Temporal lobe injury patterns following intensity modulated radiotherapy in a large cohort of nasopharyngeal carcinoma patients

Dosimetric parameters predict radiation-induced temporal lobe necrosis in nasopharyngeal carcinoma patients: A systematic review and meta-analysis

This systematic review examines the role of dosimetric parameters in predicting temporal lobe necrosis (TLN) risk in nasopharyngeal carcinoma (NPC) patients treated with three-dimensional conformal RT (3D-CRT), intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). TLN is a serious late complication that can adversely affect the quality of life of NPC patients. Understanding the relationship between dosimetric parameters and TLN can guide treatment planning and minimize radiation-related complications. A comprehensive search identified relevant studies published up to July 2023. Studies reporting on dosimetric parameters and TLN in NPC patients undergoing 3D-CRT, IMRT, and VMAT were included. TLN incidence, follow-up duration, and correlation with dosimetric parameters of the temporal lobe were analyzed. The review included 30 studies with median follow-up durations ranging from 28 to 110 months. The crude incidence of TLN varied from 2.3 % to 47.3 % and the average crude incidence of TLN is approximately 14 %. Dmax and D1cc emerged as potential predictors of TLN in 3D-CRT and IMRT-treated NPC patients. Threshold values of >72 Gy for Dmax and >62 Gy for D1cc were associated with increased TLN risk. However, other factors should also be considered, including host characteristics, tumor-specific features and therapeutic factors. In conclusion, this systematic review highlights the significance of dosimetric parameters, particularly Dmax and D1cc, in predicting TLN risk in NPC patients undergoing 3D-CRT, IMRT, and VMAT. The findings provide valuable insights that can help in developing optimal treatment planning strategies and contribute to the development of clinical guidelines in this field.

Neurological complications of modern radiotherapy for head and neck cancer

Radiotherapy is one of the mainstay treatment modalities for the management of non-metastatic head and neck cancer (HNC). Notable improvements in treatment outcomes have been observed in the recent decades. Modern radiotherapy techniques, such as intensity-modulated radiotherapy and charged particle therapy, have significantly improved tumor target conformity and enabled better preservation of normal structures. However, because of the intricate anatomy of the head and neck region, multiple critical neurological structures such as the brain, brainstem, spinal cord, cranial nerves, nerve plexuses, autonomic pathways, brain vasculature, and neurosensory organs, are variably irradiated during treatment, particularly when tumor targets are in close proximity. Consequently, a diverse spectrum of late neurological sequelae may manifest in HNC survivors. These neurological complications commonly result in irreversible symptoms, impair patients' quality of life, and contribute to a substantial proportion of non-cancer deaths. Although the relationship between radiation dose and toxicity has not been fully elucidated for all complications, appropriate application of dosimetric constraints during radiotherapy planning may reduce their incidence. Vigilant surveillance during the course of survivorship also enables early detection and intervention. This article endeavors to provide a comprehensive review of the various neurological complications of modern radiotherapy for HNC, summarize the current incidence data, discuss methods to minimize their risks during radiotherapy planning, and highlight potential strategies for managing these debilitating toxicities.

Evolution of radiation-induced temporal lobe injury after intensity-modulated radiation therapy in nasopharyngeal carcinoma: a large cohort retrospective study

BACKGROUND

Previous studies have demonstrated conflicting findings regarding the initial MRI patterns of radiotherapy-induced temporal lobe injury (RTLI) and the evolution of different RTLI patterns. The aim of this study was to evaluate the initial MRI pattern and evolution of RTLI in patients with nasopharyngeal carcinoma (NPC) by means of a large cohort study.

METHODS

Data of patients with RTLI were retrospectively collected from two hospitals between January 2011 and December 2021. The injured lobes were categorized into three patterns based on initial MRI patterns: isolated white matter lesions (WMLs), isolated contrast-enhanced lesions (CELs), and combined WMLs and CELs. The latency period, MRI appearances, and temporal changes in WMLs and CELs were evaluated.

RESULTS

A total of 913 RTLI patients with 1092 injured lobes were included in this study. The numbers of isolated WMLs, isolated CELs, and combined WMLs and CELs identified at the first MRI detection were 7 (0.6%), 172 (15.8%), and 913 (83.6%), respectively. The evolution of bilateral RTLI was different in the same patient, and that of unilateral RTLI combined with WMLs and CELs also may occur asynchronously. The time intervals from the initial MRI detection of isolated WMLs, isolated CELs, combined WMLs and CELs to the last negative MRI scan were 8.6, 8.9 and 11.0 months, respectively. A significant difference was observed in the time intervals between the three patterns (H = 14.287, P = 0.001). And the time interval was identified as an independent factor influencing the initial MRI pattern of RTLI after Poisson regression (P = 0.002).

CONCLUSION

Both WMLs and CELs could be the initial and only MRI abnormalities in patients with RTLI. This study is of great significance in accurately diagnosing RTLI early and providing timely treatment options. Additionally, it provides clinical evidence for guidelines on NPC, emphasizing the importance of regular follow-up of NPC patients.

Risk of temporal lobe necrosis between proton beam and volumetric modulated arc therapies in patients with different head and neck cancers

BACKGROUND

To investigate the frequency of temporal lobe necrosis (TLN) soon after radiotherapy (RT) and identify differences among patients with various types of head and neck cancer (HNC) and between different RT methods.

METHODS

We retrospectively reviewed 483 patients with HNC who had completed RT in our hospital after January, 2015. These patients were followed-up at the radio-oncology department and received contrast-enhanced magnetic resonance imaging (MRI) or computed tomography (CT) to identify metastases or recurrence of cancer at regular intervals. Meanwhile, the occurrence of TLN, graded according to the Common Terminology Criteria for Adverse Events V5.0, was recorded. We categorized the patients into nasopharyngeal carcinoma (NPC) and non-NPC groups and compared the cumulative occurrence of TLN between the groups using Kaplan-Meier and Cox regression analyses. We further compared the cumulative occurrence of TLN between proton beam therapy (PBT) and volumetric modulated arc therapy (VMAT) in patients with any HNC, NPC, and non-NPC HNC.

RESULTS

Compared with the non-NPC group, the NPC group had a higher frequency of TLN (5.6% vs. 0.4%,  p < 0.01) and were more commonly associated with TLN in the Kaplan-Meier analysis (p < 0.01) and the Cox regression model after covariates were adjusted for (adjusted hazard ratio: 13.35, 95% confidence interval: 1.37-130.61) during the follow-up period. Furthermore, the frequency of TLN was similar between patients receiving PBT and those receiving VMAT (PBT vs. VMAT: 4.7% vs. 6.3%, p = 0.76). Kaplan-Meier analysis revealed that the accumulated risks of TLN were similar between PBT and VMAT in patients with any HNC (p = 0.44), NPC (p = 0.84), and non-NPC HNC (p = 0.70).

CONCLUSION

Our study demonstrated that patients with NPC are susceptible to TLN during the early period after RT. In addition, PBT may be associated with an equivalent risk of TLN when compared with VMAT in patients with NPC or other HNCs.

Dosiomics Risk Model for Predicting Radiation Induced Temporal Lobe Injury and Guiding Individual Intensity-Modulated Radiation Therapy

PURPOSE

We aimed to assess the value of dose distribution-based dosiomics and planning computed tomography-based radiomics to predict radiation-induced temporal lobe injury (TLI) and guide individualized intensity modulated radiation therapy.

METHODS AND MATERIALS

A total of 5599 nasopharyngeal carcinoma patients were enrolled, including 2503, 1072, 988, and 1036 patients in the training, validation, prospective test, and external test cohorts, respectively. The concordance index (C-index) was used to compare the performance of the radiomics and dosiomics models with that of the quantitative analyses of normal tissue effects in the clinic and Wen's models. The predicted TLI-free survival rates of redesigned simulated plans with the same dose-volume histogram but different dose distributions for same patient in a cohort of 30 randomly selected patients were compared by the Wilcoxon matched-pairs signed-rank test.

RESULTS

The radiomics and dosiomics signatures were constructed based on 30 selected computed tomography features and 10 selected dose distribution features, respectively, which were important predictors of TLI-free survival (all P <.001). However, the radiomics signature had a low C-index. The dosiomics risk model combining the dosiomics signature, D_1cc, and age had favorable performance, with C-index values of 0.776, 0.811, 0.805, and 0.794 in the training, validation, prospective test, and external test cohorts, respectively, which were better than those of the quantitative analyses of normal tissue effects in the clinic model and Wen's model (all P <.001). The dosiomics risk model can further distinguish patients in a same risk category divided by other models (all P <.05). Conversely, the other models were unable to separate populations classified by the dosiomics risk model (all P > .05). Two simulated plans with the same dose-volume histogram but different dose distributions had different TLI-free survival rates predicted by dosiomics risk model (all P ≤ .002).

CONCLUSIONS

The dosiomics risk model was superior to traditional models in predicting the risk of TLI. This is a promising approach to precisely predict radiation-induced toxicities and guide individualized intensity modulated radiation therapy.

Deep learning-based precise prediction and early detection of radiation-induced temporal lobe injury for nasopharyngeal carcinoma

Background

Radiotherapy is the mainstay of treatment for nasopharyngeal carcinoma. Radiation-induced temporal lobe injury (TLI) can regress or resolve in the early phase, but it is irreversible at a later stage. However, no study has proposed a risk-based follow-up schedule for its early detection. Planning evaluation is difficult when dose-volume histogram (DVH) parameters are similar and optimization is terminated.

Methods

This multicenter retrospective study included 6065 patients between 2014 and 2018. A 3D ResNet-based deep learning model was developed in training and validation cohorts and independently tested using concordance index in internal and external test cohorts. Accordingly, the patients were stratified into risk groups, and the model-predicted risks were used to develop risk-based follow-up schedules. The schedule was compared with the Radiation Therapy Oncology Group (RTOG) recommendation (every 3 months during the first 2 years and every 6 months in 3-5 years). Additionally, the model was used to evaluate plans with similar DVH parameters.

Findings

Our model achieved concordance indexes of 0.831, 0.818, and 0.804, respectively, which outperformed conventional prediction models (all P < 0.001). The temporal lobes in all the cohorts were stratified into three groups with discrepant TLI-free survival. Personalized follow-up schedules developed for each risk group could detect TLI 1.9 months earlier than the RTOG recommendation. According to a higher median predicted 3-year TLI-free survival (99.25% vs. 99.15%, P < 0.001), the model identified a better plan than previous models.

Interpretation

The deep learning model predicted TLI more precisely. The model-determined risk-based follow-up schedule detected the TLI earlier. The planning evaluation was refined because the model identified a better plan with a lower risk of TLI.

Funding

The Sun Yat-sen University Clinical Research 5010 Program (2015020), Guangdong Basic and Applied Basic Research Foundation (2022A1515110356), Medical Scientific Research Foundation of Guangdong Province (A2022367), and Guangzhou Science and Technology Program (2023A04J1788).

NTCP modelling for high-grade temporal radionecrosis in a large cohort of patients receiving pencil beam scanning proton therapy for skull base and head and neck tumors

PURPOSE/OBJECTIVES

To develop a normal tissue complication probability (NTCP) model including clinical and dosimetric parameters for high-grade temporal lobe radionecroses (TRN) after pencil beam scanning (PBS) proton therapy (PT).

MATERIALS/METHODS

Data of 299 patients with skull base and Head and Neck tumors treated with PBS PT with a total dose of ≥60 Gy_RBE from 05/2004-11/2018 were included. Patients with a ≥ grade (G) 2 TRN (CTCAE v5.0 criteria) were considered as having a high-grade TRN. Nine clinical and 27 dosimetric parameters were considered for structure-wise modelling. After elimination of strongly cross-correlated variables, logistic regression models were generated using penalized LASSO regression. Bootstrapping was performed to assess parameter selection robustness. Model performance was evaluated via cross-correlation by assessing the area under the curve of receiver operating characteristic curves (AUC-ROC) and calibration with a Hosmer-Lemeshow test statistic.

RESULTS

After a median radiological follow-up of 51.5 months (range, 4-190), 27 (9%) patients developed a ≥ G2 TRN. Eleven patients had bitemporal necrosis, resulting in 38 events in 598 temporal lobes for structure-wise analysis. During Bootstrapping analysis, the highest selection frequency was found for prescription dose (PD), followed by Age, V_40Gy[%], Hypertension (HBP) and D_1cc[Gy]. During cross validation Age*PD* D_1cc[Gy]*HBP was superior in all described test statistics. Full cohort structure wise and patient wise models were built with a maximum AUC-ROC of 0.79 (structure-wise) and 0.76 (patient-wise).

CONCLUSION

While developing a logistic regression NTCP model to predict ≥ G2 TRN, the best fit was found for the model containing Age, PD, D_1cc[Gy] and HBP as risk factors. External validation will be the next step to improve generalizability and potential introduction into clinical routine.

Treatment of Radiation-Induced Brain Necrosis

Radiation-induced brain necrosis (RBN) is a serious complication of intracranial as well as skull base tumors after radiotherapy. In the past, due to the lack of effective treatment, radiation brain necrosis was considered to be progressive and irreversible. With better understanding in histopathology and neuroimaging, the occurrence and development of RBN have been gradually clarified, and new treatment methods are constantly emerging. In recent years, some scholars have tried to treat RBN with bevacizumab, nerve growth factor, and gangliosides and have achieved similar results. Some cases of brain necrosis can be repairable and reversible. We aimed to summarize the incidence, pathogenesis, and treatment of RBN.

Assessing the robustness of artificial intelligence powered planning tools in radiotherapy clinical settings-a phantom simulation approach

Background

Artificial intelligence (AI) based radiotherapy treatment planning tools have gained interest in automating the treatment planning process. It is essential to understand their overall robustness in various clinical scenarios. This is an existing gap between many AI based tools and their actual clinical deployment. This study works to fill the gap for AI based treatment planning by investigating a clinical robustness assessment (CRA) tool for the AI based planning methods using a phantom simulation approach.

Methods

A cylindrical phantom was created in the treatment planning system (TPS) with the axial dimension of 30 cm by 18 cm. Key structures involved in pancreas stereotactic body radiation therapy (SBRT) including PTV25, PTV33, C-Loop, stomach, bowel and liver were created within the phantom. Several simulation scenarios were created to mimic multiple scenarios of anatomical changes, including displacement, expansion, rotation and combination of three. The goal of treatment planning was to deliver 25 Gy to PTV25 and 33 Gy to PTV33 in 5 fractions in simultaneous integral boost (SIB) manner while limiting luminal organ-at-risk (OAR) max dose to be under 29 Gy. A previously developed deep learning based AI treatment planning tool for pancreas SBRT was identified as the validation object. For each scenario, the anatomy information was fed into the AI tool and the final fluence map associated to the plan was generated, which was subsequently sent to TPS for leaf sequencing and dose calculation. The final auto plan's quality was analyzed against the treatment planning constraint. The final plans' quality was further analyzed to evaluate potential correlation with anatomical changes using the Manhattan plot.

Results

A total of 32 scenarios were simulated in this study. For all scenarios, the mean PTV25 V25Gy of the AI based auto plans was 96.7% while mean PTV33 V33Gy was 82.2%. Large variation (16.3%) in PTV33 V33Gy was observed due to anatomical variations, a.k.a. proximity of luminal structure to PTV33. Mean max dose was 28.55, 27.68 and 24.63 Gy for C-Loop, bowel and stomach, respectively. Using D_0.03cc as max dose surrogate, the value was 28.03, 27.12 and 23.84 Gy for C-Loop, bowel and stomach, respectively. Max dose constraint of 29 Gy was achieved for 81.3% cases for C-Loop and stomach, and 78.1% for bowel. Using D_0.03cc as max dose surrogate, the passing rate was 90.6% for C-Loop, and 81.3% for bowel and stomach. Manhattan plot revealed high correlation between the OAR over dose and the minimal distance between the PTV33 and OAR.

Conclusions

The results showed promising robustness of the pancreas SBRT AI tool, providing important evidence of its readiness for clinical implementation. The established workflow could guide the process of assuring clinical readiness of future AI based treatment planning tools.

Per-voxel constraints to minimize hot spots in linear energy transfer-guided robust optimization for base of skull head and neck cancer patients in IMPT

PURPOSE

Due to the employment of quadratic programming using soft constraints to implement dose volume constraints and the "trial-and-error" procedure needed to achieve a clinically acceptable plan, conventional dose volume constraints (upper limit) are not adequately effective in controlling small and isolated hot spots in the dose/linear energy transfer (LET) distribution. Such hot spots can lead to adverse events. In order to mitigate the risk of brain necrosis, one of the most clinically significant adverse events in patients receiving intensity-modulated proton therapy (IMPT) for base of skull (BOS) cancer, we propose per-voxel constraints to minimize hot spots in LET-guided robust optimization.

METHODS AND MATERIALS

Ten BOS cancer patients treated with IMPT were carefully selected by meeting one of the following conditions: (1) diagnosis of brain necrosis during follow-up; and (2) considered high risk for brain necrosis by not meeting dose constraints to the brain. An optimizing structure (BrainOPT) and an evaluating structure (BrainROI) that both contained the aforementioned hot dose regions in the brain were generated for optimization and evaluation, respectively. Two plans were generated for every patient: one using conventional dose-only robust optimization, the other using LET-guided robust optimization. The impact of LET was integrated into the optimization via a term of extra biological dose (xBD). A novel optimization tool of per-voxel constraints to control small and isolated hot spots in either the dose, LET, or combined (dose/LET) distribution was developed and used to minimize dose/LET hot spots of the selected structures. Indices from dose-volume histogram (DVH) and xBD dose-volume histogram (xBDVH) were used in the plan evaluation. A newly developed tool of the dose-LET-volume histogram (DLVH) was also adopted to illustrate the underlying mechanism. Wilcoxon signed-rank test was used for statistical comparison of the DVH and xBDVH indices between the conventional dose-only and the LET-guided robustly optimized plans.

RESULTS

Per-voxel constraints effectively and efficiently minimized dose hot spots in both dose-only and LET-guided robust optimization and LET hot spots in LET-guided robust optimization. Compared to the conventional dose-only robust optimization, the LET-guided robust optimization could generate plans with statistically lower xBD hot spots in BrainROI (VxBD,50 Gy[RBE], p = 0.009; VxBD,60 Gy[RBE], p = 0.025; xBD1cc, p = 0.017; xBD2cc, p = 0.022) with comparable dose coverage, dose hot spots in the target, and dose hot spots in BrainROI. DLVH analysis indicated that LET-guided robust optimization could either reduce LET at the same dose level or redistribute high LET from high dose regions to low dose regions.

CONCLUSION

Per-voxel constraint is a powerful tool to minimize dose/LET hot spots in IMPT. The LET-guided robustly optimized plans outperformed the conventional dose-only robustly optimized plans in terms of xBD hot spots control.

Research progress on mechanism and imaging of temporal lobe injury induced by radiotherapy for head and neck cancer

Radiotherapy (RT) is an effective treatment for head and neck cancer (HNC). Radiation-induced temporal lobe injury (TLI) is a serious complication of RT. Late symptoms of radiation-induced TLI are irreversible and manifest as memory loss, cognitive impairment, and even temporal lobe necrosis (TLN). It is currently believed that the mechanism of radiation-induced TLI involves microvascular injury, neuron and neural stem cell injury, glial cell damage, inflammation, and the production of free radicals. Significant RT-related structural changes and dose-dependent changes in gray matter (GM) and white matter (WM) volume and morphology were observed through computed tomography (CT) and magnetic resonance imaging (MRI) which were common imaging assessment tools. Diffusion tensor imaging (DTI), dispersion kurtosis imaging (DKI), susceptibility-weighted imaging (SWI), resting-state functional magnetic resonance (rs-fMRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET) can be used for early diagnosis and prognosis evaluation according to functional, molecular, and cellular processes of TLI. Early diagnosis of TLI is helpful to reduce the incidence of TLN and its related complications. This review summarizes the clinical features, mechanisms, and imaging of radiation-induced TLI in HNC patients. KEY POINTS: • Radiation-induced temporal lobe injury (TLI) is a clinical complication and its symptoms mainly include memory impairment, headache, and cognitive impairment. • The mechanisms of TLI include microvascular injury, cell injury, and inflammatory and free radical injury. Significant RT-related structural changes and dose-dependent changes in TL volume and morphology were observed through CT and MRI. • SWI, MRS, DTI, and DKI and other imaging examinations can detect anatomical and functional, molecular, and cellular changes of TLI.

Half-Brain Delineation for Prediction of Radiation-Induced Temporal Lobe Injury in Nasopharyngeal Carcinoma Receiving Intensity-Modulated Radiotherapy

Purpose

To investigate the role of half-brain delineation in the prediction of radiation-induced temporal lobe injury (TLI) in nasopharyngeal carcinoma (NPC) receiving intensity-modulated radiotherapy (IMRT).

Methods and Materials

A total of 220 NPC cases treated with IMRT and concurrent platinum-based chemotherapy were retrospectively analyzed. Dosimetric parameters of temporal lobes, half-brains, and brains included maximum dose (D_max), doses covering certain volume (D_V) from 0.03 to 20 cc and absolute volumes receiving specific dose (V_D) from 40 to 80 Gy. Inter-structure variability was assessed by coefficients of variation (CV) and paired samples t-tests. Receiver operating characteristic curve (ROC) and Youden index were used for screening dosimetric parameters to predict TLI. Dose/volume response curve was calculated using the logistic dose/volume response model.

Results

CVs of brains, left/right half-brains, and left/right temporal lobes were 9.72%, 9.96%, 9.77%, 27.85%, and 28.34%, respectively. Each D_V in temporal lobe was significantly smaller than that in half-brain (P < 0.001), and the reduction ranged from 3.10% to 45.98%. The area under the curve (AUC) of D_V and V_D showed an "increase-maximum-decline" behavior with a peak as the volume or dose increased. The maximal AUCs of D_Vs in brain, half-brain and temporal lobe were 0.808 (D_2cc), 0.828 (D_1.2cc) and 0.806 (D_0.6cc), respectively, and the maximal AUCs of V_Ds were 0.818 (D_75Gy), 0.834 (V_72Gy) and 0.814 (V_70Gy), respectively. The cutoffs of V_70Gy (0.86 cc), V_71Gy (0.72 cc), V_72Gy (0.60 cc), and V_73Gy (0.45 cc) in half-brain had better Youden index. TD5/5 and TD50/5 of D_1.2cc were 58.7 and 80.0 Gy, respectively. The probability of TLI was higher than >13% when V_72Gy>0 cc, and equal to 50% when V_72Gy = 7.66 cc.

Conclusion

Half-brain delineation is a convenient and stable method which could reduce contouring variation and could be used in NPC patients. D_1.2cc and V_72Gy of half-brain are feasible for TLI prediction model. The dose below 70 Gy may be relatively safe for half-brain. The cutoff points of V_70-73Gy could be considered when the high dose is inevitable.

Altered properties of brain white matter structural networks in patients with nasopharyngeal carcinoma after radiotherapy

Previous neuroimaging studies revealed radiation-induced brain injury in patients with nasopharyngeal carcinoma (NPC) in the years after radiotherapy (RT). These injuries may be associated with structural and functional alterations. However, differences in the brain structural connectivity of NPC patients at different times after RT, especially in the early-delayed period, remain unclear. We acquired diffusion tensor imaging (DTI) data from three groups of NPC patients, 25 in the pre-RT (before RT) group, 22 in the early-delayed (1-6 months) period (post-RT-ED) group, and 33 in the late-delayed (>6 months) period (post-RT-LD) group. Then, we constructed brain white matter (WM) structural networks and used graph theory to compare their between-group differences. The NPC patients in the post-RT-ED group showed decreased global properties when compared with the pre-RT group. We also detected the nodes with between-group differences in nodal parameters. The nodes that differed between the post-RT-ED and pre-RT groups were mainly located in the default mode (DMN) and central executive networks (CEN); those that differed between the post-RT-LD and pre-RT groups were located in the limbic system; and those that differed between the post-RT-LD and post-RT-ED groups were mainly in the DMN. These findings may indicate that radiation-induced brain injury begins in the early-delayed period and that a reorganization strategy begins in the late-delayed period. Our findings may provide new insight into the pathogenesis of radiation-induced brain injury in normal-appearing brain tissue from the network perspective.

Normal tissue complication probability (NTCP) models for predicting temporal lobe injury after intensity-modulated radiotherapy in nasopharyngeal carcinoma: A large registry-based retrospective study from China

PURPOSE

To develop predictive models with dosimetric and clinical variables for temporal lobe injury (TLI) in nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).

MATERIALS AND METHODS

Data of 8194 NPC patients who received IMRT-based treatment were retrospectively reviewed. TLI was diagnosed by magnetic resonance imaging. Dosimetric factors were selected by penalized regression and machine learning, with area under the receiver operating curve (AUC) calculated. Cox proportional hazards models containing the most predictive dosimetric factor with/without clinical variables were performed. A nomogram was generated as a visualization of Cox regression for predicting TLI-free survival.

RESULTS

During median follow-up of 66.8 months (interquartile range [IQR] 54.2-82.2 months), 12.1% of patients (989/8194) developed TLI. Median latency from IMRT to TLI was 36 months (IQR 28-47 months). D_0.5cc (dose delivered to 0.5-cm³ temporal-lobe volume) was the most predictive dosimetric factor (AUC: 0.799). Tolerance dose for 5% and 50% probabilities to develop TLI in 5 years were 65.06 Gy (95% confidence interval [CI]: 64.19-65.92) and 89.75 Gy (95% CI: 87.39-92.11), respectively. A nomogram comprising age, T stage, and D_0.5cc significantly outperformed the model with only D_0.5cc in predicting TLI (C-index: 0.78 vs. 0.737 in train set; 0.775 vs. 0.73 in test set; both P < 0.001). The nomogram-defined high-risk group had worse 5-year TLI-free survival.

CONCLUSIONS

D_0.5cc of 65.06 Gy was the tolerance dose of the temporal lobe. Reducing D_0.5cc decreased risk of TLI, especially in older patients with advanced T stage. The nomogram could predict TLI precisely and allow individualized follow-up management.

Temporal Lobe Necrosis Following Radiotherapy in Nasopharyngeal Carcinoma: New Insight Into the Management

Cerebral radiation necrosis (CRN) is one of the most prominent sequelae following radiation therapy for nasopharyngeal carcinoma (NPC), which might have devastating effects on patients' quality of life (QOL). Advances in histopathology and neuro-radiology have shed light on the management of CRN more comprehensively, yet effective therapeutic interventions are still lacking. CRN was once regarded as progressive and irreversible, however, in the past 20 years, with the application of intensity-modulated radiation therapy (IMRT), both the incidence and severity of CRN have declined. In addition, newly developed medical agents including bevacizumab-a humanized monoclonal antibody against vascular endothelial growth factor (VEGF), nerve growth factor (NGF), monosialotetrahexosylganglioside (GM1), etc., have shown great potency in successfully reversing radiation-induced CRN. As temporal lobes are most frequently compromised in NPC patients, this review will summarize the state-of-the-art progress regarding the incidence, pathophysiology, prevention, treatment, and prognosis of temporal lobe necrosis (TLN) after IMRT in NPC.

Temporal Lobe Necrosis in Head and Neck Cancer Patients after Proton Therapy to the Skull Base

PURPOSE

To demonstrate temporal lobe necrosis (TLN) rate and clinical/dose-volume factors associated with TLN in radiation-naïve patients with head and neck cancer treated with proton therapy where the field of radiation involved the skull base.

MATERIALS AND METHODS

Medical records and dosimetric data for radiation-naïve patients with head and neck cancer receiving proton therapy to the skull base were retrospectively reviewed. Patients with <3 months of follow-up, receiving <45 GyRBE or nonconventional fractionation, and/or no follow-up magnetic resonance imaging (MRI) were excluded. TLN was determined using MRI and graded using Common Terminology Criteria for Adverse Events (CTCAE) v5.0. Clinical (gender, age, comorbidities, concurrent chemotherapy, smoking, radiation techniques) and dose-volume parameters were analyzed for TLN correlation. The receiver operating characteristic curve and area under the curve (AUC) were performed to determine the cutoff points of significant dose-volume parameters.

RESULTS

Between 2013 and 2019, 234 patients were included. The median follow-up time was 22.5 months (range = 3.2-69.3). Overall TLN rates of any grade, ≥ grade 2, and ≥ grade 3 were 5.6% (N = 13), 2.1%, and 0.9%, respectively. The estimated 2-year TLN rate was 4.6%, and the 2-year rate of any brain necrosis was 6.8%. The median time to TLN was 20.9 months from proton completion. Absolute volume receiving 40, 50, 60, and 70 GyRBE (absolute volume [aV]); mean and maximum dose received by the temporal lobe; and dose to the 0.5, 1, and 2 cm3 volume receiving the maximum dose (D0.5cm3, D1cm3, and D2cm3, respectively) of the temporal lobe were associated with greater TLN risk while clinical parameters showed no correlation. Among volume parameters, aV50 gave maximum AUC (0.921), and D2cm3 gave the highest AUC (0.935) among dose parameters. The 11-cm3 cutoff value for aV50 and 62 GyRBE for D2cm3 showed maximum specificity and sensitivity.

CONCLUSION

The estimated 2-year TLN rate was 4.6% with a low rate of toxicities ≥grade 3; aV50 ≤11 cm3, D2cm3 ≤62 GyRBE and other cutoff values are suggested as constraints in proton therapy planning to minimize the risk of any grade TLN. Patients whose temporal lobe(s) unavoidably receive higher doses than these thresholds should be carefully followed with MRI after proton therapy.

Hypoxia-Induced Epithelial-Mesenchymal Transition in Cancers: HIF-1α and Beyond

Metastasis is the main cause of cancer-related mortality. Although the actual process of metastasis remains largely elusive, epithelial-mesenchymal transition (EMT) has been considered as a major event in metastasis. Besides, hypoxia is common in solid cancers and has been considered as an important factor for adverse treatment outcomes including metastasis. Since EMT and hypoxia potentially share several signaling pathways, many recent studies focused on investigate the issue of hypoxia-induced EMT. Among all potential mediators of hypoxia-induced EMT, hypoxia-inducible factor-1α (HIF-1α) has been studied extensively. Moreover, there are other potential mediators that may also contribute to the process. This review aims to summarize the recent reports on hypoxia-induced EMT by HIF-1α or other potential mediators and provide insights for further investigations on this issue. Ultimately, better understanding of hypoxia-induced EMT may allow us to develop anti-metastatic strategies and improve treatment outcomes.