The techniques of CT scanning in evaluation of diffuse lung disease

Abstract

Author(s): Sahar Ahmed Mahdi*, Younis Yaqoub Obid and Israa F Jaafar

Diffuse (Interstitial) lung diseases are a diverse group of pathologies that involve the lung parenchyma and may end with respiratory failure. High resolution computed tomography has made significant progress in describing the pattern and extent of the illness. The study goal was to compare between the techniques of computed tomography used for chest imaging. A descriptive hospital-based study carried on in Baghdad medical city and Mosul General Hospital. A total number of 52 patients with suspected DILD (20 males and 32 females), their age was ranged from (5 to 88 years). The data have been collected from October 2019 to May 2020. The most used technique for diagnosing patients with suspicion of a lung disease is the HRCT technique, which has a percentage 36 (69.23%) while the spiral CT has a percentage 16 (30.77%), as a result the HRCT have twice accuracy than spiral tomography technique. The commonest pattern of diffuse lung disease is high attenuation, as it reached a percentage of 42.55%. It was discovered 13 times by HRCT and 7 times by spiral CT. Consolidation was the commonest pattern in the high attenuation pattern (21.27%). Nodular pattern accounts for 31.91% of diffuse lung disease. The most common nodular lesion is sarcoidosis (14.89%). Because to low sensitivity, specificity, and diagnostic accuracy of X-ray, HRCT scan is recommended, particularly for symptomatic patients with normal or ambiguous chest X-rays. HRCT is presently regarded as the best imaging method for diffuse lung diseases.

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Awards Nomination

Editors List

  • Prof. Elhadi Miskeen

    Obstetrics and Gynaecology Faculty of Medicine, University of Bisha, Saudi Arabia

  • Ahmed Hussien Alshewered

    University of Basrah College of Medicine, Iraq

  • Sudhakar Tummala

    Department of Electronics and Communication Engineering SRM University – AP, Andhra Pradesh

     

     

     

  • Alphonse Laya

    Supervisor of Biochemistry Lab and PhD. students of Faculty of Science, Department of Chemistry and Department of Chemis

     

  • Fava Maria Giovanna

     

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