Assessing the uncertainty in a normal tissue complication probability difference (∆NTCP): radiation-induced liver disease (RILD) in liver tumour patients treated with proton vs X-ray therapy

Kobashi, Keiji; Prayongrat, Anussara; Kimoto, Tsunenobu; Toramatsu, Chie; Dekura, Yasuhiro; Katoh, Norio; Shimizu, Satoru; Ito, Yoichi M.; Shirato, Hiroki

doi:10.1093/jrr/rry018

Cited by 6 publications

(5 citation statements)

References 29 publications

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“…Even more simplistic and thus complicating IMRT/IMPT comparison, the majority of current approaches for modeling of radiation dose-response rely on single parameters such as mean dose or generalized effective uniform dose to an OAR represented by a single segmented (contoured) region-of-interest (Yorke 2001, Troeller et al 2015. Data suggest that such NTCP models might fail to discriminate even at the level of physical dose whether an individual proton plan is effectively ranked superior to a comparison photon plan (Chaikh et al 2018, Kobashi et al 2018.…”

Section: Current and Future Challengesmentioning

confidence: 99%

Roadmap: proton therapy physics and biology

Paganetti¹,

Beltran²,

Both³

et al. 2021

Phys. Med. Biol.

109

111

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The treatment of cancer with proton radiation therapy was first suggested in 1946 followed by the first treatments in the 1950s. As of 2020, almost 200 000 patients have been treated with proton beams worldwide and the number of operating proton therapy (PT) facilities will soon reach one hundred. PT has long moved from research institutions into hospital-based facilities that are increasingly being utilized with workflows similar to conventional radiation therapy. While PT has become mainstream and has established itself as a treatment option for many cancers, it is still an area of active research for various reasons: the advanced dose shaping capabilities of PT cause susceptibility to uncertainties, the high degrees of freedom in dose delivery offer room for further improvements, the limited experience and understanding of optimizing pencil beam scanning, and the biological effect difference compared to photon radiation. In addition to these challenges and opportunities currently being investigated, there is an economic aspect because PT treatments are, on average, still more expensive compared to conventional photon based treatment options. This roadmap highlights the current state and future direction in PT categorized into four different themes, 'improving efficiency', 'improving planning and delivery', 'improving imaging', and 'improving patient selection'.

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Section: Current and Future Challengesmentioning

confidence: 99%

Roadmap: proton therapy physics and biology

Paganetti¹,

Beltran²,

Both³

et al. 2021

Phys. Med. Biol.

109

111

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“…and Prayongrat et al . proposed the use of the 95% CI-LB of ΔNTCP as a threshold to be more conservative [ 7 , 32 ]. According to the definition of CI, there was a 95% probability that the true ΔNTCP value in the population would be larger than the 95% CI-LB whereas there was a 50% probability that the true value would be larger than the central estimate.…”

Section: Discussionmentioning

confidence: 99%

Assessment of the confidence interval in the multivariable normal tissue complication probability model for predicting radiation-induced liver disease in primary liver cancer

Prayongrat

Srimaneekarn

Sriswasdi

et al. 2021

Journal of Radiation Research

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We developed a confidence interval-(CI) assessing model in multivariable normal tissue complication probability (NTCP) modeling for predicting radiation-induced liver disease (RILD) in primary liver cancer patients using clinical and dosimetric data. Both the mean NTCP and difference in the mean NTCP (ΔNTCP) between two treatment plans of different radiotherapy modalities were further evaluated and their CIs were assessed. Clinical data were retrospectively reviewed in 322 patients with hepatocellular carcinoma (n = 215) and intrahepatic cholangiocarcinoma (n = 107) treated with photon therapy. Dose–volume histograms of normal liver were reduced to mean liver dose (MLD) based on the fraction size-adjusted equivalent uniform dose. The most predictive variables were used to build the model based on multivariable logistic regression analysis with bootstrapping. Internal validation was performed using the cross-validation leave-one-out method. Both the mean NTCP and the mean ΔNTCP with 95% CIs were calculated from computationally generated multivariate random sets of NTCP model parameters using variance–covariance matrix information. RILD occurred in 108/322 patients (33.5%). The NTCP model with three clinical and one dosimetric parameter (tumor type, Child–Pugh class, hepatitis infection status and MLD) was most predictive, with an area under the receiver operative characteristics curve (AUC) of 0.79 (95% CI 0.74–0.84). In eight clinical subgroups based on the three clinical parameters, both the mean NTCP and the mean ΔNTCP with 95% CIs were able to be estimated computationally. The multivariable NTCP model with the assessment of 95% CIs has potential to improve the reliability of the NTCP model-based approach to select the appropriate radiotherapy modality for each patient.

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“…For photon beam therapy, mean liver dose and V 30Gy appeared to be the useful parameters in conformal radiotherapy [ 25 , 26 ]. The normal tissue complication probability (NTCP) models involving mean liver dose and generalized equivalent uniform dose were also developed to estimate the risk of RILD [ 27 , 28 ]. The concept of normal liver sparing in terms of achieving a certain amount of preserved liver receiving a dose under a certain threshold arose in the era of stereotactic body radiation therapy (SBRT).…”

Section: Discussionmentioning

confidence: 99%

Capacity of proton beams in preserving normal liver tissue during proton beam therapy for hepatocellular carcinoma

Tsai

Takei

Iizumi

et al. 2020

Journal of Radiation Research

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Unirradiated liver volume (ULV) preservation rate is an important factor associated with radiation-induced liver disease (RILD) in patients with hepatocellular carcinoma (HCC) undergoing proton beam therapy (PBT). The purpose of this study is to identify the predictors for ULV preservation and quantify the capacity of proton beams in normal liver sparing during PBT. We reviewed planning data of 92 patients with single intrahepatic HCC tumors undergoing PBT. The potential clinical and planning factors that may affect ULV preservation were involved in multiple linear regression for ULV preservation rate. The significant factors were determined to be predictors and their influences were quantified. The median ULV preservation rate was 62.08%. All the assessed clinical factors showed significant effects on ULV preservation rate: clinical target volume (CTV), P < 0.001; portal vein tumor thrombosis (PVTT), P = 0.010; left lobe tumor, P = 0.010. In contrast, none of the planning factors demonstrated significance. The coefficients of significant factors in multiple linear regression were 60.85 for intercept, −0.02 for CTV, −9.01 for PVTT and 8.31 for left lobe tumors. The capacity of proton beams to spare normal liver tissue during PBT for HCC is mainly affected by clinical factors. The baseline of the ULV preservation rate is 60.85%, decreasing 0.02% with each milliliter of CTV increase and 9.01% for tumors with PVTT, and increasing 8.31% for tumors limited to the left lobe. Further clinical studies should be carried out to correlate our dosimetric findings with clinical outcomes.

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Assessing the uncertainty in a normal tissue complication probability difference (∆NTCP): radiation-induced liver disease (RILD) in liver tumour patients treated with proton vs X-ray therapy

Cited by 6 publications

References 29 publications

Roadmap: proton therapy physics and biology

Roadmap: proton therapy physics and biology

Assessment of the confidence interval in the multivariable normal tissue complication probability model for predicting radiation-induced liver disease in primary liver cancer

Capacity of proton beams in preserving normal liver tissue during proton beam therapy for hepatocellular carcinoma

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