ArticleFrontiers in oncology2022
Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Evaluation of PD-L1 Expression in Patients With Non-Small Cell Lung Cancer Using DCE-MRI Quantitative Analysis.The clinical respiratory journal · 2025Article
- Machine learning model for preoperative classification of stromal subtypes in salivary gland pleomorphic adenoma based on ultrasound histogram analysis.BMC oral health · 2025Article
- Histogram analysis based on intravoxel incoherent motion diffusion-weighted imaging for determining the perineural invasion status of rectal cancer.Quantitative imaging in medicine and surgery · 2024Article
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11 authors.
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Abstract
Background: Whole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions. Purpose: To compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis. Methods: Fifty-nine patients with solitary pulmonary lesions underwent multiple Results: The ADC Conclusions: Whole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and
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