outcome variables successfully identified a cluster of voxels that are highly associated with trismus, overlapping partially with the ipsilateral masseter. Tests on an external validation cohort showed an even stronger correlation with trismus. These results support use of the region in HNRT treatment planning to potentially reduce trismus.
PURPOSE: To identify imaged regions in which dose is associated with radiation-induced trismus after head and neck cancer radiation therapy (HNRT) using a novel image-based data mining (IBDM) framework. METHODS AND MATERIALS: A cohort of 86 HNRT patients were analyzed for region identification. Trismus was characterized as a continuous variable by the maximum incisor-to-incisor opening distance (MID) at 6 months after radiation therapy. Patient anatomies and dose distributions were spatially normalized to a common frame of reference using deformable image registration. IBDM was used to identify clusters of voxels associated with MID (P ≤ .05 based on permutation testing). The result was externally tested on a cohort of 35 patients with head and neck cancer. Internally, we also performed a dose-volume histogram-based analysis by comparing the magnitude of the correlation between MID and the mean dose for the IBDM-identified cluster in comparison with 5 delineated masticatory structures. RESULTS: A single cluster was identified with the IBDM approach (P < .01), partially overlapping with the ipsilateral masseter. The dose-volume histogram-based analysis confirmed that the IBDM cluster had the strongest association with MID, followed by the ipsilateral masseter and the ipsilateral medial pterygoid (Spearman's rank correlation coefficients: Rs = -0.36, -0.35, -0.32; P = .001, .001, .002, respectively). External validation confirmed an association between mean dose to the IBDM cluster and MID (Rs = -0.45; P = .007). CONCLUSIONS: IBDM bypasses the common assumption that dose patterns within structures are unimportant. Our novel IBDM approach for continuous outcome variables successfully identified a cluster of voxels that are highly associated with trismus, overlapping partially with the ipsilateral masseter. Tests on an external validation cohort showed an even stronger correlation with trismus. These results support use of the region in HNRT treatment planning to potentially reduce trismus.
Authors: Lydia J Wilson; Abigail Bryce-Atkinson; Andrew Green; Yimei Li; Thomas E Merchant; Marcel van Herk; Eliana Vasquez Osorio; Austin M Faught; Marianne C Aznar Journal: Phys Med Date: 2022-05-21 Impact factor: 3.119
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