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Query: UMLS:C0149925 (small cell lung cancer)
 6,491 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

We read the article entitled "Patterns of brain metastasis immediately before prophylactic cranial irradiation (PCI): implications for PCI optimization in limited-stage small cell lung cancer" with great interest. In that study, the author reported about the importance of PCI timing in limited stage small cell lung cancer (LS-SCLC) in the era of MRI surveillance. In addition, the authors raise the issue of neurotoxicity of PCI. In this letter, we aimed to clarify the value of PCI in LS-SCLC and present ongoing trials regarding PCI and MRI surveillance in SCLC. As a result, we see the need for the development of a prediction tool to estimate the risk of intracranial relapse in LS-SCLC after chemoradiotherapy in order to support shared decision making through improved guidance.
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PMID:In regards to Chu et al.: Patterns of brain metastasis immediately before prophylactic cranial irradiation (PCI): implications for PCI optimization in limited-stage small cell lung cancer. 3313 45

Machine learning (ML) and artificial intelligence (AI) are aiding in improving sensitivity and specificity of diagnostic imaging. The rapid adoption of these advanced ML algorithms is transforming imaging analysis; taking us from noninvasive detection of pathology to noninvasive precise diagnosis of the pathology by identifying whether detected abnormality is a secondary to infection, inflammation and/or neoplasm. This is led to the emergence of "Radiobiogenomics"; referring to the concept of identifying biologic (genomic, proteomic) alterations in the detected lesion. Radiobiogenomic involves image segmentation, feature extraction, and ML model to predict underlying tumor genotype and clinical outcomes. Lung cancer is the most common cause of cancer related death worldwide. There are several histologic subtypes of lung cancer, e.g., small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC) (adenocarcinoma, squamous cell carcinoma). These variable histologic subtypes not only appear different at microscopic level, but these also differ at genetic and transcription level. This intrinsic heterogeneity reveals itself as different morphologic appearances on diagnostic imaging, such as CT, PET/CT and MRI. Traditional evaluation of imaging findings of lung cancer is limited to morphologic characteristics, such as lesion size, margins, density. Radiomics takes image analysis a step further by looking at imaging phenotype with higher order statistics in efforts to quantify intralesional heterogeneity. This heterogeneity, in turn, can be potentially used to extract intralesional genomic and proteomic data. This review aims to highlight novel concepts in ML and AI and their potential applications in identifying radiobiogenomics of lung cancer.
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PMID:Radiogenomics of lung cancer. 3314 87

An 84-year-old man was admitted to our hospital with new-onset refractory status epilepticus of unclear etiology. On the third day, diffusion-weighted brain MRI demonstrated lesions in the right medial temporal and parietal lobes. As a CSF sample showed pleocytosis, paraneoplastic limbic encephalitis (PLE) associated with small cell lung cancer (SCLC) was suspected. The patient was also positive for anti-gamma aminobutyric acid (GABA)B receptor antibody in the CSF, which has recently been reported in elderly patients with SCLC-related PLE. Methylprednisolone pulse therapy ameliorated the symptoms. It is noteworthy that immune therapy often improves the symptoms of PLE with anti-GABAB receptor antibody, even though radical therapy for the lung cancer may be difficult.
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PMID:[Paraneoplastic anti-gamma aminobutyric acid (GABA)B receptor antibody limbic encephalitis associated with small cell lung cancer presenting as new-onset status epilepticus: a case report]. 3322 37


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