Impact of adaptive radiotherapy on survival in locally advanced nasopharyngeal carcinoma treated with concurrent chemoradiotherapy.

PURPOSE: To investigate the clinical significance of adaptive radiotherapy (ART) in locally advanced nasopharyngeal carcinoma treated with intensity-modulated radiotherapy (IMRT). MATERIALS AND METHODS: Eligible patients were treated with concurrent chemoradiotherapy using IMRT. Planning computed tomography in ART was performed during radiotherapy, and replanning was performed. Since ART was started in May 2011 (ART group), patients who were treated without ART up to April 2011 (non-ART group) were used as the historical control. The Kaplan-Meier method was used to calculate overall survival (OS), locoregional recurrence-free survival (LRFS), progression-free survival (PFS), and distant metastasis-free survival (DMFS). LRFS for the primary tumor (LRFS_P) and regional lymph node (LRFS_LN) were also studied for more detailed analysis. Statistical significance was evaluated using the log-rank test for survival. RESULTS: The ART group tended to have higher radiation doses. The median follow-up period was 127 months (range, 10 to 211 months) in the non-ART group and 61.5 months (range, 5 to 129 months) in the ART group. Compared to the non-ART group, the ART group showed significantly higher 5-year PFS (53.8% vs. 81.3%, p = 0.015) and LRFS (61.2% vs. 85.3%, p = 0.024), but not OS (80.7% vs. 80.8%, p = 0.941) and DMFS (84.6% vs. 92.7%, p = 0.255). Five-year LRFS_P was higher in the ART group (61.3% vs. 90.6%, p = 0.005), but LRFS_LN did not show a significant difference (91.9% vs. 96.2%, p = 0.541). CONCLUSION: Although there were differences in the patient backgrounds between the two groups, this study suggests the potential effectiveness of ART in improving locoregional control, especially in the primary tumor.

Probability of normal tissue complications for hematologic and gastrointestinal toxicity in postoperative whole pelvic radiotherapy for gynecologic malignancies using intensity-modulated proton therapy with robust optimization.

This retrospective treatment-planning study was conducted to determine whether intensity-modulated proton therapy with robust optimization (ro-IMPT) reduces the risk of acute hematologic toxicity (H-T) and acute and late gastrointestinal toxicity (GI-T) in postoperative whole pelvic radiotherapy for gynecologic malignancies when compared with three-dimensional conformal radiation therapy (3D-CRT), intensity-modulated X-ray (IMXT) and single-field optimization proton beam (SFO-PBT) therapies. All plans were created for 13 gynecologic-malignancy patients. The prescribed dose was 45 GyE in 25 fractions for 95% planning target volume in 3D-CRT, IMXT and SFO-PBT plans and for 99% clinical target volume (CTV) in ro-IMPT plans. The normal tissue complication probability (NTCP) of each toxicity was used as an in silico surrogate marker. Median estimated NTCP values for acute H-T and acute and late GI-T were 0.20, 0.94 and 0.58 × 10-1 in 3D-CRT; 0.19, 0.65 and 0.24 × 10-1 in IMXT; 0.04, 0.74 and 0.19 × 10-1 in SFO-PBT; and 0.06, 0.66 and 0.15 × 10-1 in ro-IMPT, respectively. Compared with 3D-CRT and IMXT plans, the ro-IMPT plan demonstrated significant reduction in acute H-T and late GI-T. The risk of acute GI-T in ro-IMPT plan is equivalent with IMXT plan. The ro-IMPT plan demonstrated potential clinical benefits for reducing the risk of acute H-T and late GI-T in the treatment of gynecologic malignances by reducing the dose to the bone marrow and bowel bag while maintaining adequate dose coverage to the CTV. Our results indicated that ro-IMPT may reduce acute H-T and late GI-T risk with potentially improving outcomes for postoperative gynecologic-malignancy patients with concurrent chemotherapy.

Daily fraction dose-adjusted radiotherapy policy to avoid prolonging the overall treatment time for early glottic squamous cell carcinoma: a single-institutional retrospective study.

The objective of this study was to determine the outcomes of radical radiotherapy for early glottic squamous cell carcinoma (EGSCC) with the policy of increasing the fraction size during radiotherapy when the overall treatment time (OTT) was expected to be prolonged. Patients diagnosed with clinical T1-2N0M0 EGSCC, who were treated with radical radiotherapy between 2008 and 2019 at Hokkaido University Hospital, were included. Patients received 66 Gy in 33 fractions for T1 disease and 70 Gy in 35 fractions for T2 disease as our standard regimen (usual group [UG]). If the OTT was expected to extend for >1 week, the dose fraction size was increased from 2.0 to 2.5 Gy from the beginning or during radiotherapy (adjusted group [AG]). At this time, we performed a statistical analysis between UG and AG. In total, 116 patients were identified, and the treatment schedules of 29 patients were adjusted. The median follow-up was 60.9 months. In the T1 group, the cumulative 5-year local failure rate was 12.0% in the AG and 15.4% in the UG, and in the T2 group, the rate was 40.7% in the AG and 25.3% in the UG. There were no significant differences between the AG and UG. Similarly, no significant differences were observed for overall survival and progression-free survival rates. Our single-institutional retrospective analysis of EGSCC patients suggested that a method of adjusting the radiotherapy schedule to increase fraction size from the beginning or during the course may be effective in maintaining treatment outcomes.

Radiotherapy with or without chemotherapy for locally advanced head and neck cancer in elderly patients: analysis of the Head and Neck Cancer Registry of Japan.

BACKGROUND: Whether concurrent chemotherapy with radiotherapy (CRT) is effective for elderly patients with head and neck cancer is a controversial topic. This study aimed to analyze the effectiveness of CRT vs. radiation therapy (RT) among elderly patients in Japan. METHODS: Data from the Head and Neck Cancer Registry of Japan were extracted and analyzed. Patients with locally advanced squamous cell carcinoma of the oropharynx, hypopharynx, or larynx who received definitive CRT or RT between 2011 and 2014 were included. RESULTS: CRT was administered to 78% of the 1057 patients aged ≥ 70 years and 67% of the 555 patients aged ≥ 75 years. For the patients aged ≥ 75 years, the overall survival (OS) rate was significantly better in the CRT group than in the RT group (P < 0.05), while the progression-free survival (PFS) rate was not significantly different (P > 0.05). The add-on effect of CRT was significantly poor in elderly patients (P < 0.05), and it was not a significant factor in the multivariate analysis for patients aged ≥ 75 years. After propensity score matching, there were no significant differences in the OS and PFS rates between the patients aged ≥ 70 years and those aged ≥ 75 years (all, P > 0.05). CONCLUSION: Although aggressive CRT is administered to elderly patients in Japan, its effectiveness is uncertain. Further prospective randomized trials are needed to verify whether CRT is superior to RT alone for elderly patients.

Predicting the daily gastrointestinal doses of stereotactic body radiation therapy for pancreatic cancer based on the shortest distance between the tumor and the gastrointestinal tract using daily computed tomography images.

Objectives: We aimed to investigate whether daily computed tomography (CT) images could predict the daily gastroduodenal, small intestine, and large intestine doses of stereotactic body radiation therapy (SBRT) for pancreatic cancer based on the shortest distance between the gross tumor volume (GTV) and gastrointestinal (GI) tract. Methods: Twelve patients with pancreatic cancer received SBRT of 40 Gy in five fractions. We recalculated the reference clinical SBRT plan (PLANref) using daily CT images and calculated the shortest distance from the GTV to each GI tract. The maximum dose delivered to 0.5 cc (D0.5cc) was evaluated for each planning at-risk volume of the GI tract. Spearman's correlation test was used to determine the association between the daily change in the shortest distance (Δshortest distance) and the ratio of ΔD0.5cc dose to D0.5cc dose in PLANref (ΔD0.5cc/PLANref) for quantitative analysis. Results: The median shortest distance in PLANref was 0 mm in the gastroduodenum (interquartile range, 0-2.7), 16.7 mm in the small intestine (10.0-23.7), and 16.7 mm in the large intestine (8.3-28.1 mm). The D0.5cc of PLANref in the gastroduodenum was >30 Gy in all patients, with 10 (83.3%) having the highest dose. A significant association was found between the Δshortest distance and ΔD0.5cc/ PLANref in the small or large intestine (p < 0.001) but not in the gastroduodenum (p = 0.404). Conclusions: The gastroduodenum had a higher D0.5cc and predicting the daily dose was difficult. Daily dose calculations of the GI tract are recommended for safe SBRT. Advances in knowledge: This study aimed to predict the daily doses in SBRT for pancreatic cancer from the shortest distance between the GTV and the gastrointestinal tract.Daily changes in the shortest distance can predict the daily dose to the small or large intestines, but not to the gastroduodenum.

Effectiveness of CT-image guidance in proton therapy for liver cancer and the importance of daily dose monitoring for tumors and organs at risk.

BACKGROUND: It is important to have precise image guidance throughout proton therapy in order to take advantage of the therapy's physical selectivity. PURPOSE: We evaluated the effectiveness of computed tomography (CT)-image guidance in proton therapy for patients with hepatocellular carcinoma (HCC) by assessing daily proton dose distributions. The importance of daily CT image-guided registration and daily proton dose monitoring for tumors and organs at risk (OARs) was investigated. METHODS: A retrospective analysis was conducted using 570 sets of daily CT (dCT) images throughout whole treatment fractions for 38 HCC patients who underwent passive scattering proton therapy with either a 66 cobalt gray equivalent (GyE)/10 fractions (n = 19) or 76 GyE/20 fractions (n = 19) protocol. The actual daily delivered dose distributions were estimated by forward calculation using the dCT sets, their corresponding treatment plans, and the recorded daily couch correction information. We then evaluated the daily changes of the dose indices D99% , V30GyE , and Dmax for the tumor volumes, non-tumorous liver, and other OARs, that is, stomach, esophagus, duodenum, colon, respectively. Contours were created for all dCT sets. We validated the efficacy of the dCT-based tumor registrations (hereafter, "tumor registration") by comparing them with the bone registration and diaphragm registration as a simulation of the treatment based on the positioning using the conventional kV X-ray imaging. The dose distributions and the indices of three registrations were obtained by simulation using the same dCT sets. RESULTS: In the 66 GyE/10 fractions, the daily D99% value in both the tumor and diaphragm registrations agreed with the planned value with 3%-6% (SD), and the V30GyE value for the liver agreed within ±3%; the indices in the bone registration showed greater deterioration. Nevertheless, tumor-dose deterioration occurred in all registration methods for two cases due to daily changes of body shape and respiratory condition. In the 76 GyE/20 fractions, in particular for such a treatment that the dose constraints for the OARs have to be cared in the original planning, the daily D99% in the tumor registration was superior to that in the other registration (p < 0.001), indicating the effectiveness of the tumor registration. The dose constraints, set in the plan as the maximum dose for OARs (i.e., duodenum, stomach, colon, and esophagus) were maintained for 16 patients including seven treated with re-planning. For three patients, the daily Dmax increased gradually or changed randomly, resulting in an inter-fractional averaged Dmax higher than the constraints. The dose distribution would have been improved if re-planning had been conducted. The results of these retrospective analyses indicate the importance of daily dose monitoring followed by adaptive re-planning when needed. CONCLUSIONS: The tumor registration in proton treatment for HCC was effective to maintain the daily dose to the tumor and the dose constraints of OARs, particularly in the treatment where the maintenance for the dose constraints needs to be considered throughout the treatment. Nevertheless daily proton dose monitoring with daily CT imaging is important for more reliable and safer treatment.

Study of hepatic toxicity in small liver tumors after photon or proton therapy based on factors predicting the benefits of proton.

OBJECTIVES: In a previous study of hepatic toxicity, the following three factors were identified to predict the benefits of proton beam therapy (PBT) for hepatocellular carcinomas (HCCs) with a maximum diameter of ≤5 cm and Child-pugh grade A (CP-A): number of tumors (1 vs ≥2), the location of tumors (hepatic hilum or others), and the sum of the diameters of lesions. The aim of this study is to analyze the association between these three factors and hepatic toxicity. METHODS: We retrospectively reviewed patients of CP-A treated with PBT or photon stereotactic body radiotherapy (X-ray radiotherapy, XRT) for HCC ≤5 cm. For normal liver dose, the V5, V10, V20 (volumes receiving 5, 10, and 20 Gy at least), and the mean dose was evaluated. The albumin-bilirubin (ALBI) and CP score changes from the baseline were evaluated at 3 and 6 months after treatment. RESULTS: In 89 patients (XRT: 48, PBT: 41), those with two or three (2-3) predictive factors were higher normal liver doses than with zero or one (0-1) factor. In the PBT group, the ALBI score worsened more in patients with 2-3 factors than those with 0-1 factor, at 3 months (median: 0.26 vs 0.02, p = 0.032) and at 6 months (median: 0.35 vs 0.10, p = 0.009). The ALBI score change in the XRT group and CP score change in either modality were not significantly different in the number of predictive factors. CONCLUSION: The predictive factor numbers predicted the ALBI score change in PBT but not in XRT. ADVANCES IN KNOWLEDGE: This study suggest that the number of predictive factors previously identified (0-1 vs 2-3) were significantly associated with dosimetric parameters of the normal liver in both modalities. In the proton group, the number of predictive factors was associated with a worsening ALBI score at 3 and 6 months, but these associations were not found in the photon SBRT group.

Evaluation of short-term gastrointestinal motion and its impact on dosimetric parameters in stereotactic body radiation therapy for pancreatic cancer.

Background: The aim of this study is to quantify the short-term motion of the gastrointestinal tract (GI-tract) and its impact on dosimetric parameters in stereotactic body radiation therapy (SBRT) for pancreatic cancer. Methods: The analyzed patients were eleven pancreatic cancer patients treated with SBRT or proton beam therapy. To ensure a fair analysis, the simulation SBRT plan was generated on the planning CT in all patients with the dose prescription of 40 Gy in 5 fractions. The GI-tract motion (stomach, duodenum, small and large intestine) was evaluated using three CT images scanned at spontaneous expiration. After fiducial-based rigid image registration, the contours in each CT image were generated and transferred to the planning CT, then the organ motion was evaluated. Planning at risk volumes (PRV) of each GI-tract were generated by adding 5 mm margins, and the volume receiving at least 33 Gy (V33) < 0.5 cm3 was evaluated as the dose constraint. Results: The median interval between the first and last CT scans was 736 s (interquartile range, IQR:624-986). To compensate for the GI-tract motion based on the planning CT, the necessary median margin was 8.0 mm (IQR: 8.0-10.0) for the duodenum and 14.0 mm (12.0-16.0) for the small intestine. Compared to the planned V33 with the worst case, the median V33 in the PRV of the duodenum significantly increased from 0.20 cm3 (IQR: 0.02-0.26) to 0.33 cm3 (0.10-0.59) at Wilcoxon signed-rank test (p = 0.031). Conclusion: The short-term motions of the GI-tract lead to high dose differences.

Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients.

PURPOSE: The aim of this study was to develop a normal tissue complication probability model using a machine learning approach (ML-based NTCP) to predict the risk of radiation-induced liver disease in hepatocellular carcinoma (HCC) patients. MATERIALS AND METHODS: The study population included 201 HCC patients treated with radiotherapy. The patients' medical records were retrospectively reviewed to obtain the clinical and radiotherapy data. Toxicity was defined by albumin-bilirubin (ALBI) grade increase. The normal liver dose-volume histogram was reduced to mean liver dose (MLD) based on the fraction size-adjusted equivalent uniform dose (2 Gy/fraction and α/ß = 2). Three types of ML-based classification models were used, a penalized logistic regression (PLR), random forest (RF), and gradient-boosted tree (GBT) model. Model performance was compared using the area under the receiver operating characteristic curve (AUROC). Internal validation was performed by 5-fold cross validation and external validation was done in 44 new patients. RESULTS: Liver toxicity occurred in 87 patients (43.1%). The best individual model was the GBT model using baseline liver function, liver volume, and MLD as inputs and the best overall model was an ensemble of the PLR and GBT models. An AUROC of 0.82 with a standard deviation of 0.06 was achieved for the internal validation. An AUROC of 0.78 with a standard deviation of 0.03 was achieved for the external validation. The behaviors of the best GBT model were also in good agreement with the domain knowledge on NTCP. CONCLUSION: We propose the methodology to develop an ML-based NTCP model to estimate the risk of ALBI grade increase.

A study on predicting cases that would benefit from proton beam therapy in primary liver tumors of less than or equal to 5 cm based on the estimated incidence of hepatic toxicity.

Background: For small primary liver tumors, favorable outcomes have been reported with both of proton beam therapy (PBT) and X-ray therapy (XRT). However, no clear criteria have been proposed in the cases for which and when of PBT or XRT has to be used. The aim of this study is to investigate cases that would benefit from PBT based on the predicted rate of hepatic toxicity. Materials and methods: Eligible patients were those who underwent PBT for primary liver tumors with a maximum diameter of ≤ 5 cm and Child-Pugh grade A (n = 40). To compare the PBT-plan, the treatment plan using volumetric modulated arc therapy was generated as the XRT-plan. The rate of predicted hepatic toxicity was estimated using five normal tissue complication probability (NTCP) models with three different endpoints. The differences in NTCP values (ΔNTCP) were calculated to determine the relative advantage of PBT. Factors predicting benefits of PBT were analyzed by logistic regression analysis. Results: From the dose-volume histogram comparisons, an advantage of PBT was found in sparing of the normal liver receiving low doses. The factors predicting the benefit of PBT differed depending on the selected NTCP model. From the five models, the total tumor diameter (sum of the target tumors), location (hepatic hilum vs other), and number of tumors (1 vs 2) were significant factors. Conclusions: From the radiation-related hepatic toxicity, factors were identified to predict benefits of PBT in primary liver tumors with Child-Pugh grade A, with the maximum tumor diameter of ≤ 5 cm.

Dosimetric advantages of daily adaptive strategy in IMPT for high-risk prostate cancer.

PURPOSE: To evaluate the dosimetric advantages of daily adaptive radiotherapy (DART) in intensity-modulated proton therapy (IMPT) for high-risk prostate cancer by comparing estimated doses of the conventional non-adaptive radiotherapy (NART) that irradiates according to an original treatment plan through the entire treatment and the DART that uses an adaptive treatment plan generated by using daily CT images acquired before each treatment. METHODS: Twenty-three patients with prostate cancer were included. A treatment plan with 63 Gy (relative biological effectiveness (RBE)) in 21 fractions was generated using treatment planning computed tomography (CT) images assuming that all patients had high-risk prostate cancer for which the clinical target volume (CTV) needs to include prostate and the seminal vesicle (SV) in our treatment protocol. Twenty-one adaptive treatment plans for each patient (total 483 data sets) were generated using daily CT images, and dose distributions were calculated. Using a 3 mm set-up uncertainty in the robust optimization, the doses to the CTV, prostate, SV, rectum, and bladder were compared. RESULTS: Estimated accumulated doses of NART and DART in the 23 patients were 60.81 ± 3.47 Gy (RBE) and 63.24 ± 1.04 Gy (RBE) for CTV D99 (p < 0.01), 62.99 ± 1.28 Gy (RBE) and 63.43 ± 1.33 Gy (RBE) for the prostate D99 (p = 0.2529), and 59.07 ± 5.19 Gy (RBE) and 63.17 ± 1.04 Gy (RBE) for SV D99 (p < 0.001). No significant differences were observed between NART and DART in the estimated accumulated dose for the rectum and bladder. CONCLUSION: Compared with the NART, DART was shown to be a useful approach that can maintain the dose coverage to the target without increasing the dose to the organs at risk (OAR) using the 3 mm set-up uncertainty in the robust optimization in patients with high-risk prostate cancer.

Prediction of liver Dmean for proton beam therapy using deep learning and contour-based data augmentation.

The prediction of liver Dmean with 3-dimensional radiation treatment planning (3DRTP) is time consuming in the selection of proton beam therapy (PBT), and deep learning prediction generally requires large and tumor-specific databases. We developed a simple dose prediction tool (SDP) using deep learning and a novel contour-based data augmentation (CDA) approach and assessed its usability. We trained the SDP to predict the liver Dmean immediately. Five and two computed tomography (CT) data sets of actual patients with liver cancer were used for the training and validation. Data augmentation was performed by artificially embedding 199 contours of virtual clinical target volume (CTV) into CT images for each patient. The data sets of the CTVs and OARs are labeled with liver Dmean for six different treatment plans using two-dimensional calculations assuming all tissue densities as 1.0. The test of the validated model was performed using 10 unlabeled CT data sets of actual patients. Contouring only of the liver and CTV was required as input. The mean relative error (MRE), the mean percentage error (MPE) and regression coefficient between the planned and predicted Dmean was 0.1637, 6.6%, and 0.9455, respectively. The mean time required for the inference of liver Dmean of the six different treatment plans for a patient was 4.47±0.13 seconds. We conclude that the SDP is cost-effective and usable for gross estimation of liver Dmean in the clinic although the accuracy should be improved further if we need the accuracy of liver Dmean to be compatible with 3DRTP.

A treatment planning study of urethra-sparing intensity-modulated proton therapy for localized prostate cancer.

BACKGROUND AND PURPOSE: Urethra-sparing radiation therapy for localized prostate cancer can reduce the risk of radiation-induced genitourinary toxicity by intentionally underdosing the periurethral transitional zone. We aimed to compare the clinical impact of a urethra-sparing intensity-modulated proton therapy (US-IMPT) plan with that of conventional clinical plans without urethral dose reduction. MATERIALS AND METHODS: This study included 13 patients who had undergone proton beam therapy. The prescribed dose was 63 GyE in 21 fractions for 99% of the clinical target volume. To compare the clinical impact of the US-IMPT plan with that of the conventional clinical plan, tumor control probability (TCP) and normal tissue complication probability (NTCP) were calculated with a generalized equivalent uniform dose-based Lyman-Kutcher model using dose volume histograms. The endpoints of these model parameters for the rectum, bladder, and urethra were fistula, contraction, and urethral stricture, respectively. RESULTS: The mean NTCP value for the urethra in US-IMPT was significantly lower than that in the conventional clinical plan (0.6% vs. 1.2%, p < 0.05). There were no statistically significant differences between the conventional and US-IMPT plans regarding the mean minimum dose for the urethra with a 3-mm margin, TCP value, and NTCP value for the rectum and bladder. Additionally, the target dose coverage of all plans in the robustness analysis was within the clinically acceptable range. CONCLUSIONS: Compared with the conventional clinically applied plans, US-IMPT plans have potential clinical advantages and may reduce the risk of genitourinary toxicities, while maintaining the same TCP and NTCP in the rectum and bladder.

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

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.

Analysis of acute-phase toxicities of intensity-modulated proton therapy using a model-based approach in pharyngeal cancer patients.

Pharyngeal cancer patients treated with intensity-modulated proton therapy (IMPT) using a model-based approach were retrospectively reviewed, and acute toxicities were analyzed. From June 2016 to March 2019, 15 pharyngeal (7 naso-, 5 oro- and 3 hypo-pharyngeal) cancer patients received IMPT with robust optimization. Simulation plans for IMPT and intensity-modulated X-ray therapy (IMXT) were generated before treatment. We also reviewed 127 pharyngeal cancer patients with IMXT in the same treatment period. In the simulation planning comparison, all of the normal-tissue complication probability values for dysphagia, dysgeusia, tube-feeding dependence and xerostomia were lower for IMPT than for IMXT in the 15 patients. After completing IMPT, 13 patients completed the evaluation, and 12 of these patients had a complete response. The proportions of patients who experienced grade 2 or worse acute toxicities in the IMPT and IMXT cohorts were 21.4 and 56.5% for dysphagia (P < 0.05), 46.7 and 76.3% for dysgeusia (P < 0.05), 73.3 and 62.8% for xerostomia (P = 0.43), 73.3 and 90.6% for mucositis (P = 0.08) and 66.7 and 76.4% for dermatitis (P = 0.42), respectively. Multivariate analysis revealed that IMPT was independently associated with a lower rate of grade 2 or worse dysphagia and dysgeusia. After propensity score matching, 12 pairs of IMPT and IMXT patients were selected. Dysphagia was also statistically lower in IMPT than in IMXT (P < 0.05). IMPT using a model-based approach may have clinical benefits for acute dysphagia.

The normal tissue complication probability model-based approach considering uncertainties for the selective use of radiation modality in primary liver cancer patients.

PURPOSE: To predict the probability of radiation-induced liver toxicity (RILT) and implement the normal tissue complication probability (NTCP) model-based approach considering confidence intervals (CIs) to select patients for new treatment techniques, such as proton beam therapy, based on a certain NTCP reduction (ΔNTCP) threshold for primary liver cancer patients. METHODS AND MATERIALS: Common Toxicity Criteria for Adverse Events (CTCAE) grade ≥2 RILT was scored. The Lyman NTCP models predicting the probability of CTCAE grade ≥2 RILT as a function of the fraction-size adjusted mean liver dose (MLD), using reference fraction size = 2 Gy/fraction and α/ß ratio = 2 Gy, were fitted using the maximum likelihood method. At certain combinations of MLDs, ΔNTCP with a CI was evaluated by the delta method. RESULTS: Of the 239 patients, the incidence of CTCAE grade ≥2 RILT was 55% (46% in the Child-Pugh (CP)-A vs. 81% in the CP-B/C, p < 0.001). Among 180 CP-A patients, 40% who had viral hepatitis infections experienced toxicity vs. 32% in the nonhepatitis subgroup. The MLD was 18 Gy in the toxicity group vs. 16.1 Gy in the nontoxicity group (p = 0.002). The estimated NTCP model parameters specific to the patient subgroups and the ΔNTCP with CI assuming a particular CP classification and viral hepatitis infection status were considerably different which possible changed treatment decision. CONCLUSIONS: Patients with CP-A and viral hepatitis infection or CP-B/C cirrhosis had greater susceptibility to CTCAE grade ≥2 RILT. The estimated NTCP and ΔNTCP for individual patients along with a consideration of uncertainties improve the reliability of the NTCP model-based approach.

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.

Modern radiotherapy technologies such as proton beam therapy (PBT) permit dose escalation to the tumour and minimize unnecessary doses to normal tissues. To achieve appropriate patient selection for PBT, a normal tissue complication probability (NTCP) model can be applied to estimate the risk of treatment-related toxicity relative to X-ray therapy (XRT). A methodology for estimating the difference in NTCP (∆NTCP), including its uncertainty as a function of dose to normal tissue, is described in this study using the Delta method, a statistical method for evaluating the variance of functions, considering the variance-covariance matrix. We used a virtual individual patient dataset of radiation-induced liver disease (RILD) in liver tumour patients who were treated with XRT as a study model. As an alternative option for individual patient data, dose-bin data, which consists of the number of patients who developed toxicity in each dose level/bin and the total number of patients in that dose level/bin, are useful for multi-institutional data sharing. It provides comparable accuracy with individual patient data when using the Delta method. With reliable NTCP models, the ∆NTCP with uncertainty might potentially guide the use of PBT; however, clinical validation and a cost-effectiveness study are needed to determine the appropriate ∆NTCP threshold.

Present developments in reaching an international consensus for a model-based approach to particle beam therapy.

Particle beam therapy (PBT), including proton and carbon ion therapy, is an emerging innovative treatment for cancer patients. Due to the high cost of and limited access to treatment, meticulous selection of patients who would benefit most from PBT, when compared with standard X-ray therapy (XRT), is necessary. Due to the cost and labor involved in randomized controlled trials, the model-based approach (MBA) is used as an alternative means of establishing scientific evidence in medicine, and it can be improved continuously. Good databases and reasonable models are crucial for the reliability of this approach. The tumor control probability and normal tissue complication probability models are good illustrations of the advantages of PBT, but pre-existing NTCP models have been derived from historical patient treatments from the XRT era. This highlights the necessity of prospectively analyzing specific treatment-related toxicities in order to develop PBT-compatible models. An international consensus has been reached at the Global Institution for Collaborative Research and Education (GI-CoRE) joint symposium, concluding that a systematically developed model is required for model accuracy and performance. Six important steps that need to be observed in these considerations include patient selection, treatment planning, beam delivery, dose verification, response assessment, and data analysis. Advanced technologies in radiotherapy and computer science can be integrated to improve the efficacy of a treatment. Model validation and appropriately defined thresholds in a cost-effectiveness centered manner, together with quality assurance in the treatment planning, have to be achieved prior to clinical implementation.

Selection of external beam radiotherapy approaches for precise and accurate cancer treatment.

Physically precise external-beam radiotherapy (EBRT) technologies may not translate to the best outcome in individual patients. On the other hand, clinical considerations alone are often insufficient to guide the selection of a specific EBRT approach in patients. We examine the ways in which to compare different EBRT approaches based on physical, biological and clinical considerations, and how they can be enhanced with the addition of biophysical models and machine-learning strategies. The process of selecting an EBRT modality is expected to improve in tandem with knowledge-based treatment planning.