Narrow interval dual phase 18F-FDG PET/CT: A practical approach for distinguishing tumor recurrence from radiation necrosis in brain metastasis.

Purpose of our research is to demonstrate efficacy of narrow interval dual phase [18F]-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) imaging in distinguishing tumor recurrence (TR) from radiation necrosis (RN) in patients treated for brain metastases. 35 consecutive patients (22 female, 13 male) with various cancer subtypes, lesion size > 1.0 cm3, and suspected recurrence on brain magnetic resonance imaging (MRI) underwent narrow interval dual phase FDG-PET/CT (30 and 90 min after tracer injection). Clinical outcome was determined via sequential MRIs or pathology reports. Maximum standard uptake value (SUVmax) of lesion (L), gray matter (GM), and white matter (WM) was measured on early (1) and delayed (2) imaging. Analyzed variables include % change, late phase, and early phase for L uptake, L/GM uptake, and L/WM uptake. Statistical analysis (P < .01), receiver operator characteristic (ROC) curve and area under curve (AUC) cutoff values were obtained. Change in L/GM ratio of > -2% was 95% sensitive, 91% specific, and 93% accurate (P < .001, AUC = 0.99) in distinguishing TR from RN. Change in SUVmax of lesion alone was the second-best indicator (P < .001, AUC = 0.94) with an ROC cutoff > 30.5% yielding 86% sensitivity, 83% specificity, and 84% accuracy. Other variables (L alone or L/GM ratios in early or late phase, all L/WM ratios) were significantly less accurate. Utilizing narrow interval dual phase FDG-PET/CT in patients with brain metastasis treated with radiation therapy provides a practical approach to distinguish TR from RN. Narrow time interval allows for better patient comfort, greater efficiency of PET/CT scanner, and lower disruption of workflow.

Imaging Assessment of Radiation Therapy-Related Normal Tissue Injury in Children: A PENTEC Visionary Statement.

The Pediatric Normal Tissue Effects in the Clinic (PENTEC) consortium has made significant contributions to understanding and mitigating the adverse effects of childhood cancer therapy. This review addresses the role of diagnostic imaging in detecting, screening, and comprehending radiation therapy-related late effects in children, drawing insights from individual organ-specific PENTEC reports. We further explore how the development of imaging biomarkers for key organ systems, alongside technical advancements and translational imaging approaches, may enhance the systematic application of imaging evaluations in childhood cancer survivors. Moreover, the review critically examines knowledge gaps and identifies technical and practical limitations of existing imaging modalities in the pediatric population. Addressing these challenges may expand access to, minimize the risk of, and optimize the real-world application of, new imaging techniques. The PENTEC team envisions this document as a roadmap for the future development of imaging strategies in childhood cancer survivors, with the overarching goal of improving long-term health outcomes and quality of life for this vulnerable population.

Radiation-induced lumbosacral plexopathy and pelvic insufficiency fracture: A case report of unique coexistence of complications after radiotherapy for prostate cancer.

Case reports of plexopathy after prostate cancer are usually neoplastic. Radiation-induced lumbosacral plexopathy and insufficiency fractures have clinical significance due to the need to differentiate them from tumoral invasions, metastases, and spinal pathologies. Certain nuances, including clinical presentation and screening methods, help distinguish radiation-induced plexopathy from tumoral plexopathy. This case report highlights the coexistence of these two rare clinical conditions. Herein, we present a 78-year-old male with a history of radiotherapy for prostate cancer who developed right foot drop, severe lower back and right groin pain, difficulty in standing up and walking, and tingling in both legs over the past month during remission. The diagnosis of lumbosacral plexopathy and pelvic insufficiency fracture was made based on magnetic resonance imaging, positron emission tomography, and electroneuromyography. The patient received conservative symptomatic treatment and was discharged with the use of a cane for mobility. Radiation-induced lumbosacral plexopathy following prostate cancer should be kept in mind in patients with neurological disorders of the lower limbs. Pelvic insufficiency fracture should also be considered if the pain does not correspond to the clinical findings of plexopathy. These two pathologies, which can be challenging to diagnose, may require surgical or complex management approaches. However, in this patient, conservative therapies led to an improvement in quality of life and a reduction in the burden of illness.

Leveraging radiomics and machine learning to differentiate radiation necrosis from recurrence in patients with brain metastases.

OBJECTIVE: Radiation necrosis (RN) can be difficult to radiographically discern from tumor progression after stereotactic radiosurgery (SRS). The objective of this study was to investigate the utility of radiomics and machine learning (ML) to differentiate RN from recurrence in patients with brain metastases treated with SRS. METHODS: Patients with brain metastases treated with SRS who developed either RN or tumor reccurence were retrospectively identified. Image preprocessing and radiomic feature extraction were performed using ANTsPy and PyRadiomics, yielding 105 features from MRI T1-weighted post-contrast (T1c), T2, and fluid-attenuated inversion recovery (FLAIR) images. Univariate analysis assessed significance of individual features. Multivariable analysis employed various classifiers on features identified as most discriminative through feature selection. ML models were evaluated through cross-validation, selecting the best model based on area under the receiver operating characteristic (ROC) curve (AUC). Specificity, sensitivity, and F1 score were computed. RESULTS: Sixty-six lesions from 55 patients were identified. On univariate analysis, 27 features from the T1c sequence were statistically significant, while no features were significant from the T2 or FLAIR sequences. For clinical variables, only immunotherapy use after SRS was significant. Multivariable analysis of features from the T1c sequence yielded an AUC of 76.2% (standard deviation [SD] ± 12.7%), with specificity and sensitivity of 75.5% (± 13.4%) and 62.3% (± 19.6%) in differentiating radionecrosis from recurrence. CONCLUSIONS: Radiomics with ML may assist the diagnostic ability of distinguishing RN from tumor recurrence after SRS. Further work is needed to validate this in a larger multi-institutional cohort and prospectively evaluate it's utility in patient care.

Dynamic monitoring of radiation-induced white matter microstructure injury in nasopharyngeal carcinoma via high-angular resolution diffusion imaging.

PURPOSE: To investigate white matter microstructural abnormalities caused by radiotherapy in nasopharyngeal carcinoma (NPC) patients using MRI high-angular resolution diffusion imaging (HARDI). METHODS: We included 127 patients with pathologically confirmed NPC: 36 in the pre-radiotherapy group, 29 in the acute response period (post-RT-AP), 23 in the early delayed period (post-RT-ED) group, and 39 in the late-delayed period (post-RT-LD) group. HARDI data were acquired for each patient, and dispersion parameters were calculated to compare the differences in specific fibre bundles among the groups. The Montreal Neurocognitive Assessment (MoCA) was used to evaluate neurocognitive function, and the correlations between dispersion parameters and MoCA were analysed. RESULTS: In the right cingulum frontal parietal bundles, the fractional anisotropy value decreased to the lowest level post-RT-AP and then reversed and increased post-RT-ED and post-RT-LD. The mean, axial, and radial diffusivity were significantly increased in the post-RT-AP (p < 0.05) and decreased in the post-RT-ED and post-RT-LD groups to varying degrees. MoCA scores were decreased post-radiotherapy than those before radiotherapy (p = 0.005). MoCA and mean diffusivity exhibited a mild correlation in the left cingulum frontal parahippocampal bundle. CONCLUSIONS: White matter tract changes detected by HARDI are potential biomarkers for monitoring radiotherapy-related brain damage in NPC patients.

Progression rate of radiation-induced carotid stenosis in head and neck cancer survivors after statin treatment: a retrospective cohort study.

BACKGROUND AND AIMS: Whether statin treatment is effective in retarding the progression of radiation-induced carotid stenosis (RICS) in head and neck cancer (HNC) survivors has not been well studied. The purpose of this study was to assess the association of statin treatment with RICS progression rate in HNC survivors after radiotherapy. METHODS: We conducted a retrospective cohort study at Sun Yat-sen Memorial Hospital, Sun Yat-sen University in Guangzhou, China. Between January 2010 and December 2021, we screened HNC survivors whose carotid ultrasound scans had shown stenosis of the common and/or internal carotid arteries. The primary outcome was the RICS progression rate. We compared eligible patients treated with statins with those who did not in multivariable Cox regression models. RESULTS: A total of 200 patients were included in this study, of whom 108 received statin treatment and 92 did not. Over a mean follow-up time of 1.5 years, 56 (28.0%) patients showed RICS progression, 24 (42.9%) and 32 (57.1%) in the statin and control groups, respectively. The statin group showed less RICS progression than the control group (adjusted-HR 0.49, 95% CI 0.30-0.80, P = 0.005). In the subgroup analysis, there was no significant interaction in the effect of statins on lowering RICS progression rate in the subgroups stratified by baseline low-density lipoprotein cholesterol (LDL-C) levels (P for interaction = 0.53) or baseline degrees of stenosis (P for interaction = 0.50). CONCLUSIONS: Statin treatment was associated with a lower risk of RICS progression in patients with HNC after radiotherapy, regardless of baseline LDL-C level and baseline stenosis degrees.

Adverse radiation effect versus tumor progression following stereotactic radiosurgery for brain metastases: Implications of radiologic uncertainty.

BACKGROUND: Adverse radiation effect (ARE) following stereotactic radiosurgery (SRS) for brain metastases is challenging to distinguish from tumor progression. This study characterizes the clinical implications of radiologic uncertainty (RU). METHODS: Cases reviewed retrospectively at a single-institutional, multi-disciplinary SRS Tumor Board between 2015-2022 for RU following SRS were identified. Treatment history, diagnostic or therapeutic interventions performed upon RU resolution, and development of neurologic deficits surrounding intervention were obtained from the medical record. Differences in lesion volume and maximum diameter at RU onset versus resolution were compared with paired t-tests. Median time from RU onset to resolution was estimated using the Kaplan-Meier method. Univariate and multivariate associations between clinical characteristics and time to RU resolution were assessed with Cox proportional-hazards regression. RESULTS: Among 128 lesions with RU, 23.5% had undergone ≥ 2 courses of radiation. Median maximum diameter (20 vs. 16 mm, p < 0.001) and volume (2.7 vs. 1.5 cc, p < 0.001) were larger upon RU resolution versus onset. RU resolution took > 6 and > 12 months in 25% and 7% of cases, respectively. Higher total EQD2 prior to RU onset (HR = 0.45, p = 0.03) and use of MR perfusion (HR = 0.56, p = 0.001) correlated with shorter time to resolution; larger volume (HR = 1.05, p = 0.006) portended longer time to resolution. Most lesions (57%) were diagnosed as ARE. Most patients (58%) underwent an intervention upon RU resolution; of these, 38% developed a neurologic deficit surrounding intervention. CONCLUSIONS: RU resolution took > 6 months in > 25% of cases. RU may lead to suboptimal outcomes and symptom burden. Improved characterization of post-SRS RU is needed.

Umbrella review and network meta-analysis of diagnostic imaging test accuracy studies in Differentiating between brain tumor progression versus pseudoprogression and radionecrosis.

PURPOSE: In this study we gathered and analyzed the available evidence regarding 17 different imaging modalities and performed network meta-analysis to find the most effective modality for the differentiation between brain tumor recurrence and post-treatment radiation effects. METHODS: We conducted a comprehensive systematic search on PubMed and Embase. The quality of eligible studies was assessed using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) instrument. For each meta-analysis, we recalculated the effect size, sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio from the individual study data provided in the original meta-analysis using a random-effects model. Imaging technique comparisons were then assessed using NMA. Ranking was assessed using the multidimensional scaling approach and by visually assessing surface under the cumulative ranking curves. RESULTS: We identified 32 eligible studies. High confidence in the results was found in only one of them, with a substantial heterogeneity and small study effect in 21% and 9% of included meta-analysis respectively. Comparisons between MRS Cho/NAA, Cho/Cr, DWI, and DSC were most studied. Our analysis showed MRS (Cho/NAA) and 18F-DOPA PET displayed the highest sensitivity and negative likelihood ratios. 18-FET PET was ranked highest among the 17 studied techniques with statistical significance. APT MRI was the only non-nuclear imaging modality to rank higher than DSC, with statistical insignificance, however. CONCLUSION: The evidence regarding which imaging modality is best for the differentiation between radiation necrosis and post-treatment radiation effects is still inconclusive. Using NMA, our analysis ranked FET PET to be the best for such a task based on the available evidence. APT MRI showed promising results as a non-nuclear alternative.

Imaging of the Posttreatment Head and Neck: Expected Findings and Potential Complications.

Interpretation of posttreatment imaging findings in patients with head and neck cancer can pose a substantial challenge. Malignancies in this region are often managed through surgery, radiation therapy, chemotherapy, and newer approaches like immunotherapy. After treatment, patients may experience various expected changes, including mucositis, soft-tissue inflammation, laryngeal edema, and salivary gland inflammation. Imaging techniques such as CT, MRI, and PET scans help differentiate these changes from tumor recurrence. Complications such as osteoradionecrosis, chondroradionecrosis, and radiation-induced vasculopathy can arise because of radiation effects. Radiation-induced malignancies may occur in the delayed setting. This review article emphasizes the importance of posttreatment surveillance imaging to ensure proper care of patients with head and neck cancer and highlights the complexities in distinguishing between expected treatment effects and potential complications. Keywords: CT, MR Imaging, Radiation Therapy, Ear/Nose/Throat, Head/Neck, Nervous-Peripheral, Bone Marrow, Calvarium, Carotid Arteries, Jaw, Face, Larynx © RSNA, 2024.

Diffusion tensor imaging parameters for the early diagnosis of radiation-induced brain injury in patients with nasopharyngeal carcinoma: a meta-analysis.

PURPOSE: To estimate diffusion tensor imaging (DTI) parameters for early diagnosis during the stage of radiation-induced brain injury (RBI) in nasopharyngeal carcinoma (NPC) patients.PubMed, Embase, Web of Science and Cochrane Library were searched up to March 2019. Eligible studies comparing early brain injuries with controls of temporal lobe in NPC patients before and after radiotherapy which collected the DTI parameters such as apparent diffusion coefficient (ADC), fractional anisotropy (FA), axial diffusibility (λa), radial diffusibility (λr), mean diffusion (MD) were included. CONCLUSION: Seven studies (N = 21) were selected from the studies in the databases. Overall, FA, λa, λr values were significant difference between early RBI and healthy control (HC) in NPC patients after radiotherapy (MD= -0.03, 95% CI= -0.05∼-0.01; p = .008 in FA, MD= -0.07, 95% CI= -0.11∼-0.02; p = .002 in λa and MD = 0.02, 95% CI = 0.00 ∼ 0.04; p = .04 in λr). The meta regression analysis about dose dependence with FA value was: -0.057 ∼ 0.0003 in 95% CI, I2=74.70%, P = 0.052 (adjust p = .029). The overall heterogeneity is p < .001, I2=91% in FA, P = 0.08, I2=61% in λa and p = .04, I2=69% in λr. DTI parameters such as the reduced FA value, the decreased λa value, and the increased λr value were significant in the early period of RBI in NPC patients after radiotherapy, which becoming a more sensitive method in diagnosing the early stage of RBI.

Delayed Imaging Changes 18 Months or Longer After Stereotactic Radiosurgery for Brain Metastases: Necrosis or Progression.

OBJECTIVE: Imaging changes after stereotactic radiosurgery (SRS) can occur for years after treatment, although the available data on the incidence of tumor progression and adverse radiation effects (ARE) are generally limited to the first 2 years after treatment. METHODS: A single-institution retrospective review was conducted of patients who had >18 months of imaging follow-up available. Patients who had ≥1 metastatic brain lesions treated with Gamma Knife SRS were assessed for the time to radiographic progression. Those with progression ≥18 months after the initial treatment were included in the present study. The lesions that progressed were characterized as either ARE or tumor progression based on the tissue diagnosis or imaging characteristics over time. RESULTS: The cumulative incidence of delayed imaging radiographic progression was 35% at 5 years after the initial SRS. The cumulative incidence curves of the time to radiographic progression for lesions determined to be ARE and lesions determined to be tumor progression were not significantly different statistically. The cumulative incidence of delayed ARE and delayed tumor progression was 17% and 16% at 5 years, respectively. Multivariate analysis indicated that the number of metastatic brain lesions present at the initial SRS was the only factor associated with late radiographic progression. CONCLUSIONS: The timing of late radiographic progression does not differ between ARE and tumor progression. The number of metastatic brain lesions at the initial SRS is a risk factor for late radiographic progression.

Multiparametric Analysis Combining DSC-MR Perfusion and [18F]FET-PET is Superior to a Single Parameter Approach for Differentiation of Progressive Glioma from Radiation Necrosis.

PURPOSE: Perfusion-weighted (PWI) magnetic resonance imaging (MRI) and O­(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) positron emission tomography (PET) are both useful for discrimination of progressive disease (PD) from radiation necrosis (RN) in patients with gliomas. Previous literature showed that the combined use of FET-PET and MRI-PWI is advantageous; hhowever the increased diagnostic performances were only modest compared to the use of a single modality. Hence, the goal of this study was to further explore the benefit of combining MRI-PWI and [18F]FET-PET for differentiation of PD from RN. Secondarily, we evaluated the usefulness of cerebral blood flow (CBF), mean transit time (MTT) and time to peak (TTP) as previous studies mainly examined cerebral blood volume (CBV). METHODS: In this single center study, we retrospectively identified patients with WHO grades II-IV gliomas with suspected tumor recurrence, presenting with ambiguous findings on structural MRI. For differentiation of PD from RN we used both MRI-PWI and [18F]FET-PET. Dynamic susceptibility contrast MRI-PWI provided normalized parameters derived from perfusion maps (r(relative)CBV, rCBF, rMTT, rTTP). Static [18F]FET-PET parameters including mean and maximum tumor to brain ratios (TBRmean, TBRmax) were calculated. Based on histopathology and radioclinical follow-up we diagnosed PD in 27 and RN in 10 cases. Using the receiver operating characteristic (ROC) analysis, area under the curve (AUC) values were calculated for single and multiparametric models. The performances of single and multiparametric approaches were assessed with analysis of variance and cross-validation. RESULTS: After application of inclusion and exclusion criteria, we included 37 patients in this study. Regarding the in-sample based approach, in single parameter analysis rTBRmean (AUC = 0.91, p < 0.001), rTBRmax (AUC = 0.89, p < 0.001), rTTP (AUC = 0.87, p < 0.001) and rCBVmean (AUC = 0.84, p < 0.001) were efficacious for discrimination of PD from RN. The rCBFmean and rMTT did not reach statistical significance. A classification model consisting of TBRmean, rCBVmean and rTTP achieved an AUC of 0.98 (p < 0.001), outperforming the use of rTBRmean alone, which was the single parametric approach with the highest AUC. Analysis of variance confirmed the superiority of the multiparametric approach over the single parameter one (p = 0.002). While cross-validation attributed the highest AUC value to the model consisting of TBRmean and rCBVmean, it also suggested that the addition of rTTP resulted in the highest accuracy. Overall, multiparametric models performed better than single parameter ones. CONCLUSION: A multiparametric MRI-PWI and [18F]FET-PET model consisting of TBRmean, rCBVmean and PWI rTTP significantly outperformed the use of rTBRmean alone, which was the best single parameter approach. Secondarily, we firstly report the potential usefulness of PWI rTTP for discrimination of PD from RN in patients with glioma; however, for validation of our findings the prospective studies with larger patient samples are necessary.

Increased 18F-FAPI Uptake in Radiation-Induced Liver Injury.

ABSTRACT: A 51-year-old woman with breast cancer underwent a complete surgical resection and chemoradiotherapy approximately 3 months ago. Follow-up abdominal ultrasound detected a new lesion with decreased echogenicity in the hepatic segment IV/VIII. 18F-FDG PET/CT showed the hepatic lesion without abnormal uptake. The patient was subsequently enrolled in a clinical trial of 18F-FAPI PET/CT to assess the hepatic lesion. An intense 18F-FAPI activity was identified in the hepatic lesion. Finally, pathological analysis combined with imaging follow-up confirmed the diagnosis of radiation-induced liver injury.

Radiomics based predictive modeling of rectal toxicity in prostate cancer patients undergoing radiotherapy: CT and MRI comparison.

BACKGROUND: Rectal toxicity is one of the common side effects after radiotherapy in prostate cancer patients. Radiomics is a non-invasive and low-cost method for developing models of predicting radiation toxicity that does not have the limitations of previous methods. These models have been developed using individual patients' information and have reliable and acceptable performance. This study was conducted by evaluating the radiomic features of computed tomography (CT) and magnetic resonance (MR) images and using machine learning (ML) methods to predict radiation-induced rectal toxicity. METHODS: Seventy men with pathologically confirmed prostate cancer, eligible for three-dimensional radiation therapy (3DCRT) participated in this prospective trial. Rectal wall CT and MR images were used to extract first-order, shape-based, and textural features. The least absolute shrinkage and selection operator (LASSO) was used for feature selection. Classifiers such as Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), and K-Nearest Neighbors (KNN) were used to create models based on radiomic, dosimetric, and clinical data alone or in combination. The area under the curve (AUC) of the receiver operating characteristic curve (ROC), accuracy, sensitivity, and specificity were used to assess each model's performance. RESULTS: The best outcomes were achieved by the radiomic features of MR images in conjunction with clinical and dosimetric data, with a mean of AUC: 0.79, accuracy: 77.75%, specificity: 82.15%, and sensitivity: 67%. CONCLUSIONS: This research showed that as radiomic signatures for predicting radiation-induced rectal toxicity, MR images outperform CT images.

Use of 18 F-PSMA PET to Distinguish Cerebral Radiation Necrosis From Tumor Recurrence.

ABSTRACT: Brain metastasis in prostate adenocarcinoma is extremely rare and usually arises in the setting of widespread osseous and visceral metastases. Surgical resection and radiation therapy, including stereotactic radiosurgery, are the mainstays of treatment for brain metastasis. Radiation necrosis is a common complication of radiotherapy for brain metastasis, and distinguishing it from tumor recurrence by MRI is difficult because of overlapping findings. We present a 73-year-old man with prostate cancer with a solitary brain metastasis where PET with 18 F-piflufolostat helped detect disease recurrence in the setting of ambiguous MRI findings.

Artificial intelligence and radiation effects on brain tissue in glioblastoma patient: preliminary data using a quantitative tool.

PURPOSE: The quantification of radiotherapy (RT)-induced functional and morphological brain alterations is fundamental to guide therapeutic decisions in patients with brain tumors. The magnetic resonance imaging (MRI) allows to define structural RT-brain changes, but it is unable to evaluate early injuries and to objectively quantify the volume tissue loss. Artificial intelligence (AI) tools extract accurate measurements that permit an objective brain different region quantification. In this study, we assessed the consistency between an AI software (Quibim Precision® 2.9) and qualitative neruroradiologist evaluation, and its ability to quantify the brain tissue changes during RT treatment in patients with glioblastoma multiforme (GBM). METHODS: GBM patients treated with RT and subjected to MRI assessment were enrolled. Each patient, pre- and post-RT, undergoes to a qualitative evaluation with global cerebral atrophy (GCA) and medial temporal lobe atrophy (MTA) and a quantitative assessment with Quibim Brain screening and hippocampal atrophy and asymmetry modules on 19 extracted brain structures features. RESULTS: A statistically significant strong negative association between the percentage value of the left temporal lobe and the GCA score and the left temporal lobe and the MTA score was found, while a moderate negative association between the percentage value of the right hippocampus and the GCA score and the right hippocampus and the MTA score was assessed. A statistically significant strong positive association between the CSF percentage value and the GCA score and a moderate positive association between the CSF percentage value and the MTA score was found. Finally, quantitative feature values showed that the percentage value of the cerebro-spinal fluid (CSF) statistically differences between pre- and post-RT. CONCLUSIONS: AI tools can support a correct evaluation of RT-induced brain injuries, allowing an objective and earlier assessment of the brain tissue modifications.

Imaging features of radiation-induced lung disease and its relationship with clinical and dosimetric factors in breast cancer patients.

Aim: The aim is to extensively evaluate imaging features of radiation induced lung disease in breast cancer patients and to determine the relationship of imaging alterations with dosimetric parameters and patient related characteristics. Materials and Methods: A total of 76 breast cancer patients undergoing radiotherapy (RT) were studied retrospectively by case notes, treatment plans, dosimetric parameters, and chest computed tomography (CT) scans. Time intervals, that chest CT scans were acquired, were grouped as 1-6 months, 7-12 months, 13-18 months and more than 18 months after RT. Chest CTs (one or more for each patient) were assessed for the presence of ground glass opacity, septal thickening, consolidation/patchy pulmonary opacity/alveolar infiltrates, subpleural air cyst, air bronchogram, parenchymal bands, traction bronchiectasis, pleural/subpleural thickening and pulmonary volume loss. These alterations were scored by applying a system devised by Nishioka et al. Nishioka scores were analyzed for the relationship with clinical and dosimetric factors. Statistical Analysis Used: IBM SPSS Statistics for Windows, version 22.0 (IBM Corp., Armonk, N.Y., USA) was used to analyze data. Results: Median follow-up time was 49 months. Advanced age and aromatase inhibitor intake were correlated with higher Nishioka scores for 1-6 months' period. However, both were found nonsignificant in multivariate analysis. Nishioka scores of CT scans acquired more than 12 months after RT were positively correlated with mean lung dose, V5, V20, V30, and V40. Receiver operating characteristic analysis revealed that V5 for ipsilateral lung was the most robust dosimetric parameter predicting chronic lung injury. V5 >41% indicates the development of radiological lung changes. Conclusions: Keeping V5 ≤41% for ipsilateral lung could provide avoiding chronic lung sequelae.

High-dose bevacizumab for radiation-induced brain necrosis: a case report.

Radiation-induced brain necrosis (RIBN) is a common adverse event from radiation therapy. We present a case of a 56-year-old man, diagnosed with non-small-cell lung cancer with brain metastases 2 years prior, for which he had received whole brain radiotherapy and brain stereotactic radiosurgery, who presented to the oncology unit with headache, dizziness and abnormal gait. MRI of the brain revealed radiological worsening of a cerebellar mass, including edema and mass effect. After a multidisciplinary tumor board meeting, the patient was diagnosed with RIBN and received 4 cycles of high-dose bevacizumab, with complete symptom resolution and significant radiological response. We report the successful use of a high-dose, shorter-duration treatment protocol of bevacizumab for RIBN.

Radiation therapy, which is commonly used in the treatment of cancer, often causes cells to die. We report the case of a 56-year-old man with lung cancer that had spread to his brain, who received radiation therapy, but later experienced symptoms like headache, dizziness and difficulty walking. Scans showed that the radiation had caused damage to his brain, specifically a mass in the cerebellum. The patient received bevacizumab, a drug that inhibits the growth of new blood vessels, in a higher dose than usual but for fewer times overall. After treatment, the patient was completely symptom-free, while the scans showed significant improvement.

What effective technique to differentiate radiation brain necrosis from a tumor progression in patients treated with radiation: A monocentric retrospective study combining the MRI TRAMs technique and the (18F)-dopa PET/CT.

PURPOSE: Brain necrosis after radiotherapy is a challenging diagnosis, since it has similar radiological appearance on standard MRI to tumor progression. Consequences on treatment decisions can be important. We compare recent imaging techniques in order to adopt a reliable diagnostic protocol in doubtful situations. PATIENTS AND METHOD: This is a retrospective study comparing the performance of three imaging techniques after radiotherapy of brain metastasis: Perfusion-MRI, TRAMs technique and F-dopa PET-CT. The evolution of the treated metastasis volume was also analyzed by contouring all patients MRIs. All included patients were suspected of relapse and had the three exams once the volume of treated metastasis increased. RESULTS: The majority of our patients were treated by stereotactic radiotherapy. Suspicion of relapse was on average around 17months after treatment. Four cases of radionecrosis were diagnosed and six cases of real tumor progression. Neurological symptoms were less present in radionecrosis cases. All of our radionecrosis cases had relative cerebral blood volume below 1. F-dopa PET-CT succeeded to set the good diagnosis in eight cases, although we found one false positive and one false negative exam. The TRAMs technique failed in one case of false negative exam. CONCLUSIONS: Perfusion-MRI showed high performance in the diagnosis of radionecrosis, especially when calculating relative cerebral blood volume rate. The TRAMs technique showed interesting results and deserves application in daily routine combined with the perfusion-MRI. F-dopa CT might induce false results because of different metabolic uptake according to tumor type, medication and brain blood barrier leak.

Machine-learning with region-level radiomic and dosimetric features for predicting radiotherapy-induced rectal toxicities in prostate cancer patients.

BACKGROUND AND PURPOSE: This study aims to build machine learning models to predict radiation-induced rectal toxicities for three clinical endpoints and explore whether the inclusion of radiomic features calculated on radiotherapy planning computerised tomography (CT) scans combined with dosimetric features can enhance the prediction performance. MATERIALS AND METHODS: 183 patients recruited to the VoxTox study (UK-CRN-ID-13716) were included. Toxicity scores were prospectively collected after 2 years with grade ≥ 1 proctitis, haemorrhage (CTCAEv4.03); and gastrointestinal (GI) toxicity (RTOG) recorded as the endpoints of interest. The rectal wall on each slice was divided into 4 regions according to the centroid, and all slices were divided into 4 sections to calculate region-level radiomic and dosimetric features. The patients were split into a training set (75%, N = 137) and a test set (25%, N = 46). Highly correlated features were removed using four feature selection methods. Individual radiomic or dosimetric or combined (radiomic + dosimetric) features were subsequently classified using three machine learning classifiers to explore their association with these radiation-induced rectal toxicities. RESULTS: The test set area under the curve (AUC) values were 0.549, 0.741 and 0.669 for proctitis, haemorrhage and GI toxicity prediction using radiomic combined with dosimetric features. The AUC value reached 0.747 for the ensembled radiomic-dosimetric model for haemorrhage. CONCLUSIONS: Our preliminary results show that region-level pre-treatment planning CT radiomic features have the potential to predict radiation-induced rectal toxicities for prostate cancer. Moreover, when combined with region-level dosimetric features and using ensemble learning, the model prediction performance slightly improved.