Differentiating radiation necrosis from tumor recurrence: a systematic review and diagnostic meta-analysis comparing imaging modalities

Advanced hybrid deep learning model for enhanced evaluation of osteosarcoma histopathology images

Background

Recent advances in machine learning are transforming medical image analysis, particularly in cancer detection and classification. Techniques such as deep learning, especially convolutional neural networks (CNNs) and vision transformers (ViTs), are now enabling the precise analysis of complex histopathological images, automating detection, and enhancing classification accuracy across various cancer types. This study focuses on osteosarcoma (OS), the most common bone cancer in children and adolescents, which affects the long bones of the arms and legs. Early and accurate detection of OS is essential for improving patient outcomes and reducing mortality. However, the increasing prevalence of cancer and the demand for personalized treatments create challenges in achieving precise diagnoses and customized therapies.

Methods

We propose a novel hybrid model that combines convolutional neural networks (CNN) and vision transformers (ViT) to improve diagnostic accuracy for OS using hematoxylin and eosin (H&E) stained histopathological images. The CNN model extracts local features, while the ViT captures global patterns from histopathological images. These features are combined and classified using a Multi-Layer Perceptron (MLP) into four categories: non-tumor (NT), non-viable tumor (NVT), viable tumor (VT), and non-viable ratio (NVR).

Results

Using the Cancer Imaging Archive (TCIA) dataset, the model achieved an accuracy of 99.08%, precision of 99.10%, recall of 99.28%, and an F1-score of 99.23%. This is the first successful four-class classification using this dataset, setting a new benchmark in OS research and offering promising potential for future diagnostic advancements.

Radiomics for differentiating radiation-induced brain injury from recurrence in gliomas: systematic review, meta-analysis, and methodological quality evaluation using METRICS and RQS

OBJECTIVE

To systematically evaluate glioma radiomics literature on differentiating between radiation-induced brain injury and tumor recurrence.

METHODS

Literature was searched on PubMed and Web of Science (end date: May 7, 2024). Quality of eligible papers was assessed using METhodological RadiomICs Score (METRICS) and Radiomics Quality Score (RQS). Reliability of quality scoring tools were analyzed. Meta-analysis, meta-regression, and subgroup analysis were performed.

RESULTS

Twenty-seven papers were included in the qualitative assessment. Mean average METRICS score and RQS percentage score across three readers was 57% (SD, 14%) and 16% (SD, 12%), respectively. Score-wise inter-rater agreement for METRICS ranged from poor to excellent, while RQS demonstrated moderate to excellent agreement. Item-wise agreement was moderate for both tools. Meta-analysis of 11 eligible studies yielded an estimated area under the receiver operating characteristic curve of 0.832 (95% CI, 0.757-0.908), with significant heterogeneity (I2 = 91%) and no statistical publication bias (p = 0.051). Meta-regression did not identify potential sources of heterogeneity. Subgroup analysis revealed high heterogeneity across all subgroups, with the lowest I2 at 68% in studies with proper validation and higher quality scores. Statistical publication bias was generally not significant, except in the subgroup with the lowest heterogeneity (p = 0.044). However, most studies in both qualitative analysis (26/27; 96%) and primary meta-analysis (10/11; 91%) reported positive effects of radiomics, indicating high non-statistical publication bias.

CONCLUSION

While a good performance was noted for radiomics, results should be interpreted cautiously due to heterogeneity, publication bias, and quality issues thoroughly examined in this study.

KEY POINTS

Question Radiomic literature on distinguishing radiation-induced brain injury from glioma recurrence lacks systematic reviews and meta-analyses that assess methodological quality using radiomics-specific tools. Findings While the results are encouraging, there was substantial heterogeneity, publication bias toward positive findings, and notable concerns regarding methodological quality. Clinical relevance Meta-analysis results need cautious interpretation due to significant problems detected during the analysis (e.g., suboptimal quality, heterogeneity, bias), which may help explain why radiomics has not yet been translated into clinical practice.

Advanced Imaging in the Diagnosis and Response Assessment of High-Grade Glioma: AJR Expert Panel Narrative Review

This AJR Expert Panel Narrative Review explores the current status of advanced MRI and PET techniques for the posttherapeutic response assessment of high-grade adult-type gliomas, focusing on ongoing clinical controversies in current practice. Discussed techniques that complement conventional MRI and aid the differentiation of recurrent tumor from posttreatment effects include DWI and diffusion-tensor imaging; perfusion MRI techniques including dynamic susceptibility contrast (DSC), dynamic contrast-enhanced, and arterial spin labeling MRI; MR spectroscopy (MRS) including assessment of 2-hydroxyglutarate (2HG) concentration; glucose- and amino acid (AA)-based PET; and amide proton transfer imaging. Updated criteria for the Response Assessment in Neuro-Oncology are presented. Given the abundant supporting clinical evidence, the panel supports a recommendation that routine response assessment after high-grade glioma treatment should include perfusion MRI, particularly given the development of a consensus recommended DSC-MRI protocol. Although published studies support 2HG MRS and AA PET, these techniques' widespread adoption will likely require increased availability (for 2HG MRS) or increased insurance funding in the United States (for AA PET). The review concludes with a series of consensus opinions from the author panel, centered on the clinical integration of the advanced imaging techniques into posttreatment surveillance protocols.

Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM)

The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections-the connectome-both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.

Brain and Brain Stem Necrosis After Reirradiation for Recurrent Childhood Primary Central Nervous System Tumors: A PENTEC Comprehensive Review

PURPOSE

Reirradiation is increasingly used in children and adolescents/young adults (AYA) with recurrent primary central nervous system tumors. The Pediatric Normal Tissue Effects in the Clinic (PENTEC) reirradiation task force aimed to quantify risks of brain and brain stem necrosis after reirradiation.

METHODS AND MATERIALS

A systematic literature search using the PubMed and Cochrane databases for peer-reviewed articles from 1975 to 2021 identified 92 studies on reirradiation for recurrent tumors in children/AYA. Seventeen studies representing 449 patients who reported brain and brain stem necrosis after reirradiation contained sufficient data for analysis. While all 17 studies described techniques and doses used for reirradiation, they lacked essential details on clinically significant dose-volume metrics necessary for dose-response modeling on late effects. We, therefore, estimated incidences of necrosis with an exact 95% CI and qualitatively described data. Results from multiple studies were pooled by taking the weighted average of the reported crude rates from individual studies.

RESULTS

Treated cancers included ependymoma (n = 279 patients; 7 studies), medulloblastoma (n = 98 patients; 6 studies), any CNS tumors (n = 62 patients; 3 studies), and supratentorial high-grade gliomas (n = 10 patients; 1 study). The median interval between initial and reirradiation was 2.3 years (range, 1.2-4.75 years). The median cumulative prescription dose in equivalent dose in 2-Gy fractions (EQD22; assuming α/β value = 2 Gy) was 103.8 Gy (range, 55.8-141.3 Gy). Among 449 reirradiated children/AYA, 22 (4.9%; 95% CI, 3.1%-7.3%) developed brain necrosis and 14 (3.1%; 95% CI, 1.7%-5.2%) developed brain stem necrosis with a weighted median follow-up of 1.6 years (range, 0.5-7.4 years). The median cumulative prescription EQD22 was 111.4 Gy (range, 55.8-141.3 Gy) for development of any necrosis, 107.7 Gy (range, 55.8-141.3 Gy) for brain necrosis, and 112.1 Gy (range, 100.2-117 Gy) for brain stem necrosis. The median latent period between reirradiation and the development of necrosis was 5.7 months (range, 4.3-24 months). Though there were more events among children/AYA undergoing hypofractionated versus conventionally fractionated reirradiation, the differences were not statistically significant (P = .46).

CONCLUSIONS

Existing reports suggest that in children/AYA with recurrent brain tumors, reirradiation with a total EQD22 of about 112 Gy is associated with an approximate 5% to 7% incidence of brain/brain stem necrosis after a median follow-up of 1.6 years (with the initial course of radiation therapy being given with conventional prescription doses of ≤2 Gy per fraction and the second course with variable fractionations). We recommend a uniform approach for reporting dosimetric endpoints to derive robust predictive models of late toxicities following reirradiation.

Rational combination platform trial design for children and young adults with diffuse midline glioma: A report from PNOC

Background Diffuse midline glioma (DMG) is a devastating pediatric brain tumor unresponsive to hundreds of clinical trials. Approximately 80% of DMGs harbor H3K27M oncohistones, which reprogram the epigenome to increase the metabolic profile of the tumor cells. Methods We have previously shown preclinical efficacy of targeting both oxidative phosphorylation and glycolysis through treatment with ONC201, which activates the mitochondrial protease ClpP, and paxalisib, which inhibits PI3K/mTOR, respectively. Results ONC201 and paxalisib combination treatment aimed at inducing metabolic distress led to the design of the first DMG-specific platform trial PNOC022 (NCT05009992). Conclusions Here, we expand on the PNOC022 rationale and discuss various considerations, including liquid biome, microbiome, and genomic biomarkers, quality-of-life endpoints, and novel imaging modalities, such that we offer direction on future clinical trials in DMG.

MRI Treatment Response Assessment Maps (TRAMs) for differentiating recurrent glioblastoma from radiation necrosis

BACKGROUND

MRI treatment response assessment maps (TRAMs) were introduced to distinguish recurrent malignant glioma from therapy related changes. TRAMs are calculated with two contrast-enhanced T1-weighted sequences and reflect the "late" wash-out (or contrast clearance) and wash-in of gadolinium. Vital tumor cells are assumed to produce a wash-out because of their high turnover rate and the associated hypervascularization, whereas contrast medium slowly accumulates in scar tissue. To examine the real value of this method, we compared TRAMs with the pathology findings obtained after a second biopsy or surgery when recurrence was suspected.

METHODS

We retrospectively evaluated TRAMs in adult patients with histologically demonstrated glioblastoma, contrast-enhancing tissue and a pre-operative MRI between January 1, 2017, and December 31, 2022. Only patients with a second biopsy or surgery were evaluated. Volumes of the residual tumor, contrast clearance and contrast accumulation before the second surgery were analyzed.

RESULTS

Among 339 patients with mGBM who underwent MRI, we identified 29 repeated surgeries/biopsies in 27 patients 59 ± 12 (mean ± standard deviation) years of age. Twenty-eight biopsies were from patients with recurrent glioblastoma histology, and only one was from a patient with radiation necrosis. We volumetrically evaluated the 29 pre-surgery TRAMs. In recurrent glioblastoma, the ratio of wash-out volume to tumor volume was 36 ± 17% (range 1-73%), and the ratio of the wash-out volume to the sum of wash-out and wash-in volumes was 48 ± 21% (range 22-92%). For the one biopsy with radiation necrosis, the ratios were 42% and 54%, respectively.

CONCLUSIONS

Typical recurrent glioblastoma shows a > 20%ratio of the wash-out volume to the sum of wash-out and wash-in volumes. The one biopsy with radiation necrosis indicated that such necrosis can also produce high wash-out in individual cases. Nevertheless, the additional information provided by TRAMs increases the reliability of diagnosis.

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.

Radionecrosis mimicking pseudo‑progression in a patient with lung cancer and brain metastasis following the combination of anti‑PD‑1 therapy and stereotactic radiosurgery: A case report

Brain metastases (BMs) usually develop in patients with non-small cell lung cancer. In addition to systemic therapy, radiation therapy and surgery, anti-programmed cell death-ligand 1 (PD-L1) therapy is another promising clinical anticancer treatment modality. However, the optimal timing and drug-drug interactions of anti-PD-L1 therapy with other combined treatments remain to be elucidated. Treatment with anti-PD-L1 therapy is associated with an increased risk of radionecrosis (RN) regardless of tumor histology. The present study described a case of RN in a patient with lung adenocarcinoma and with BM who received anti-PD-L1 therapy. Before anti-PD-L1 treatment, the patient received whole brain radiotherapy. During durvalumab treatment, the intracranial metastases regressed. The progression of intracranial lesions 9 months later prompted a second-line of therapy with PD-L1 inhibitor durvalumab and stereotactic radiotherapy (SRT). Despite stereotactic irradiation, the lesions progressed further, leading to surgical resection. On examination, RN was detected, but there was no evidence of metastatic lung cancer. The aim of the present study was to present the longitudinal change in magnetic resonance imaging in RN following STR and anti-PD-L1 combined therapy. The atypical image of RN is conditionally important for making an accurate preoperative diagnosis.