Academic Journal
The role of patient-and treatment-related factors and early functional imaging in late radiation-induced xerostomia in oropharyngeal cancer patients
| العنوان: | The role of patient-and treatment-related factors and early functional imaging in late radiation-induced xerostomia in oropharyngeal cancer patients |
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| المؤلفون: | Marzi S., Farneti A., Marucci L., D'urso P., Vidiri A., Gangemi E., Sanguineti G. |
| المساهمون: | Marzi, S., Farneti, A., Marucci, L., D'Urso, P., Vidiri, A., Gangemi, E., Sanguineti, G. |
| بيانات النشر: | MDPI |
| سنة النشر: | 2021 |
| المجموعة: | Sapienza Università di Roma: CINECA IRIS |
| مصطلحات موضوعية: | DCE-MRI, DWI, Oropharyngeal cancer, Parotid gland, Radiotherapy, Xerostomia |
| الوصف: | The advent of quantitative imaging in personalized radiotherapy (RT) has offered the opportunity for a better understanding of individual variations in intrinsic radiosensitivity. We aimed to assess the role of magnetic resonance imaging (MRI) biomarkers, patient-related factors, and treatment-related factors in predicting xerostomia 12 months after RT (XER12 ) in patients affected by oropharyngeal squamous cell carcinoma (OSCC). Patients with locally advanced OSCC underwent diffusion-weighted imaging (DWI) and dynamic-contrast enhanced MRI at baseline; DWI was repeated at the 10th fraction of RT. The Radiation Therapy Oncology Group (RTOG) toxicity scale was used to evaluate salivary gland toxicity. Xerostomia-related questionnaires (XQs) were administered weekly during and after RT. RTOG toxicity ≥ grade 2 at XER12 was considered as endpoint to build prediction models. A Decision Tree classification learner was applied to build the prediction models following a five-fold cross-validation. Of the 89 patients enrolled, 63 were eligible for analysis. Thirty-six (57.1%) and 21 (33.3%) patients developed grade 1 and grade 2 XER12, respectively. Including only baseline variables, the model based on DCE-MRI and V65 (%) (volume of both glands receiving doses ≥ 65 Gy) had a fair accuracy (77%, 95% CI: 66.5–85.4%). The model based on V65 (%) and XQ-Intmid (integral of acute XQ scores from the start to the middle of RT) reached the best accuracy (81%, 95% CI: 71–88.7%). In conclusion, non-invasive biomarkers from DCE-MRI, in combination with dosimetric variables and self-assessed acute XQ scores during treatment may help predict grade 2 XER12 with a fair to good accuracy. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/34944916; info:eu-repo/semantics/altIdentifier/wos/WOS:000736275100001; volume:13; issue:24; journal:CANCERS; https://hdl.handle.net/11573/1693561; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85121045687 |
| DOI: | 10.3390/cancers13246296 |
| الاتاحة: | https://hdl.handle.net/11573/1693561 https://doi.org/10.3390/cancers13246296 |
| Rights: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.2CE6B859 |
| قاعدة البيانات: | BASE |
| DOI: | 10.3390/cancers13246296 |
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