title: PATTERN OF INTERSTITIAL LUNG DISEASE AS SEEN BY HIGH RESOLUTION COMPUTERISED TOMOGRAPHY.
abstract: BACKGROUND
  Diffuse lung diseases constitute a major cause of morbidity and mortality worldwide. High Resolution Computed Tomography (HRCT) is the recommended imaging technique in the diagnosis, assessment and followup of these diseases.
  
  
  OBJECTIVE
  To describe the pattern of HRCT findings in patients with suspected interstitial lung disease.
  
  
  METHODS
  Kenyatta National Hospital (KNH), Nairobi Hospital and MP Shah Hospital; all situated in Nairobi, during the period February to August 2010.
  
  
  METHODS
  One hundred and one patients sent for HRCT in the six month study period.
  
  
  RESULTS
  A total of 101 patients were recruited with age range 18 to 100 years, with a mean age of 53.6 (SD 19.7) years and a median age of 54 years. The male-female ratio was 1.2:1. Cough [80.2% (n = 81)] was the most common presenting complaint followed by dyspnoea (53.5%, n = 53) and chest pain [24.8% (n = 25)]. Overall, the predominant pattern of involvement on chest HRCT was reticular pattern seen in 56.1% (n = 82) of patients, followed by honey-comb pattern (37.8%, n = 82).
  
  
  CONCLUSIONS
  The study demonstrated marked lung parenchymal destruction in most cases; a poor prognostic indicator which could have been due to delayed referral. HRCT has a high pick up rate of subtle parenchymal lung lesions as well as defining the lesions and their distribution compared to plain chest radiography. This is important in narrowing the differential diagnosis as well as for pre-biopsy planning. The diagnosis of ILD requires a multidisciplinary approach including a detailed clinical history, physical findings, and laboratory investigations, radiological and histological assessment.
authors: Department of Diagnostic Imaging and Radiation Medicine, College of Health Sciences, University of Nairobi, Kenya.
authors: C K
authors: CK
authors: Onyambu
authors: M N
authors: MN
authors: Waigwa
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001706:Biopsy; D005260:Female; D006785:Hospitals, University; D006801:Humans; D007630:Kenya; D017563:Lung Diseases, Interstitial / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D014057:Tomography, X-Ray Computed / Q000379:methods