Cerebral Radiation Necrosis: Incidence, Pathogenesis, Diagnostic Challenges, and Future Opportunities

Ali, Faisal S.; Arevalo, Octavio; Zorofchian, Soheil; Patrizz, Anthony; Riascos, Roy; Tandon, Nitin; Blanco, Angel I.; Ballester, Leomar Y.; Esquenazi, Yoshua

doi:10.1007/s11912-019-0818-y

Cited by 91 publications

(123 citation statements)

References 98 publications

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“…The rst hypothesis postulates that radiation causes damage to endothelial cells by upregulating ceramide, resulting in vascular insu ciency and infarction, followed by brain necrosis (4,6,8,9). Hypoxia caused by endothelial cell damage leads to the liberation of hypoxia-inducible factor 1α and vascular endothelial growth factor (VEGF) (4,6,8,9).VEGF induce new vessel formation, but these tend to be leaky capillaries, resulting in perilesional edema (6,8,9). The second hypothesis postulates that radiation damages the glial cells, especially oligodendrocytes, aggravating capillary permeability defects and causing demyelination of the white matter (4, 6).…”

Section: Discussionmentioning

confidence: 99%

“…The clinical features of CRN vary depending upon the location and size, including features of increased intracranial pressure. The characteristic ndings are seizures, hemiparesis, headache, vomiting, poor concentration, and altered level of consciousness (4)(5)(6)10). The literature also reported Neurocognitive impairment (hippocampus), especially in children, which includes poor academic performance, distorted self-image, and psychological distress (6,11).…”

Section: Discussionmentioning

confidence: 99%

“…It may re ect the di culty of MRS in differentiating radiation-induced cytolytic changes from reactive gliosis from a recurrent tumor (14). Positron emission tomography (PET) scan uses 18F-uorodeoxyglucose (FDG) to assess the tissue activity (4,6,10). Necrotic tissue will demonstrate low FDG uptake (4,6,10).…”

Section: Discussionmentioning

confidence: 99%

“…Positron emission tomography (PET) scan uses 18F-uorodeoxyglucose (FDG) to assess the tissue activity (4,6,10). Necrotic tissue will demonstrate low FDG uptake (4,6,10). However, a PET scan can provide false-positive ndings when epileptic activity coexist (hypermetabolism) (10).…”

Section: Discussionmentioning

confidence: 99%

“…Recent studies have suggested that immediate, adjuvant RT appears to be strongly associated with improved survival rate of high-grade meningiomas (2,3). CRN is the most relevant side effect after RT and can masquerade as tumor recurrence (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16). Thus, both establishing an accurate diagnosis and reaching a prompt treatment decisions are challenging.…”

Section: Introductionmentioning

confidence: 99%

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Cerebral Radiation Necrosis Masquerading as Recurrent, High-Grade Meningioma: A Case Report

AlQooti¹,

Luther²,

Shah³

et al. 2020

Preprint

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Background: Cerebral radiation necrosis (CRN) is a complication caused by radiation therapy (RT) used for treating high-grade intracranial neoplasms. It is essential to be aware of this condition as it can be frequently mistaken for tumor recurrence. Herein, we report a case of misdiagnosis of CRN in a young male, which has heavily influenced his clinical history.Case Presentation: We report a 25-year-old male diagnosed with right frontal convexity meningioma based on computerized tomography (CT)/magnetic resonance imaging (MRI). The operation achieved a macroscopically complete tumor resection. The histopathology was an atypical meningioma. Accordingly, the patient received RT. The patient reported new-onset of generalized seizures and worsening of left hemiparesis three months after completion of RT. MRI showed abnormal peripheral enhancement in the right frontal region involving the genu of the corpus callosum and extensive brain edema. Magnetic resonance spectrometry (MRS) changes were suggestive of tumor recurrence. The patient underwent surgery with total resection of the lesion. The histopathology was CRN without evidence of tumor recurrence. Due to refractory progressive brain edema, the patient’s clinical status deteriorated until he expired.Conclusion: CRN carries morbidity and mortality as a complication from brain irradiation. There is no single modality that can reliably distinguish CRN from recurrent tumor. Therefore, a multimodality approach highly recommended.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cerebral Radiation Necrosis Masquerading as Recurrent, High-Grade Meningioma: A Case Report

AlQooti¹,

Luther²,

Shah³

et al. 2020

Preprint

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A pretreatment multiparametric MRI‐based radiomics‐clinical machine learning model for predicting radiation‐induced temporal lobe injury in patients with nasopharyngeal carcinoma

Wang,

Qiu,

Zhou

et al. 2024

Head & Neck

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BackgroundTo establish and validate a machine learning model using pretreatment multiparametric magnetic resonance imaging‐based radiomics data with clinical data to predict radiation‐induced temporal lobe injury (RTLI) in patients with nasopharyngeal carcinoma (NPC) after intensity‐modulated radiotherapy (IMRT).MethodsData from 230 patients with NPC who received IMRT (130 with RTLI and 130 without) were randomly divided into the training (n = 161) and validation cohort (n = 69) with a ratio of 7:3. Radiomics features were extracted from pretreatment apparent diffusion coefficient (ADC) map, T2‐weighted imaging (T2WI), and CE‐T1‐weighted imaging (CE‐T1WI). T‐test, spearman rank correlation, and least absolute shrinkage and selection operator (LASSO) algorithm were employed to identify significant radiomics features. Clinical features were selected with univariate and multivariate analyses. Radiomics and clinical models were constructed using multiple machine learning classifiers, and a clinical‐radiomics nomogram that combined clinical with radiomics features was developed. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were drawn to compare and verify the predictive performances of the clinical model, radiomics model, and clinical‐radiomics nomogram.ResultsA total of 5064 radiomics features were extracted, from which 52 radiomics features were selected to construct the radiomics signature. The AUC of the radiomics signature based on multiparametric MRI was 0.980 in the training cohort and 0.969 in the validation cohort, outperforming the radiomics signature only based on T2WI and CE‐T1WI (p < 0.05), which highlighted the significance of the DWI sequence in the prediction of temporal lobe injury. The area under the curve (AUC) of the clinical model was 0.895 in the training cohort and 0.905 in the validation cohort. The nomogram, which integrated radiomics and clinical features, demonstrated an impressive AUC value of 0.984 in the validation set; however, no statistically significant difference was observed compared to the radiomics model. The calibration curve and decision curve analysis of the nomogram demonstrated excellent predictive performance and clinical feasibility.ConclusionsThe clinical‐radiomics nomogram, integrating clinical features with radiomics features derived from pretreatment multiparametric MRI, exhibits compelling predictive performance for RTLI in patients diagnosed with NPC.

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Cost-effectiveness analysis of bevacizumab for cerebral radiation necrosis treatment based on real-world utility value in China

Luo,

Lai,

et al. 2024

Strahlenther Onkol

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Cerebral Radiation Necrosis: Incidence, Pathogenesis, Diagnostic Challenges, and Future Opportunities

Cited by 91 publications

References 98 publications

Cerebral Radiation Necrosis Masquerading as Recurrent, High-Grade Meningioma: A Case Report

Cerebral Radiation Necrosis Masquerading as Recurrent, High-Grade Meningioma: A Case Report

A pretreatment multiparametric MRI‐based radiomics‐clinical machine learning model for predicting radiation‐induced temporal lobe injury in patients with nasopharyngeal carcinoma

Cost-effectiveness analysis of bevacizumab for cerebral radiation necrosis treatment based on real-world utility value in China

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