OBJECTIVE: Conventional normal tissue complication probability (NTCP) models for head and neck cancer (HNC) patients are typically based on single-value variables, which for radiation-induced xerostomia are baseline xerostomia and mean salivary gland doses. This study aims to improve the prediction of late xerostomia by utilizing 3D information from radiation dose distributions, CT imaging, organ-at-risk segmentations, and clinical variables with deep learning (DL).
METHODS: An international cohort of 1208 HNC patients from two institutes was used to train and twice validate DL models (DCNN, EfficientNet-v2, and ResNet) with 3D dose distribution, CT scan, organ-at-risk segmentations, baseline xerostomia score, sex, and age as input. The NTCP endpoint was moderate-to-severe xerostomia 12 months post-radiotherapy. The DL models\' prediction performance was compared to a reference model: a recently published xerostomia NTCP model that used baseline xerostomia score and mean salivary gland doses as input. Attention maps were created to visualize the focus regions of the DL predictions. Transfer learning was conducted to improve the DL model performance on the external validation set.
RESULTS: All DL-based NTCP models showed better performance (AUCtest=0.78 - 0.79) than the reference NTCP model (AUCtest=0.74) in the independent test. Attention maps showed that the DL model focused on the major salivary glands, particularly the stem cell-rich region of the parotid glands. DL models obtained lower external validation performance (AUCexternal=0.63) than the reference model (AUCexternal=0.66). After transfer learning on a small external subset, the DL model (AUCtl, external=0.66) performed better than the reference model (AUCtl, external=0.64).
CONCLUSIONS: DL-based NTCP models performed better than the reference model when validated in data from the same institute. Improved performance in the external dataset was achieved with transfer learning, demonstrating the need for multicenter training data to realize generalizable DL-based NTCP models.

Objective.This study simulated the potential of gold nanoparticles (GNPs) to improve the effectiveness of radiation therapy in pancreatic cancer cases. The purpose of this study was to assess the impact of GNPs on tumor control probability (TCP) and normal tissue complication probability (NTCP) in pancreatic cancer cases undergoing radiation therapy. The work aimed to compare treatment plans generated with a novel 2.5 MV beam using GNPs to conventional 6 MV plans and evaluate the dose-volume histogram (DVH), TCP, and NTCP.Approach.Treatment planning for five pancreatic computed tomography (CT) images was performed using the open-source MATLAB-based treatment planning program matRad. MATLAB codes were developed to calculate the relative biological effectiveness (RBE) of GNPs and apply the corresponding dose and RBE values to each voxel. TCP and NTCP were calculated based on the applied RBE values.Main results.Adding GNPs to the 2.5 MV treatment plan resulted in a significant increase in TCP, from around 59% to 93.5%, indicating that the inclusion of GNPs improved the effectiveness of the radiation treatment. The range in NTCP without GNPs was relatively larger compared to that with GNPs.Significance.The results indicated that the addition of GNPs to a 2.5 MV plan can increase TCP while maintaining a relatively low NTCP value (<1%). The use of GNPs may also reduce NTCP values by decreasing the dose to normal tissues while maintaining the same prescribed dose to the tumor. Hence, the addition of GNPs can improve the balance between TCP and NTCP.

OBJECTIVE: Radiation-induced alopecia (RIA) is one of the most frequent and upsetting cosmetic side effects after radiotherapy (RT) for brain cancer. We report the incidence of RIA in a cohort of brain tumours patients treated with Proton Therapy (PT) and externally validate published NTCP models of grade 2 (G2) RIA for their implementation in clinical practice.
METHODS: Data for patients treated for brain tumours with scanning beam PT between 2018 and 2022 were extracted. Acute, late and permanent RIA events were evaluated according to CTCAE 5.0. Lyman-Kutcher-Burman (LKB) and multivariable logistic regression (MLR) published models were computed from the relative dose-surface histogram of the scalp. External validity of models was assessed in terms of discrimination and calibration.
RESULTS: In the 264 patients analysed, rates of any grade acute (≤90 days after PT completion), late (>90 days) and permanent RIA (persisting for> 12 months) were 61.8 %, 24.7 % and 14.4 %, respectively. In our independent cohort, LKB- and MLR-NTCP showed a good discrimination for G2 RIA (0.71≤ROC-AUC≤0.83) while model calibration was unsatisfactory possibly due to a different outcome evaluation between training and validation cohorts, as well as differences in clinical and treatment related variables between the two groups.
CONCLUSIONS: Despite the reasonable sensitivity and specificity of the NTCP models for RIA in the validation cohort, our study emphasizes the significance of differences between the cohorts utilized for model development and validation. Specifically, variations in the reporting of clinical outcomes inevitably jeopardize the validation of NTCP models. A standardize and objective RIA scoring system is essential.

UNASSIGNED: Difficulties remain in dose optimization and evaluation of cervical cancer radiotherapy that combines external beam radiotherapy (EBRT) and brachytherapy (BT). This study estimates and improves the accumulated dose distribution of EBRT and BT with deep learning-based dose prediction.
UNASSIGNED: A total of 30 patients treated with combined cervical cancer radiotherapy were enrolled in this study. The dose distributions of EBRT and BT plans were accumulated using commercial deformable image registration. A ResNet-101-based deep learning model was trained to predict pixel-wise dose distributions. To test the role of the predicted accumulated dose in clinic, each EBRT plan was designed using conventional method and then redesigned referencing the predicted accumulated dose distribution. Bladder and rectum dosimetric parameters and normal tissue complication probability (NTCP) values were calculated and compared between the conventional and redesigned accumulated doses.
UNASSIGNED: The redesigned accumulated doses showed a decrease in mean values of V50, V60, and D2cc for the bladder (-3.02%, -1.71%, and -1.19 Gy, respectively) and rectum (-4.82%, -1.97%, and -4.13 Gy, respectively). The mean NTCP values for the bladder and rectum were also decreased by 0.02‰ and 0.98%, respectively. All values had statistically significant differences (p < 0.01), except for the bladder D2cc (p = 0.112).
UNASSIGNED: This study realized accumulated dose prediction for combined cervical cancer radiotherapy without knowing the BT dose. The predicted dose served as a reference for EBRT treatment planning, leading to a superior accumulated dose distribution and lower NTCP values.

Membrane transporters interact not only with endogenous substrates but are also engaged in the transport of xenobiotics, including drugs. While the coordinated function of uptake (solute carrier family-SLC and SLCO) and efflux (ATP-binding cassette family-ABC, multidrug and toxic compound extrusion family-MATE) transporter system allows vectorial drug transport, efflux carriers alone achieve barrier functions. The modulation of transport functions was proved to be effective in the treatment strategies of various pathological states. Sodium-glucose cotransporter-2 (SGLT2) inhibitors are the drugs most widely applied in clinical practice, especially in the treatment of diabetes mellitus and heart failure. Sodium taurocholate co-transporting polypeptide (NTCP) serves as virus particles (HBV/HDV) carrier, and inhibition of its function is applied in the treatment of hepatitis B and hepatitis D by myrcludex B. Inherited cholestatic diseases, such as Alagille syndrome (ALGS) and progressive familial intrahepatic cholestasis (PFIC) can be treated by odevixibat and maralixibat, which inhibit activity of apical sodium-dependent bile salt transporter (ASBT). Probenecid can be considered to increase uric acid excretion in the urine mainly via the inhibition of urate transporter 1 (URAT1), and due to pharmacokinetic interactions involving organic anion transporters 1 and 3 (OAT1 and OAT3), it modifies renal excretion of penicillins or ciprofloxacin as well as nephrotoxicity of cidofovir. This review discusses clinically approved drugs that affect membrane/drug transporter function.

Helium ion therapy (HRT) is a promising modality for the treatment of pediatric tumors and those located close to critical structures due to the favorable biophysical properties of helium ions. This in silico study aimed to explore the potential benefits of HRT in advanced juvenile nasopharyngeal angiofibroma (JNA) compared to proton therapy (PRT). We assessed 11 consecutive patients previously treated with PRT for JNA in a definitive or postoperative setting with a relative biological effectiveness (RBE) weighted dose of 45 Gy (RBE) in 25 fractions at the Heidelberg Ion-Beam Therapy Center. HRT plans were designed retrospectively for dosimetric comparisons and risk assessments of radiation-induced complications. HRT led to enhanced target coverage in all patients, along with sparing of critical organs at risk, including a reduction in the brain integral dose by approximately 27%. In terms of estimated risks of radiation-induced complications, HRT led to a reduction in ocular toxicity, cataract development, xerostomia, tinnitus, alopecia and delayed recall. Similarly, HRT led to reduced estimated risks of radiation-induced secondary neoplasms, with a mean excess absolute risk reduction of approximately 30% for secondary CNS malignancies. HRT is a promising modality for advanced JNA, with the potential for enhanced sparing of healthy tissue and thus reduced radiation-induced acute and long-term complications.

OBJECTIVE: To compare the dosimetric advantages and disadvantages between hybrid intensity-modulated radiation therapy (h-IMRT) and the volumetric modulated arc therapy (VMAT) technique in hypofractionated whole-breast irradiation (HF-WBI) for early-stage breast cancer (BC).
METHODS: The dose distribution of h-IMRT and VMAT plans was compared in 20 breast cancer patients. This comparison included evaluation of dosimetric parameters using dose volume histograms (DVHs) for the planning target volume (PTV) and organs-at-risk (OARs). Additionally, the study examined the normal tissue complication probability (NTCP), the second cancer complication probability (SCCP) and the tumor control probability (TCP) based on different models.
RESULTS: Significant differences were detected between the two plans, in terms of Machine units (MUs), the control points, 95 % volume (V95 %), dose homogeneity index (DHI) and conformity index (CI). The endpoint of grade II radiation pneumonitis and cardiac death due to ischemic heart disease were assessed. In h-IMRT plan, the NTCP values were marginally lower for radiation pneumonitis and slightly higher for cardiac death compared to VMAT plan, as determined by the Lyman-Kutcher-Burman model. The Schneider model was employed to predict the SCCP for both the bilateral lungs and contralateral breast, the results demonstrate that the h-IMRT plan outperforms the VMAT plan, with statistical significance. Additionally, the LQ-Poisson model was employed to forecast the TCP of the PTV, showing that the h-IMRT plan outperformed the VMAT plan (P > 0.05).
CONCLUSIONS: The h-IMRT technique, offering superior dose coverage and better therapeutic efficacy with fewer side effects as calculated by models, is more suitable for HF-WBI compared to the VMAT technique.

BACKGROUND: Limited literature exists on the feasibility and effectiveness of integrating stereotactic ablative radiotherapy (SABR) techniques with hyperfractionated regimens for patients with lung cancer. This study aims to assess whether the SABR technique with hyperfractionation can potentially reduce lung toxicity.
METHODS: We utilized the linear-quadratic model to find the optimal fraction to maximize the tumor biological equivalent dose (BED) to normal-tissue BED ratio. Validation was performed by comparing the SABR plans with 50 Gy/5 fractions and hyperfractionationed plans with 88.8 Gy/74 fractions with the same tumor BED and planning criteria for 10 patients with early-stage lung cancer. Mean lung BED, Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP), critical volume (CV) criteria (volume below BED of 22.92 and 25.65 Gy, and mean BED for lowest 1000 and 1500 cc) and the percentage of the lung receiving 20Gy or more (V20) were compared using the Wilcoxon signed-rank test.
RESULTS: The transition point occurs when the tumor-to-normal tissue ratio (TNR) of the physical dose equals the TNR of α/β in the BED dose-volume histogram of the lung. Compared with the hypofractionated regimen, the hyperfractionated regimen is superior in the dose range above but inferior below the transition point. The hyperfractionated regimen showed a lower mean lung BED (6.40 Gy vs. 7.73 Gy) and NTCP (3.50% vs. 4.21%), with inferior results concerning CV criteria and higher V20 (7.37% vs. 7.03%) in comparison with the hypofractionated regimen (p < 0.01 for all).
CONCLUSIONS: The hyperfractionated regimen has an advantage in the high-dose region of the lung but a disadvantage in the low-dose region. Further research is needed to determine the superiority between hypo- and hyperfractionation.

OBJECTIVE: To assess the robustness and to define the dosimetric and NTCP advantages of pencil-beam-scanning proton therapy (PBSPT) compared with VMAT for unresectable Stage III non-small lung cancer (NSCLC) in the immunotherapy era.
METHODS: 10 patients were re-planned with VMAT and PBSPT using: 1) ITV-based robust optimization with 0.5 cm setup uncertainties and (for PBSPT) 3.5 % range uncertainties on free-breathing CT 2) CTV-based RO including all 4DCTs anatomies. Target coverage (TC), organs at risk dose and TC robustness (TCR), set at V95%, were compared. The NTCP risk for radiation pneumonitis (RP), 24-month mortality (24MM), G2 + acute esophageal toxicity (ET), the dose to the immune system (EDIC) and the left anterior descending (LAD) coronary artery V15 < 10 % were registered. Wilcoxon test was used.
RESULTS: Both PBSPT methods improved TC and TCR (p < 0.01). The mean lung dose and lung V20 were lower with PBSPT (p < 0.01). Median mean heart dose reduction with PBSPT was 8 Gy (p < 0.001). PT lowered median LAD V15 (p = 0.004). ΔNTCP > 5 % with PBSPT was observed for two patients for RP and for five patients for 24 MM. ΔNTCP for ≥ G2 ET was not in favor of PBSPT for all patients. PBSPT halved median EDIC (4.9/5.1 Gy for ITV/CTV-based VMAT vs 2.3 Gy for both ITV/CTV-based PBSPT, p < 0.01).
CONCLUSIONS: PBSPT is a robust approach with significant dosimetric and NTCP advantages over VMAT; the EDIC reduction could allow for a better integration with immunotherapy. A clinical benefit for a subset of NSCLC patients is expected.

OBJECTIVE: The current research compared radiobiological and dosimetric results for simultaneous integrated boost (SIB) plans employing RapidArc and IMRT planning procedures in oropharyngeal cancer from head-and-neck cancer (HNC) patients.
METHODS: The indigenously developed Python-based software was used in this study for generation and analysis. Twelve patients with forty-eight total plans with SIB were planned using Rapid arc (2 and 3 arcs) and IMRT (7 and 9 fields) and compared with radiobiological models Lyman, Kutcher, Burman (LKB) and EUD (Equivalent Uniform Dose) along with physical index such as homogeneity index(HI), conformity index(CI) of target volumes.
RESULTS: These models\' inputs are the dose-volume histograms (DVHs) calculated by the treatment planning system (TPS). The values obtained vary from one model to the other for the same technique and patient. The maximum dose to the brainstem and spinal cord and the mean dose to the parotids were analysed both dosimetrically and radiobiologically, such as the LKB model effective volume, equivalent uniform dose, EUD-based normal tissue complication probability, and normal tissue integral dose. The mean and max dose to target volume with conformity, homogeneity index, tumor control probability compared with treatment times, and monitor units.
CONCLUSIONS: Rapid arc (3 arcs) resulted in significantly better OAR sparing, dose homogeneity, and conformity. The findings indicate that the rapid arc plan has improved dose distribution in the target volume compared with IMRT, but the tumor control probability obtained for the two planning methods, Rapid arc (3 arcs) and IMRT (7 fields), are similar. The treatment time and monitor units for the Rapid arc (3 arcs) were superior to other planning methods and considered to be standard in head & neck radiotherapy.