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Delta-radiomics features during radiotherapy improve the prediction of late xerostomia.

ABSTRACT: The response of the major salivary glands, the parotid glands, to radiation dose is patient-specific. This study was designed to investigate whether parotid gland changes seen in weekly CT during treatment, quantified by delta-radiomics features (?features), could improve the prediction of moderate-to-severe xerostomia at 12 months after radiotherapy (Xer12m). Parotid gland ?features were extracted from in total 68 planning and 340 weekly CTs, representing geometric, intensity and texture characteristics. Bootstrapped forward variable selection was performed to identify the best predictors of Xer12m. The predictive contribution of the resulting ?features to a pre-treatment reference model, based on contralateral parotid gland mean dose and baseline xerostomia scores (Xerbaseline) only, was evaluated. Xer12m was reported by 26 (38%) of the 68 patients included. The most predictive ?feature was the contralateral parotid gland surface change, which was significantly associated with Xer12m for all weeks (p?

SUBMITTER: van Dijk LV

PROVIDER: S-EPMC6713775 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Delta-radiomics features during radiotherapy improve the prediction of late xerostomia.

van Dijk Lisanne V LV Langendijk Johannes A JA Zhai Tian-Tian TT Vedelaar Thea A TA Noordzij Walter W Steenbakkers Roel J H M RJHM Sijtsema Nanna M NM

Scientific reports 20190828 1

The response of the major salivary glands, the parotid glands, to radiation dose is patient-specific. This study was designed to investigate whether parotid gland changes seen in weekly CT during treatment, quantified by delta-radiomics features (Δfeatures), could improve the prediction of moderate-to-severe xerostomia at 12 months after radiotherapy (Xer<sub>12m</sub>). Parotid gland Δfeatures were extracted from in total 68 planning and 340 weekly CTs, representing geometric, intensity and tex ...[more]

PMID: 31462719

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Project description:BackgroundAcute xerostomia is the most common side effect of radiation therapy (RT) for head and neck (H&N) malignancies. Investigating radiation-induced changes of computed tomography (CT) radiomics in parotid glands (PGs) and saliva amount (SA) can predict acute xerostomia during the RT for nasopharyngeal cancer (NPC).MethodsCT and SA data from 35 patients with stages I-IVB were randomly collected from an NPC clinical trial registered on the clinicaltrials.gov (ID: NCT01762514). All patients received radical treatment based on intensity-modulated RT (IMRT) with a prescription dose of 68.1 Gy in 30 fractions. The patients' ages ranged 24-72 years, and each patient had five CT sets acquired at treatment position: at the 0th, 10th, 20th, 30th fractions during the RT, and at 3-month later after the RT. The PGs for each CT set were delineated by a radiation oncologist and verified independently by another. Patients' saliva was collected every other 10 days during the RT. Acute xerostomia was evaluated based on the RTOG acute toxicity scoring and the SA. In total, 1,703 radiomics features were calculated for PGs from each CT set, including feature value at 0th fraction (FV0F), FV10F, and delta FV (ΔFV10F-0F), respectively. Extensive experiments were conducted to achieve the optimal results. RidgeCV and Recursive Feature Elimination (RFE) were used for feature selection, while linear regression was used for predicting SA30F. Four more patients were added for independent testing.ResultsSubstantial changes in various radiomics metrics of PGs were observed during the RT. Eight normalized feature value (NFV), selected from NFV0F, predicted SA10F with a mean square error (MSE) of 0.9042 and a R2 score of 0.7406. Fourteen NFV, selected from ΔNFV10F-0F, NFV0F, and NFV10F to predict SA30F, showed the best predictive ability with an MSE of 0.0569. The model predicted the level of acute xerostomia with a precision of 0.9220 and a sensitivity of 100%, compared to the clinical observed SA. For the independent test, the MSE of PSA30F was 0.0233.ConclusionsThis study demonstrated that radiation-induced acute xerostomia level could be early predicted based on the SA and radiomics changes of the PGs during IMRT delivery. SA, NFV0F, NFV10F, and especially ΔNFV10F-0F provided the best performance on acute xerostomia prediction for individual patient based on RidgeCV_RFE_LinearRegression method of delta radiomics.

Dataset Information

Delta-radiomics features during radiotherapy improve the prediction of late xerostomia.

Publications

Delta-radiomics features during radiotherapy improve the prediction of late xerostomia.

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