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article · The Egyptian Journal of Radiology and Nuclear Medicine

Correlation between chest DW-MRI and 18F-FDG PET/CT in newly diagnosed non-small cell lung cancer (NSCLC)

2024Open accessAin Shams University

Abstract

Abstract Background PET/CT is currently the gold standard for lung cancer staging, and it is also used to identify distant and nodal metastases. High-resolution MRI can also be used to diagnose and provide morphological details about lung cancer. Standardized uptake value ‘SUV’ calculated from PET/CT gives information about tumor behavior where the SUV reflects metabolic tumor activity. Apparent diffusion coefficient ‘ADC’ calculated from DW-MRI is a quantitative imaging marker aiming to assess tumor cellularity which reflects tumor behavior. The study aimed to correlate ADC assessed by DW-MRI and metabolic activity determined by SUV max in PET/CT in local and nodal staging of newly diagnosed NSCLC. Results Our study involved twenty-one patients who were pathologically proven to be NSCLC, 19 males (90.5%) and 2 females (9.5%), with a median age of 61 years (ranging from 37 to 84 years). Among all NSCLC primary mass lesions, we observed a statistically significant inverse correlation between SUV max achieved from PET/CT and ADC max, ADC mean, and ADC min calculated from DW-MR ( r = − 0.509 and p = 0.019, r = − 0.472 and p = 0.031 and r = − 0.434 and p = 0.049 for correlation between SUV max of PET/CT and ADC max, ADC mean and ADC min of DW-MR, respectively). Additionally, we observed another statistically significant inverse correlation between SUV max achieved from PET/CT and ADC max, ADC mean, and ADC min calculated from DW-MR in NSCLC mediastinal lymph nodes ( r = − 0.699 and p = 0.011, r = − 0.58 and p = 0.048 and r = − 0.629 and p = 0.028 for correlation between SUV max of PET/CT and ADC max, ADC mean and ADC min of DW-MR, respectively). Conclusions ADC values calculated from DW-MRI might act as a new prognostic tool owing to its significant inverse correlation with SUV max achieved from PET/CT in NSCLC primary mass lesions as well as mediastinal lymph nodes.

Research topics

  • Medical Imaging Techniques and Applications
  • Radiomics and Machine Learning in Medical Imaging
  • MRI in cancer diagnosis

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DOI: 10.1186/s43055-024-01284-1

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