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Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...

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Advances in diffuse glial tumors diagnosis.

Luis Filipe de Souza Godoy1,2, Vitor Ribeiro Paes3,4, Aline Sgnolf Ayres2

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Advances in diffuse glioma diagnosis leverage new technologies and the 2021 WHO classification. Multidisciplinary approaches integrating pathology, molecular data, and advanced imaging improve patient outcomes.

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Area of Science:

  • Neuro-oncology
  • Pathology
  • Radiology

Background:

  • Diffuse gliomas require precise diagnosis for effective treatment.
  • Recent technological integration has significantly advanced understanding of glioma biology and classification.
  • The 2021 fifth edition of the WHO classification of CNS tumors reflects these diagnostic improvements.

Approach:

  • This review explores diagnostic advancements within a multidisciplinary framework, focusing on the latest WHO classification.
  • It examines morphologic pathology, molecular/genetic techniques (immunohistochemistry, genetic sequencing, methylation profiling), and their correlation with neuroimaging radiophenotypes.
  • The review also covers the utility of tractography, functional neuroimaging, perfusion MRI, spectroscopy, and nuclear medicine for surgical planning and distinguishing tumor progression from treatment effects.

Key Points:

  • Morphologic pathology and molecular/genetic techniques are pivotal for accurate diffuse glioma diagnosis.
  • Correlation between neuroimaging radiophenotypes and glioma pathology/genetics is crucial.
  • Advanced imaging techniques aid in surgical planning and differentiating tumor progression from treatment-related changes.
  • Emerging technologies like AI, radiomics, and radiogenomics show promise for future glioma diagnosis.

Conclusions:

  • Evolving diagnostic techniques offer advantages but also face limitations in availability and utilization.
  • Multidisciplinary collaboration is essential for translating diagnostic advancements into improved patient survival and quality of life for glioma patients.
  • The integration of novel technologies promises to revolutionize diffuse glioma diagnosis and management.