Anatomic imaging procedures (computed tomography [CT] and magnetic resonance imaging [MRI]) have become essential tools for brain tumor assessment. Functional images (positron emission tomography [PET] and single-photon emission computed tomography [SPECT]) can provide additional information useful during the diagnostic workup to determine the degree of malignancy and as a substitute or guide for biopsy. After surgery and/or radiotherapy, nuclear medicine examinations are essential to assess persistence of tumor, to differentiate recurrence from radiation necrosis and gliosis, and to monitor the disease. The combination of functional images with anatomic ones is of the utmost importance for a full evaluation of these patients, which can be obtained by means of imaging fusion. Despite the fast-growing diffusion of PET, in most cases of brain tumors, SPECT studies are adequate and provide results that parallel those obtained with PET. The main limitation of SPECT imaging with brain tumor-seeking radiopharmaceuticals is the lack of precise anatomic details; this drawback is overcome by the fusion with morphological studies that provide an anatomic map to scintigraphic data. In the past, software-based fusion of independently performed SPECT and CT or MRI demonstrated usefulness for brain tumor assessment, but this process is often time consuming and not practical for everyday nuclear medicine studies. The recent development of dual-modality integrated imaging systems, which allow the acquisition of SPECT and CT images in the same scanning session, and their co-registration by means of the hardware, has facilitated this process. In SPECT studies of brain tumors with various radiopharmaceuticals, fused images are helpful in providing the precise localization of neoplastic lesions, and in excluding the disease in sites of physiologic tracer uptake. This information is useful for optimizing diagnosis, therapy monitoring, and radiotherapy treatment planning, with a positive impact on patient management.
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http://dx.doi.org/10.1053/j.semnuclmed.2006.08.003 | DOI Listing |
Mol Biol Rep
January 2025
Institute of Pathogenic Biology, Guilin Medical University, Guilin, 541199, China.
Cyclin-dependent kinase 5 (CDK5), a unique member of the CDK family, is a proline-directed serine/threonine protein kinase with critical roles in various physiological and pathological processes. Widely expressed in the central nervous system, CDK5 is strongly implicated in neurological diseases. Beyond its neurological roles, CDK5 is involved in metabolic disorders, psychiatric conditions, and tumor progression, contributing to processes such as proliferation, migration, immune evasion, genomic stability, and angiogenesis.
View Article and Find Full Text PDFElectromagn Biol Med
January 2025
Department of Computer Applications, Kalasalingam Academy of Research and Education - Deemed to be University, Krishnankoil, India.
Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central nervous system. In contrast, healthy tumors typically develop slowly and do not invade surrounding tissues.
View Article and Find Full Text PDFElife
January 2025
Department of Neurology, Weill Institute for Neuroscience, University of California San Francisco, San Francisco, United States.
Mutations in Sonic Hedgehog (SHH) signaling pathway genes, for example, (SUFU), drive granule neuron precursors (GNP) to form medulloblastomas (MB). However, how different molecular lesions in the Shh pathway drive transformation is frequently unclear, and mutations in the cerebellum seem distinct. In this study, we show that fibroblast growth factor 5 (FGF5) signaling is integral for many infantile MB cases and that expression is uniquely upregulated in infantile MB tumors.
View Article and Find Full Text PDFPediatr Blood Cancer
January 2025
The Hospital for Sick Children, University of Toronto, Toronto, Canada.
Introduction: Medulloblastoma (MB) is the most common malignant childhood brain tumor. Molecular subgrouping of MB has become a major determinant of management in high-income countries. Subgrouping is still very limited in low- and middle-income countries (LMICs), and its relevance to management with the incorporation of risk stratification (low risk, standard risk, high risk, and very high risk) has yet to be evaluated in this setting.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Objective: To develop a machine learning-based clinical and/or radiomics model for predicting the primary site of brain metastases using multiparametric magnetic resonance imaging (MRI).
Materials And Methods: A total of 202 patients (87 males, 115 females) with 439 brain metastases were retrospectively included, divided into training sets (brain metastases of lung cancer [BMLC] = 194, brain metastases of breast cancer [BMBC] = 108, brain metastases of gastrointestinal tumor [BMGiT] = 48) and test sets (BMLC = 50, BMBC = 27, BMGiT = 12). A total of 3,404 quantitative image features were obtained through semi-automatic segmentation from MRI images (T1WI, T2WI, FLAIR, and T1-CE).
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