Dose-Averaged LET Evaluation in Head and Neck Adenoid Cystic Carcinoma Patients for Carbon-Ion Radiotherapy

Purpose: In carbon ion radiation therapy (CIRT), the dose-averaged LET (LETd) is one of the important factors in determining clinical outcomes. In order to investigate the local control of adenoid cystic carcinoma (ACC) and the optic neuropathy of optic nerve (ON)s in CIRT, the effects of the LETd were evaluated clinically. We propose novel tumor control probability (TCP) and normal tissue complication probability (NTCP) models with D90-value of RBE-weighted dose and LETd as clinical parameters.Methods and Materials: Total 99 patients with head and neck ACC who received CIRT at the National Institute of Radiological Sciences were investigated. The physical dose and LETd distributions for each patient were recalculated using in-house treatment planning system. For ACC tumor, minimum-value of dose-averaged LET and D90-value of RBE-weighted dose as an indicator of evaluation were estimated. For ONs, maximum-value of LETd and maximum-value of RBE-weighted dose were evaluated.Results: For each prescribed RBE-weighted dose of 57.6 and 64 Gy (RBE), no statistical significance for local control by RBE-weighted dose was found, but for 64 Gy (RBE), we observed the LETd may be a marginally significant. For ONs, it was obvious that the optic neuropathy had a greater effect from RBE-weighted dose rather than dose-averaged LET. The proposed models could be applied to both TCP and NTCP prediction, and was found that the clinical outcomes from low to high LETd region were predictable.Conclusions: We analysed clinically the physical dose and LETd distributions for 99 patients with head and neck ACC. Our results indicated that LETd may be a determining factor for local control for ACC tumors. For ON, it was obvious that the RBE-weighted dose was related to optic neuropathy rather than LETd. The proposed approach may be helpful to predict whether LETd will affect clinical outcomes and be useful when constraining not only RBE-weighted dose but also LETd.AAPM202

Assesment of F-FDG PET/CT texture analysis to discriminate NSCLC from radiation pneumonitis after CIRT

Aim: The differentiation of local recurrence from a primary tumor and radiation pneumonitis (RP) is critically important for selecting optimal clinical therapeutic strategies to manage post carbon-ion radiotherapy (CIRT) in patients with non-small cell lung cancer (NSCLC). Although 18F-FDG PET/CT (FDG-PET/CT) plays a key role in the metabolic imaging of patients with NSCLC who require CIRT management, PET/CT diagnosis based on SUVmax cannot always distinguish between NSCLC and RP. The present study aimed to determine whether FDG-PET/CT texture parameters can differentiate NSCLC from RP after CIRT.Material and Methods: We retrospectively analyzed FDG-PET/CT image data from 32 patients with histopathologically proven NSCLC who were scheduled to undergo CIRT, and 31 patients who were diagnosed with RP after CIRT (50.0 Gy in 4 fractions/day). Radiation pneumonitis was diagnosed by biopsy or at clinical follow-up > 1 year after CIRT. Volumes of interest (VOI) on tumors were delineated using a threshold of 40% of the maximum standard uptake value (SUVmax) in each lesion. The SUV parameters of SUVmax, SUVpeak, SUVmean, metabolic tumor volume (MTV), total lesion glycolysis (TLG) and seven typical texture parameters of FDG-PET/CT were determined using PETSTAT image-analysis software. Data were statistically compared between NSCLC and RP using nonparametric Wilcoxon rank sum tests. Diagnostic accuracy was assessed using ROC curves.Results: Among SUV parameters, MTV (p < 0.0001) and TLG (p = 0.001) significantly differed between NSCLC and RP. The feature quantities of texture parameters, namely, GLRLM, GLSZM, NGLCM3D, NGLCM and NGTDM significantly differed between NSCLC and RP. The areas under the receiver operating characteristics (ROC) curves (AUC) were as follows: SUVmax 0.64, MTV 0.86, TLG 0.75, GLRLM 0.83, GLSZM 0.76, NGLCM3D 0.71, NGLCM 0.72 and GTDM 0.82. Diagnostic accuracy was better using GLRLRM or NGTDM than SUVmax (p < 0.01). Conclusion: The texture parameters of FDG-PET/CT were useful to differentiate NSCLC from radiation pneumonitis after CIRT, and GLRLM and NGTDM in particular would be promising parameters with excellent diagnostic accuracy.EANM2019(ヨーロッパ核医学会

Preliminary Clinical Analysis with Dose-Averaged LET Calculation for Head and Neck Cancer Patients Treated by Using Carbon-Ion Radiotherapy

Purpose: For head and neck cancer patients treated with carbon-ion radiotherapy (CIRT), normal tissues such as brain and optic nerve are close to the irradiation field such that those may receive radiation damage. In order to estimate their clinical results, a dose-averaged LET (LETd) calculation tool was developed. We focused on the usefulness of LETd as a clinical analytical parameter.Methods: In-house Heavy Ion Plan (HIPLAN) treatment planning system was used in the CIRT with a wobbler-scattering method. We developed the LETd and its standard deviation (LETdSD) calculation tool, and implemented in the HIPLAN. 33 head and neck patients treated with CIRT, who had follow-up more than 3 years and did not receive additional radiotherapy, were selected in order to evaluate local control and optic neuropathy. LETd and LETdSD for these 33 patients were calculated using the analysis tool.Results: By implementing the clinical analysis tool in HIPLAN, it was possible to efficiently calculate and analyze the LETd and LETdSD for each patient. Of the 33 patients, 13 had local recurrences and 8 had optic neuropathies. Among 33 with and without recurrence cases, the mean LETd values in the PTV were 58.7±5.4 for with recurrence and 61.7±6.9 keV/m for without recurrence, respectively. On the other hand, the mean LETd values were 45.6±12.8 for with optic neuropathy and 29.0±19.0 keV/m for without optic neuropathy (p-value=0.046).Conclusion: We developed the LETd and LETdSD calculation tool and analyzed 33 patients of head and neck cancer for local control and optic neuropathy. Although the mean LETd in the PTV were similar values between cases with and without recurrence, we could observe the usefulness of the LETd analysis for optic neuropathy cases. We will continue to analyze more patients in the future.AAPM202

RBE calculation using the Survival simulation tool for HSG, V79 and CHO cells irradiated by 12C, 20Ne and 3He ions

Purpose: The clinical dose in carbon ion radiotherapy with wobbler method at National Institute of Radiological Sciences in Japan is defined by calculating the biological dose based on RBE for human salivary gland (HSG) cells, and normalizing it to the clinical RBE value obtained by neutron radiotherapy. However, irradiated various tumors and normal tissues are actually different from HSG cells. Therefore, the predicted biological dose for irradiated field may have large uncertainty. In order to estimate the RBE for various cells, we introduced radiobiological computation software ‘Survival’, and tried to calculate the RBE using the ‘Survival’ for three typical cells irradiated by each ions.Methods: We used the biological dose analysis software ‘Survival’. Particle Irradiation Data Ensemble (PIDE) ver.3.2 was used as literature data on past cell irradiation. RBE (RBESurvival) values were calculated by analyzing cell survival rate with the ‘Survival’ using PIDE irradiation conditions. Microdosimetric Kinetic Model (MKM) as a biological effect model was used in this study. The target cells were HSG, V79 and CHO cells, and the irradiated particles were 12C, 20Ne, and 3He. The linear energy transfer (dose averaged LET: LETD) described in PIDE was used. By comparing these with RBE (RBEPIDE) values obtained from the PIDE, the RBE values calculated by using the ‘Survival’ was evaluated. Results: We calculated the RBE values for HSG, V79 and CHO cells irradiated by 12C, 20Ne, and 3He ions by using the ‘Survival’. The RBESurvival values were generally consistent with RBEPIDE values for them.Conclusion: RBE calculations by using the ‘Survival’ for HSG, V79 and CHO cells irradiated by 12C, 20Ne, and 3He ions were evaluated in this study. The ‘Survival’ could roughly estimate the RBE for three typical cells. In the future, we will evaluate the RBE calculation accuracy of the ‘Survival’ for various cells.AAPM202

Differentiation between non-small cell lung cancer and radiation pneumonitis after carbon-ion radiotherapy by FDG-PET/CT metabolic parameters

Objectives: In management after carbon-ion radiotherapy (CIRT) in patients with non-small cell lung cancer (NSCLC, LC), differentiation of local recurrence or presence of the tumor and radiation pneumonitis (RP) is one of paramount importance for the following clinical therapeutic strategy. 18F-FDG PET/CT (FDG-PET/CT) is playing a key metabolic imaging in management of CIRT for LC patients, however PET/CT diagnosis using SUVmax parameter often encounters cases where it is difficult to distinguish between LC and RP. The aim of this study is to assess FDG-PET/CT metabolic parameters such as SUVpeak, MTV and TLG for differentiating LC and RP after CIRT.Methods: We retrospectively analyzed FDG-PET/CT image data of histopathologically proven 19 LC patients who were scheduled to undergo CIRT and 28 patients who were diagnosed having RP after CIRT (50.0 Gy / 1 fraction). RP was diagnosed by biopsy or by clinical follow-up more than 1 year after CIRT. Volumes of interest (VOI) on tumors were delineated using a threshold of 40% of the maximum standard uptake value (SUVmax) in each lesion. SUVmax, SUVpeak, MTV and TLG which were metabolic parameters of FDG-PET/CT were determined using an image-analysis software. Statistical analysis was performed between LC and RP using nonparametric Wilcoxon rank sum test. The diagnostic accuracy by ROC analysis was also assessed.Results: As a result of the test, SUVmax: LC 4.446 ± 0.552, RP 2.329 ± 0.255 (p <0.001), MTV: LC 10.59 ± 1.333, RP 46.94 ± 6.073 (p <0.0001), TLG: LC 30.66 ± 7.096, RP 63.35 ± 9.177 p <0.005), and significant differences were observed in all indices.The area under the ROC curve (area under curve, AUC) was SUVmax: 0.80, MTV: 0.96, TLG: 0.77, and the diagnostic accuracy of MTV was the highest among these FDG-PET/CT metabolic parameters.Conclusions: In differentiation between NSCLC and radiation pneumonitis after CIRT, FDG-PET/CT metabolic parameters were useful, and MTV in particular would be an appropriate parameter with high diagnostic accuracy.SNMMI 2019 Annual Meetin

Differentiation between non-small cell lung cancer and radiation pneumonitis after carbon-ion radiotherapy by 18F-FDG PET/CT texture analysis

The differentiation of non-small cell lung cancer (NSCLC) and radiation pneumonitis (RP) is critically essential for selecting optimal clinical therapeutic strategies to manage post carbon-ion radiotherapy (CIRT) in patients with NSCLC. The aim of this study was to assess the ability of F-FDG PET/CT metabolic parameters and its textural image features to differentiate NSCLC from RP after CIRT to develop a differential diagnosis of malignancy and benign lesion. We retrospectively analyzed F-FDG PET/CT image data from 32 patients with histopathologically proven NSCLC who were scheduled to undergo CIRT and 31 patients diagnosed with RP after CIRT. The SUV parameters, metabolic tumor volume (MTV), total lesion glycolysis (TLG) as well as fifty-six texture parameters derived from seven matrices were determined using PETSTAT image-analysis software. Data were statistically compared between NSCLC and RP using Wilcoxon rank-sum tests. Diagnostic accuracy was assessed using receiver operating characteristics (ROC) curves. Several texture parameters significantly differed between NSCLC and RP (p < 0.05). The parameters that were high in areas under the ROC curves (AUC) were as follows: SUV, 0.64; GLRLM run percentage, 0.83 and NGTDM coarseness, 0.82. Diagnostic accuracy was improved using GLRLM run percentage or NGTDM coarseness compared with SUV (p < 0.01). The texture parameters of F-FDG uptake yielded excellent outcomes for differentiating NSCLC from radiation pneumonitis after CIRT, which outperformed SUV-based evaluation. In particular, GLRLM run percentage and NGTDM coarseness of F-FDG PET/CT images would be appropriate parameters that can offer high diagnostic accuracy