Search Results (90)

Recurrent brain tumors—including high-grade gliomas, brain metastases, and aggressive meningiomas—continue to carry a poor prognosis, with high mortality despite therapeutic advances. The aim of this narrative review is to summarize and critically discuss the current evidence on the role of intra-arterial radioligand therapy (RLT) in the treatment of recurrent brain tumors. RLT, a targeted form of radionuclide therapy, has gained increasing attention for its potential theranostic applications in neuro-oncology. A literature search was conducted using PubMed and Scopus, including clinical studies evaluating intra-arterial radioligand delivery in central nervous system tumors. Recent research has explored intra-arterial administration of radioligands targeting somatostatin receptors and prostate-specific membrane antigen (PSMA). Somatostatin receptors are overexpressed in meningiomas, while PSMA is highly expressed in the neovasculature of glioblastomas and brain metastases; both targets can be addressed using lutetium-177 (¹⁷⁷Lu)- or actinium-225 (²²⁵Ac)-labeled radiopharmaceuticals, traditionally delivered intravenously. Available evidence indicates that the intra-arterial route achieves markedly higher radionuclide uptake on ⁶⁸Ga-PSMA-11 and ⁶⁸Ga-DOTATOC PET, as well as increased absorbed doses in dosimetric models. Dosimetric analyses consistently show greater tracer accumulation compared with intravenous administration, without evidence of significant peri-procedural toxicity. Uptake in healthy brain tissue is minimal, and no relevant differences have been reported in liver or salivary gland accumulation between intra-arterial and intravenous RLT. Although based on heterogeneous and limited data, intra-arterial RLT appears to be a promising therapeutic strategy for recurrent brain tumors. Future research should focus on improving radioligand delivery beyond the blood–brain barrier and enhancing effective tumor targeting. Full article

Background and Clinical Significance: Breast cancer is the most frequent malignancy in women. Metastatic breast cancer is considered a treatable but incurable condition, with a median overall survival of only 2–3 years. Among its subtypes, triple-negative breast cancer (TNBC) accounts for a high proportion of breast cancer-related deaths. It is characterized by an aggressive clinical course, early recurrence, and a strong propensity for visceral and brain metastases. Case Presentation: We report the case of a Caucasian woman who developed systemic disease recurrence with lung and mediastinal lymph node metastases, occurring two years after her primary diagnosis and treatment for TNBC. The patient received three months of chemotherapy combined with an adjuvant integrative protocol consisting of melatonin, cannabidiol, and oxygen–ozone therapy. This combined approach led to the complete disappearance of the lung nodules. Subsequently, stereotactic radiotherapy was performed and, in association with the ongoing integrative treatment, resulted in a significant reduction in mediastinal adenopathy. Introduction of immunotherapy, supported continuously by the same adjuvant strategy, achieved a complete and durable remission. Strikingly, the patient remained disease-free five years after the diagnosis of lung and mediastinal metastases. Conclusions: This clinical case highlights the potential benefit of using melatonin, cannabidiol, and oxygen–ozone therapy as part of an integrative approach in patients with aggressive metastatic TNBC. While it is not possible to establish causality from a single case, the sustained remission observed suggests that such unconventional adjuvant strategies could play a supportive role in enhancing the efficacy of standard oncologic therapies. Full article

Background: Sinonasal neuroendocrine carcinoma (SNEC) is an extremely rare malignancy, and, to date, no clinical reports have detailed the use of proton beam therapy (PBT) for this disease. The present study describes the clinical courses of patients with SNEC treated with PBT and highlights the advantages of PBT. Methods: In this retrospective study, we included patients with pathologically confirmed SNEC without distant metastasis who underwent PBT at our institution between 2006 and 2021. To evaluate the dosimetric advantages of PBT, comparative treatment plans using VMAT were created. Result: Six patients with pathologically diagnosed SNEC without distant metastasis were treated with PBT. Multimodal treatment was applied in five patients, including chemotherapy in four cases and surgery in two cases. The median follow-up period was 37.4 months (range: 6.9 to 108.9 months). At the end of the follow-up, three patients were alive without recurrence, while three had died due to the disease. Recurrence occurred in three cases: one local recurrence, one in cervical lymph nodes, and two distant metastases. A late adverse event of Grade 4 vision decrease was observed in one patient on the ipsilateral side. Compared with VMAT, PBT lowered the average brain dose (median 3.3 Gy (RBE) vs. 12.6 Gy), brainstem D2 cc (10.7 Gy (RBE) vs. 34.9 Gy) and contralateral optic nerve D0.1 cc (47.6 Gy (RBE) vs. 63.3 Gy), while doses to the ipsilateral optic pathway were comparable. Conclusions: PBT in multimodal treatment achieved feasible local control for SNEC. The dose-sparing effect of PBT was more evident in organs distant from the target, although careful consideration is required for adjacent structures. Full article

Small-cell lung carcinoma (SCLC) remains one of the most aggressive lung cancers and continues to pose a major challenge for precision oncology. Despite its morphological uniformity, SCLC exhibits marked molecular heterogeneity with recurrent, potentially targetable genomic alterations. Comprehensive profiling is often hindered by limited tissue availability and the need for rapid therapeutic intervention. We performed genomic profiling of 55 primary and metastatic SCLC samples using a 324-gene hybrid-capture next-generation sequencing panel. Consistent with prior reports, nearly all tumors exhibited biallelic TP53 and RB1 inactivation. Recurrent alterations involved the PI3K/Akt/mTOR pathway (62%), chromatin regulators (42%), and NOTCH signaling genes (15%). PTEN mutations were enriched in brain metastases. Frequent copy-number gains affected SOX2, NKX2-1, MYC-family genes, and CCNE1. Two novel recurrent amplifications of potential clinical significance were identified: TYRO3 (33%) and SDHA (13%). TYRO3, a TAM family receptor tyrosine kinase, and SDHA, a mitochondrial enzyme involved in succinate metabolism, may contribute to tumor progression and represent emerging therapeutic vulnerabilities. These findings underscore the genomic diversity of SCLC and highlight the potential utility of broad next-generation sequencing in uncovering new molecular targets for precision therapy. Full article

Background: Radiation therapy is a key treatment modality for brain metastases. While providing a treatment alternative, post-treatment imaging often presents diagnostic challenges, particularly in distinguishing tumor recurrence from radiation-induced changes such as necrosis. Advanced imaging techniques and artificial intelligence (AI)-based radiomic analyses emerge as alternatives to help lesion characterization. The objective of this study was to assess the capacity of machine learning algorithms to distinguish between brain metastases recurrence and radiation necrosis. Methods: The research was conducted in two phases and used publicly available MRI data from patients treated with Gamma Knife radiosurgery. In the first phase, 30 cases of local recurrence of brain metastases and 30 cases of radiation-induced necrosis were considered. Image segmentation and radiomic feature extraction were performed on these data using MatRadiomics_1_5_3, a MATLAB-based framework integrating PyRadiomics. Features were then selected using point-biserial correlation. In the second phase, a classification was performed using a Support Vector Machine model with repeated stratified cross-validation settings. Results: The results achieved an accuracy on the test set of 83% for distinguishing metastases from necrosis. Conclusions: The results of this feasibility study demonstrate the potential of radiomics and AI to improve diagnostic accuracy and personalized care in neuro-oncology. Full article

Recurrent ovarian cancer (OC) is challenging to detect early using current methods like CA-125 and imaging. Circulating tumor DNA (ctDNA) may improve disease monitoring. Here, we assess the real-world clinical utility of serial ctDNA analyses in patients with recurrent OC. We analyzed serial plasma samples (N = 23) from six patients with recurrent OC using a tumor-informed next-generation sequencing assay targeting 68 cancer-related genes developed at the University of Washington. ctDNA variant allele frequencies (VAFs) were correlated with CA-125 levels, radiographic findings, and clinical outcomes. ctDNA levels generally reflected clinical status, accurately mirroring disease progression and therapeutic response. In one patient, rising ctDNA preceded clinical recurrence by four months, despite normal CA-125 and imaging, highlighting its potential advantage. Conversely, some patients exhibited clinical progression with undetectable ctDNA, indicating limitations in assay sensitivity, biological factors, or metastatic sites (e.g., brain metastases). ctDNA and CA-125 showed complementary value in most cases, suggesting potential combined use in clinical monitoring. Our findings demonstrate that ctDNA is a promising biomarker to complement existing monitoring approaches for recurrent OC. In some cases, capable of predicting relapse and treatment response ahead of current clinical indicators. However, identified discordances underscore technical and biological challenges that warrant further investigation. Larger prospective studies are necessary to refine ctDNA’s clinical utility and integration into personalized OC care. Full article

Background: Brain metastases represent the most common intracranial tumours in cancer patients, with no consensus on surgical outcomes and prognostic factors. This study aimed to analyse the demographic, clinical, and tumour-related factors influencing postoperative complications, recurrence, and functional outcomes in patients undergoing surgical resection of brain metastases at a tertiary neurosurgical centre in South-Eastern Europe. Materials and Methods: A retrospective cohort of adult patients who underwent gross total (GTR) or subtotal resection (STR) for brain metastases was analysed, stratified by sex, extent of resection (GTR vs. STR), and recurrence status. Results: A total of 358 patients underwent surgical resection for brain metastases, with pulmonary carcinoma being the most common primary tumour (46.4%). Most patients had solitary metastases (87.4%), and eloquent brain regions were involved in 53.9% of cases, 20.1% experienced postoperative complications, and recurrence occurred in 10.9%. Higher preoperative KPS predicted fewer complications. GTR was not associated with complications or recurrence but was linked to lower postoperative mortality. Median overall survival was 325 days. For the three hundred fifty-four patients with survival data, median overall survival (OS) was 325 days (95% CI: 270–380). OS did not meaningfully differ by sex. Conclusions: Gross total resection was not independently associated with reduced postoperative complications or recurrence but was significantly associated with lower postoperative mortality. Functional status, eloquent brain region involvement, and age remained key determinants of clinical outcomes. Full article

Objective: The high expression of prostate-specific membrane antigen (PSMA) associated with neovascularization in non-prostatic malignant tumors and metastatic lesions has been documented in many studies. By taking advantage of the absence of PSMA-related background activity in brain tissue, in recent years, PSMA has been used for the imaging of glial tumors, especially for postoperative follow-up. The aim of this prospective study was to investigate the diagnostic value of ⁶⁸Ga-PSMA-11 PET/CT by comparing ⁶⁸Ga-PSMA-11 PET/CT, ¹⁸F-FDG PET/CT, and MRI findings in patients with brain metastases (BM). Materials and Method: In this prospective study, 27 cases, 11 female and 16 male, with a mean age of 59.48 ± 12.21 years, were included. Patients diagnosed with BM on ¹⁸F-FDG PET/CT or CT/MRI at initial diagnosis or in the follow-up period were included in the study. PET findings of BM lesions obtained from ¹⁸F-FDG and ⁶⁸Ga-PSMA-11 PET/CT imaging, demographic characteristics, histopathological data of the primary foci, and other clinical features were evaluated together. Results: Twenty-four (89%) patients were included in the study for restaging, two (7%) patients for local recurrence assessment, and one (4%) patient for local recurrence and suspicion of additional lesions. The indications for ¹⁸F-FDG PET/CT were breast carcinoma for 37% (n:10), followed by lung carcinoma for 26% (n:7), colorectal adenocarcinoma for 14% (n:4), squamous cell larynx carcinoma for 7% (n:2), gastric signet ring cell carcinoma for 4% (n:1), pancreatic NET3 for 4% (n:1), thyroid papillary carcinoma for 4% (n:1), and malignant melanoma for 4% (n:1). In total, 26/27 included patients had PSMA-positive brain metastases but only one patient had PSMA-negative brain metastases with ⁶⁸Ga-PSMA-11 PET/CT imaging. This patient was followed with a diagnosis of primary larynx squamous carcinoma and had a mass suspected of brain metastases. Further tests and an MRI revealed that the lesion in this patient was a hemorrhagic metastasis. The smallest metastatic focus on ⁶⁸Ga-PSMA-11 PET/CT imaging was 0.22 cm, also confirmed by MRI (range: 0.22–2.81 cm). The mean ± SD SUVmax of the BM lesions was 17.9 ± 8.6 and 6.8 ± 5.2 on ¹⁸F-FDG PET/CT and ⁶⁸Ga-PSMA-11 PET/CT imaging, respectively. Metastatic foci that could not be detected by ¹⁸F-FDG PET/CT imaging were successfully detected with ⁶⁸Ga-PSMA-11 PET/CT imaging in 11 cases (42%). The distribution and number of metastatic lesions observed on cranial MRI and ⁶⁸Ga-PSMA-11 PET/CT were compatible with each other for all patients. Immunohistochemical staining was performed in the primary tumor of 10 (38%) cases, and positive IHC staining with PSMA was detected in 5 patients. In addition, positive IHC staining with PSMA was detected in all of the four surgically excised brain metastatic tumor foci. Conclusions: In this study,⁶⁸Ga-PSMA-11 PET/CT appears to be superior to ¹⁸F-FDG in detecting BM from various tumors, largely due to its high expression associated with neovascularization and the absence of PSMA expression in normal brain parenchyma. This lack of physiological uptake in healthy brain tissue provides excellent tumor-to-background contrast, further supporting the advantage of ⁶⁸Ga-PSMA-11 over ¹⁸F-FDG for BM imaging. However, larger studies are required to confirm these findings, particularly through comparisons across tumor types and histopathological subgroups, integrating PSMA immunohistochemistry (IHC) scores with ⁶⁸Ga-PSMA-11 uptake levels. Beyond its diagnostic potential, our results may also inform PSMA-targeted therapeutic strategies, offering new perspectives for the management of patients with brain metastases from diverse primary tumors. Full article

Background: Risk assessment models are increasingly being used in oncology to improve therapeutic and follow-up decisions for individual patients. Methods: In our study, we used a university hospital registry database containing data on patients diagnosed with invasive cutaneous melanoma between 2000 and 2019 (training cohort: N = 1402; validation cohort: N = 601). Using multivariate Cox regression models, we identified clinicopathological variables that are independent risk factors for melanoma recurrence at specific sites. We then constructed nomograms to predict the probability of recurrence at 3, 5, and 10 years. Results: Age, sex, primary tumor location, histological subtype, Clark invasion level and AJCC pT category were independent prognostic factors for melanoma recurrence in regional lymph nodes. Age, sex, primary tumor location, Clark level of invasion, AJCC pT stage and regional lymph node metastasis were risk factors for skin/soft tissue (including muscle)/non-regional lymph node metastases. We found that AJCC pT category and sex were also independent prognostic factors for melanoma recurrence in the lung, visceral sites, and brain. Furthermore, the nomogram predicting recurrence in the lung and visceral sites incorporated the presence of regional lymph node and skin/soft tissue/non-regional lymph node metastases. ROC curves showed good performance of the nomograms in both the training and validation cohorts. The calibration curve showed a good fit. Conclusion: Our results support the high prognostic value of AJCC pT stage and patient sex, which remained consistent across all melanoma stages, and demonstrate the feasibility of creating nomogram models to predict recurrence risk in melanoma patients. Full article

Background and Objectives: The prognostic significance of body mass index (BMI) in metastatic HER2-positive breast cancer (BC) remains unclear, with previous studies yielding conflicting results. This multicenter real-world study aimed to investigate the prognostic role of BMI in this patient population. Materials and Methods: A total of 169 female patients with metastatic HER2-positive BC who received trastuzumab-based treatment between 2010 and 2024 were included. Patients were categorized by BMI (<30 kg/m² vs. ≥30 kg/m²). The primary endpoints were overall survival (OS) and progression-free survival (PFS). Kaplan–Meier and Cox regression analyses were performed overall and in subgroups stratified by hormone receptor (HR) status. Results: In the overall cohort, a BMI ≥ 30 was not significantly associated with OS or PFS. However, in the HR-positive/HER2-positive subgroup, BMI ≥ 30 kg/m² was linked to significantly shorter OS (p = 0.024) and PFS (p = 0.047) by Kaplan–Meier analysis. However, these associations did not remain statistically significant in multivariate analyses. No significant BMI-related differences were observed in the HR-negative subgroup. Other independent negative prognostic factors included recurrent disease, the presence of brain metastases, and a high Ki-67 index. Conclusions: BMI was not identified as an independent prognostic factor in the overall population. However, among HR-positive/HER2-positive patients, obesity was associated with poorer survival in univariate analysis, but this was not confirmed in multivariate analysis. These findings underscore the need for prospective studies to clarify the prognostic role of adiposity, considering biological subtypes. Full article

Purpose: This systematic review aims to analyze the literature on the application of AI in predicting patient outcomes and treatment-related toxicity in those undergoing SBRT or SRS across heterogeneous tumor sites. Materials and methods: Our review conformed to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. PubMed, EMBASE and Scopus were systematically searched for English-language human studies evaluating AI for outcome and toxicity prediction in patients undergoing SBRT or SRS for solid tumors. Search terms included (“Stereotactic Body Radiotherapy” OR “SBRT” OR “Stereotactic Radiosurgery” OR “SRS” OR “Stereotactic Ablative Radiotherapy” OR “SABR”) AND (“Artificial Intelligence” OR “AI” OR “Machine Learning” OR “Deep Learning” OR “Radiomics”) AND (“Response Prediction” OR “Response to Treatment” OR “Outcome Prediction”) AND (“Toxicity” OR “Side Effects” OR “Treatment Toxicities” OR “Adverse Events”). Results: The search yielded 29 eligible retrospective studies, published between 2020 and 2025. Eight studies addressed early-stage primary lung cancer, highlighting the potential of AI-based models in predicting radiation-induced pneumonitis, fibrosis and local control. Five studies investigated AI models for predicting hepatobiliary toxicity following SBRT for liver tumors. Sixteen studies involved SRS-treated patients with brain metastases or benign intracranial neoplasms (e.g., arteriovenous malformations, vestibular schwannomas, meningiomas), exploring AI algorithms for predicting treatment response and radiation-induced changes. In the results, AI might have been exploited to both reaffirm already known clinical predictors and to identify novel imaging, dosimetric or biological biomarkers. Examples include predicting radiation pneumonitis in lung cancer, residual liver function in hepatic tumors and local recurrence in brain metastases, thus supporting tailored treatment decisions. Conclusions: Combining AI with SBRT could greatly enhance personalized cancer care by predicting patient-specific outcomes and toxicity. AI models analyze complex datasets, including imaging and clinical data, to identify patterns that traditional methods may miss, thus enabling more accurate risk stratification and reducing variability in treatment planning. With further research and clinical validation, this integration could make radiotherapy safer, more effective and contribute to advancement in precision oncology. Full article

Background and Objectives: Over 30% of people who suffer from cancers are at risk of developing brain metastases. The typical recommended surgical therapy for metastases within the brain is gross total resection (GTR). Nevertheless, GTR solely may not always be adequate for disease management since remaining tumors can show local advancements and invasion. The focus of this research is to summarize the current data and to compare the outcomes of GTR and supramarginal resection. Materials and Methods: A search on the PubMed, Scopus, Cochrane Central Library, and Web of Science (WOS) databases was performed using specific keywords for single or multiple brain metastasis of any origin in patients who underwent either supramarginal resection or gross total resection. Results: The average age of the patients involved in the study spanned between 51 ± 6 years and 60.5 ± 10.1 years. Males represented 48.7% of the total population. The incidence of 1-year survival among the GTR group was 37.1%, whereas the supramarginal resection group showed an incidence of 91.3%, under the random effect model (0.551, 95% CI [0.18, 0.921]). The incidence of 2-year survival among the GTR group was 21.26%, whereas the supramarginal resection group showed an incidence of 72.46%, under the random effect model (0.380, 95% CI [0.113, 0.648]). The incidence of local recurrence among the GTR group was 57.69%, whereas the supramarginal resection group showed an incidence of 18.4%, under the random effect model (0.266, 95% CI [0.106, 0.426]). Conclusions: Supramarginal resection is a promising approach for the management of brain metastases. Full article

Background/Objectives: This study aims to evaluate the additional value of [¹⁸F]F-fluorocholine ([¹⁸F]F-FCH) PET/CT over contrast-enhanced magnetic resonance imaging (CE-MRI) in detecting the recurrence of brain metastases (BMs) after stereotactic radiosurgery (SRS) in patients with lung cancer brain metastases (LCBMs). Methods: Thirty-one patients with suspected recurrence of BM in LCBM after SRS were enrolled in this retrospective study. They underwent both [¹⁸F]F-FCH PET/CT and CE-MRI within 2 weeks. The tumor imaging parameters and clinical features were analyzed. The results of histopathology or radiographic follow-up served as the reference standard for the final diagnosis. Results: In these 31 patients, there were 54 lesions, of which 27 lesions were proven to be BM recurrence, while 27 lesions were non-recurrence. [¹⁸F]F-FCH PET/CT showed high radiotracer uptake in recurrent lesions of BM and identified 24 positive lesions (88.89% of sensitivity), while CE-MRI indicated 23 positive lesions (85.19% of sensitivity). [¹⁸F]F-FCH PET/CT indicated higher specificity (81.48%) and accuracy (85.19%) in detecting recurrence of BM than CE-MRI (40.74% and 62.96%, both p < 0.05), particularly in frontal lobes and cerebella. For lesion sizes, the accuracy of [¹⁸F]F-FCH PET/CT in detecting recurrent lesions was higher than that of CE-MRI for lesions over 1.0 cm but below 2.0 cm (p = 0.016). The detective performance of [¹⁸F]F-FCH PET/CT combined with CE-MRI was higher than [¹⁸F]F-FCH PET/CT or CE-MRI alone (all p < 0.05). Interestingly, TLC (≥4.11) was significantly correlated with poor intracranial PFS (iPFS), meaning it was a significant prognostic factor for iPFS. Conclusions: This study identified that compared with CE-MRI, [¹⁸F]F-FCH PET/CT demonstrated higher specificity and accuracy in diagnosing recurrence of BM in LCBM after SRS. Combining [¹⁸F]F-FCH PET/CT with CE-MRI has the potential to improve diagnostic performance for recurrence of BM and management of patient treatment. TLC was an independent risk factor for iPFS. Full article

Brain metastases (BMs) are the most common intracranial tumors in adults. Their heterogeneity, potential multifocality, and complex biomolecular behavior pose significant diagnostic and therapeutic challenges. Artificial intelligence (AI) has the potential to revolutionize BM diagnosis by facilitating early lesion detection, precise imaging segmentation, and non-invasive molecular characterization. Machine learning (ML) and deep learning (DL) models have shown promising results in differentiating BMs from other intracranial tumors with similar imaging characteristics—such as gliomas and primary central nervous system lymphomas (PCNSLs)—and predicting tumor features (e.g., genetic mutations) that can guide individualized and targeted therapies. Intraoperatively, AI-driven systems can enable optimal tumor resection by integrating functional brain maps into preoperative imaging, thus facilitating the identification and safeguarding of eloquent brain regions through augmented reality (AR)-assisted neuronavigation. Even postoperatively, AI can be instrumental for radiotherapy planning personalization through the optimization of dose distribution, maximizing disease control while minimizing adjacent healthy tissue damage. Applications in systemic chemo- and immunotherapy include predictive insights into treatment responses; AI can analyze genomic and radiomic features to facilitate the selection of the most suitable, patient-specific treatment regimen, especially for those whose disease demonstrates specific genetic profiles such as epidermal growth factor receptor mutations (e.g., EGFR, HER2). Moreover, AI-based prognostic models can significantly ameliorate survival and recurrence risk prediction, further contributing to follow-up strategy personalization. Despite these advancements and the promising landscape, multiple challenges—including data availability and variability, decision-making interpretability, and ethical, legal, and regulatory concerns—limit the broader implementation of AI into the everyday clinical management of BMs. Future endeavors should thus prioritize the development of generalized AI models, the combination of large and diverse datasets, and the integration of clinical and molecular data into imaging, in an effort to maximally enhance the clinical application of AI in BM care and optimize patient outcomes. Full article

Background: Distinguishing tumor recurrence from radiation necrosis after radiotherapy for brain metastases remains a major diagnostic challenge. Perfusion MRI, particularly the measurement of relative cerebral blood volume (rCBV), is a commonly used technique to differentiate between these two entities. However, variations in the placement of regions of interest (ROIs) affect diagnostic accuracy. This study compares the diagnostic performance of different cerebral perfusion methods, including a novel volumetric 3D ROI method and automatic thresholding, to differentiate tumor recurrence from radiation necrosis. Methods: We retrospectively analyzed data from 23 patients, including 25 brain metastases treated with stereotactic radiotherapy, who were suspected of local recurrence and had histological confirmation via biopsy or surgical resection. Each patient underwent perfusion MRI before surgery. The diagnostic performance of the different ROI methods (manual and 3D) was evaluated using the area under the ROC curve (AUC), as well as sensitivity and specificity measures. An automatic thresholding method was also applied, generating tumor sub-volumes with predefined cut-off values to determine the rCBV threshold most specific for differentiating relapse from necrosis. Results: The 3D ROI method, considering the whole lesion and a healthy ROI in the head of the caudate nucleus, demonstrated superior diagnostic performance (AUC = 0.65), outperforming manual methods (AUC = 0.53). Robustness was moderate, with an intraclass correlation coefficient of 0.60 between Syngo.via and IntelliSpace. Conclusions: The 3D ROI method shows promise in improving diagnostic accuracy in distinguishing tumor recurrence from radiation necrosis. Further studies with standardized protocols and larger populations are needed to validate these results. Full article