A novel, integrated PET-guided MRS technique resulting in more accurate initial diagnosis of high-grade glioma

The Utility of Prostate-Specific Membrane Antigen-11 PET in Detection and Management of Central Nervous System Neoplasms

ABSTRACT

We present a case series of 5 patients diagnosed with schwannoma and 1 patient diagnosed with astrocytoma who underwent PSMA PET imaging for tumor detection. We retrospectively analyzed the records of 4 male and 2 female patients (mean age, 53.2 ± 13.2) who underwent PSMA PET imaging between March and September 2023. PET interpretation showed increased Ga-PSMA-11 accumulation in all patients with a mean SUV max of 3.11 ± 1.8. This series underscores PSMA PET's potential for CNS neoplasm detection.

Preoperative 11 C-Methionine PET-MRI in Pediatric Infratentorial Tumors

PURPOSE

MRI is the main imaging modality for pediatric brain tumors, but amino acid PET can provide additional information. Simultaneous PET-MRI acquisition allows to fully assess the tumor and lower the radiation exposure. Although symptomatic posterior fossa tumors are typically resected, the patient management is evolving and will benefit from an improved preoperative tumor characterization. We aimed to explore, in children with newly diagnosed posterior fossa tumor, the complementarity of the information provided by amino acid PET and MRI parameters and the correlation to histopathological results.

PATIENTS AND METHODS

Children with a newly diagnosed posterior fossa tumor prospectively underwent a preoperative 11 C-methionine (MET) PET-MRI. Images were assessed visually and semiquantitatively. Using correlation, minimum apparent diffusion coefficient (ADC min ) and contrast enhancement were compared with MET SUV max . The diameter of the enhancing lesions was compared with metabolic tumoral volume. Lesions were classified according to the 2021 World Health Organization (WHO) classification.

RESULTS

Ten children were included 4 pilocytic astrocytomas, 2 medulloblastomas, 1 ganglioglioma, 1 central nervous system embryonal tumor, and 1 schwannoma. All lesions showed visually increased MET uptake. A negative moderate correlation was found between ADC min and SUV max values ( r = -0.39). Mean SUV max was 3.8 (range, 3.3-4.2) in WHO grade 4 versus 2.5 (range, 1.7-3.0) in WHO grade 1 lesions. A positive moderate correlation was found between metabolic tumoral volume and diameter values ( r = 0.34). There was no correlation between SUV max and contrast enhancement intensity ( r = -0.15).

CONCLUSIONS

Preoperative 11 C-MET PET and MRI could provide complementary information to characterize pediatric infratentorial tumors.

Revolutionizing tumor detection and classification in multimodality imaging based on deep learning approaches: Methods, applications and limitations

BACKGROUND

The emergence of deep learning (DL) techniques has revolutionized tumor detection and classification in medical imaging, with multimodal medical imaging (MMI) gaining recognition for its precision in diagnosis, treatment, and progression tracking.

OBJECTIVE

This review comprehensively examines DL methods in transforming tumor detection and classification across MMI modalities, aiming to provide insights into advancements, limitations, and key challenges for further progress.

METHODS

Systematic literature analysis identifies DL studies for tumor detection and classification, outlining methodologies including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their variants. Integration of multimodality imaging enhances accuracy and robustness.

RESULTS

Recent advancements in DL-based MMI evaluation methods are surveyed, focusing on tumor detection and classification tasks. Various DL approaches, including CNNs, YOLO, Siamese Networks, Fusion-Based Models, Attention-Based Models, and Generative Adversarial Networks, are discussed with emphasis on PET-MRI, PET-CT, and SPECT-CT.

FUTURE DIRECTIONS

The review outlines emerging trends and future directions in DL-based tumor analysis, aiming to guide researchers and clinicians toward more effective diagnosis and prognosis. Continued innovation and collaboration are stressed in this rapidly evolving domain.

CONCLUSION

Conclusions drawn from literature analysis underscore the efficacy of DL approaches in tumor detection and classification, highlighting their potential to address challenges in MMI analysis and their implications for clinical practice.

Multiparametric Characterization of Intracranial Gliomas Using Dynamic [18F]FET-PET and Magnetic Resonance Spectroscopy

Both static and dynamic O-(2-[18F]fluoroethyl)-l-tyrosine-(FET)-PET and 1H magnetic resonance spectroscopy (MRS) are useful tools for grading and prognostication in gliomas. However, little is known about the potential of multimodal imaging comprising both procedures. We therefore acquired NAA/Cr and Cho/Cr ratios in multi-voxel MRS as well as FET-PET parameters in 67 glioma patients and determined multiparametric parameter combinations. Using receiver operating characteristics, differentiation between low-grade and high-grade glioma was possible by static FET-PET (area under the curve (AUC) 0.86, p = 0.001), time-to-peak (TTP; AUC 0.79, p = 0.049), and using the Cho/Cr ratio (AUC 0.72, p = 0.039), while the multimodal analysis led to improved discrimination with an AUC of 0.97 (p = 0.001). In order to distinguish glioblastoma from non-glioblastoma, MRS (NAA/Cr ratio, AUC 0.66, p = 0.031), and dynamic FET-PET (AUC 0.88, p = 0.001) were superior to static FET imaging. The multimodal analysis increased the accuracy with an AUC of 0.97 (p < 0.001). In the survival analysis, PET parameters, but not spectroscopy, were significantly correlated with overall survival (OS, static PET p = 0.014, TTP p = 0.012), still, the multiparametric analysis, including MRS, was also useful for the prediction of OS (p = 0.002). In conclusion, FET-PET and MRS provide complementary information to better characterize gliomas before therapy, which is particularly interesting with respect to the increasing use of hybrid PET/MRI for brain tumors.

What is the advance of extent of resection in glioblastoma surgical treatment-a systematic review

Glioblastoma multiform (GBM) is the most common malignant brain tumor characterized by poor prognosis, increased invasiveness, and high relapse rates. The relative survival estimates are quite low in spite of the standard treatment for GBM in recent years. Now, it has been gradually accepted that the amount of tumor mass removed correlates with longer survival rates. Although new technique advances allowing intraoperative analysis of tumor and normal brain tissue and functional paradigms based on stimulation techniques to map eloquent areas have been used for GBM resection, visual identification of tumor margins still remains a challenge for neurosurgeons. This article attempts to review and summarize the evolution of surgical resection for glioblastomas.

Multiparametric Evaluation in Differentiating Glioma Recurrence from Treatment-Induced Necrosis Using Simultaneous 18F-FDG-PET/MRI: A Single-Institution Retrospective Study

BACKGROUND AND PURPOSE

Differentiating glioma recurrence from treatment-induced necrosis can be a challenge on conventional imaging. This study aimed to assess the diagnostic performance of each functional MR imaging and PET parameter derived by using simultaneous FDG-PET/MR imaging individually and in combination in the evaluation of suspected glioma recurrence.

MATERIALS AND METHODS

Thirty-five treated glioma patients with 41 enhancing lesions (World Health Organization grade II = 9, III = 13, IV = 19) on MR imaging after an operation followed by radiation therapy and/or chemotherapy formed part of this study. Using PET/MR imaging, we calculated the normalized mean relative CBV, mean ADC, Cho/Cr, and maximum and mean target-to-background ratios. Statistical analysis was performed to determine the diagnostic performance of each parameter by receiver operating characteristic analysis individually and in combination with multivariate receiver operating characteristic analysis for the detection of glioma recurrence. Histopathology or clinicoradiologic follow-up was considered the criterion standard.

RESULTS

Of 35 patients, 25 (30 lesions) were classified as having a recurrence and 10 (11 lesions) patients as having treatment-induced necrosis. Parameters like rCBV_mean (mean relative CBV), ADC_mean, Cho/Cr, and maximum and mean target-to-background ratios were statistically significant in the detection of recurrent lesions with an accuracy of 77.5%, 78.0%, 90.9%, 87.8%, and 87.8%, respectively. On multivariate receiver operating characteristic analysis, the combination of all 3 MR imaging parameters resulted in an area under the curve of 0.913 ± 0.053. Furthermore, an area under the curve of 0.935 ± 0.046 was obtained when MR imaging parameters (ADC_mean and Cho/Cr) were combined with the PET parameter (mean target-to-background ratio), demonstrating an increase in diagnostic accuracy.

CONCLUSIONS

Simultaneous PET/MR imaging with FDG offers correlative and synergistic multiparametric assessment of glioma recurrence with increased accuracy and clinical utility.

A comprehensive approach in high-grade glioma management: position statement from the Neuro-Oncology Scientific Club (NOSC), Shiraz, Iran

Establishing a robust teamwork model in the practice of neuro-oncology requires continued interdisciplinary efforts. The Neuro-Oncology Scientific Club (NOSC) initiative is an interdisciplinary clinical forum promoting the comprehensive approach across involved disciplines in the management of central nervous system (CNS) malignancies. With its provincial founding panels and national steering board, NOSC has been operational in Iran since 2011. This initiative has pursued its mission through interval strategic meetings, tumor boards, case discussions as well as publishing neuro-oncology updates, case study periodicals, and newsletters. A provincial meeting of NOSC in Shiraz put together insights from international practice guidelines, emerging evidence, and expert opinions to draw a position statement on high-grade glioma management in adults. The present report summarizes key highlights from the above clinical forum.

PET/MRI: Multiparametric imaging of brain tumors

A combination of morphological imaging of the brain with microstructural and functional imaging provides a comprehensive overview of the properties of individual tissues. While diffusion weighted imaging provides information about tissue cellularity, spectroscopic imaging allows us to evaluate the integrity of neurons and possible anaerobic glycolysis during tumor hypoxia, in addition to the presence of accelerated synthesis or degradation of cellular membranes; on the other hand, PET metabolic imaging is used to evaluate major metabolic pathways, determining the overall extent of the tumor (¹⁸F-FET, ¹⁸F-FDOPA, ¹⁸F-FCH) or the degree of differentiation (¹⁸F-FDG, ¹⁸F-FLT, ¹⁸F-FDOPA and ¹⁸F-FET). Multi-parameter analysis of tissue characteristics and determination of the phenotype of the tumor tissue is a natural advantage of PET/MRI scanning. The disadvantages are higher cost and limited availability in all centers with neuro-oncology surgery. PET/MRI scanning of brain tumors is one of the most promising indications since the earliest experiments with integrated PET/MRI imaging systems, and along with hybrid imaging of neurodegenerative diseases, represent a new direction in the development of neuroradiology on the path towards comprehensive imaging at the molecular level.