International Journal of Anatomy Radiology and Surgery (Jan 2022)

Utility of Maximum Intensity Projections in Volumetric High Resolution Computed Tomography Lung in the Evaluation of Diffuse Lung Diseases- A Retrospective Analysis

  • Joish Upendra Kumar,
  • Harikiran Reddy,
  • S Abhishek

DOI
https://doi.org/10.7860/IJARS/2022/50217.2727
Journal volume & issue
Vol. 11, no. 01
pp. 09 – 12

Abstract

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Introduction: Though volumetric High Resolution Computed Tomography (HRCT) has increased the sensitivity of diagnosing diffuse lung diseases, there are some drawbacks related with lesion detection. Post processing techniques like Maximum Intensity Projection (MIP) can help in increasing the sensitivity of HRCT further. Aim: To study various possible utilities of MIP in HRCT lung. Materials and Methods: A retrospective cross-sectional study was done in a tertiary care hospital, including all Computed Tomography (CT) scans performed in July 2020 to August 2020, with multiple lung findings and diffuse involvement of lungs. Two radiologists reviewed the base mean axial images of 1 mm and MIP images in sliding scale from 2 to 10 mm in lung window. They recorded the findings in every scan based on widely accepted basic pattern of interpretation of HRCT thorax. The slice/slab thickness that best depicted each finding was noted. Inter reader agreement was calculated for each finding. Results: Fifty nine CT cases, which included scans of 34 males and 25 female patients with a mean age of 37.4±12.5 years were reviewed. There was near perfect to substantial agreement between the two radiologists on various findings (kappa >0.75). MIP images of 6-10 mm slab thickness were best suited to detect smaller nodules, assess vessel size in areas of mosaic attenuation and detect dense lesions in images with poor breath hold. The MIP images of 2-5 mm thickness were useful in detecting the location in relation to secondary pulmonary lobule, reticular densities and crazy-paving densities. Conclusion: The MIP being an easy to use and readily available post processing technique, when used with volumetric HRCT dataset of thorax enhanced the value of HRCT in detecting various lesions.

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