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Final ID: Poster #: SCI-082

Improving the Sensitivity and Specificity of CT to Diagnose Tracheomalacia at the Work Station

Purpose or Case Report: CT is often performed and advocated in patients with risk factors for or symptoms of tracheomalacia (TM). However, TM is traditionally defined as a 50% decrease in the cross-sectional area of the airway during a forced expiratory maneuver. This basis for detecting TBM was never meant for use in CT and leads to the under diagnosis of TM in young children by CT and typically requires inspiratory/expiratory CT (IECT). Additionally, some pictures archiving systems do not have tools to measure area. The aim of this investigation is to show that TM is under diagnosed by IECT relative to bronchoscopy and to develop a “view box” parameter to improve sensitivity while maintaining specificity in identifying the trachea as normal or affected by TM.

Methods & Materials: Patients were identified from electronic medical records that had both an IECT and bronchoscopy. The narrowest segment of the trachea was measured in the shortest transverse dimension and longest transverse dimension on both inspiratory and expiratory CT. The radiology and bronchoscopy reports were abstracted for presence and severity of reported TM.

Results: 280 patients were identified, of which 103 had TM on bronchoscopy. IECT reported TM in 20 for a sensitivity of 19.4% and specificity of 99.4%. The negative predictive value (NPV) of these clinical reads of IECT was 95% but the positive predictive value (PPV) was 68%. The ratio of anterior-posterior diameter of the normal trachea, regardless the phase of respiration, ranges from 0.8 to 1.1 (prior presentation). Using a cut-off ratio of 0.7, regardless of inspiratory phase, results in a sensitivity of 91.3% and specificity of 91.2%. The negative predictive value using this ratio is 94.5% and the positive predictive value increased to 85.8%. Using expiratory CT images alone and a cut-off ratio of 0.6, results in 93.2% sensitivity and 97.2% specificity with PPV and NPV of 95% and 96%, respectively.

Conclusions: The current clinical paradigm for identifying TM by CT has poor sensitivity and only identifies patients a small fraction of TM compared to bronchoscopy. Applying a simple ratio of two measures, short axis to long axis, acquired at the viewing station can allow us to more accurately and consistently differentiate normal tracheas from tracheas affected by TM. A ratio of 0.7 is adequately accurate if only inspiratory images, or an unknown phase of respiration, are available. Images obtained during expiration are even more accurate when a ratio of 0.6 is applied.

  • Das, Prasnjeet  ( Cincinnati Children's Hospital Medical Center , Cincinnati , Ohio , United States )
  • Thomen, Robert  ( Cincinnati Children's Hospital Medical Center , Cincinnati , Ohio , United States )
  • Halula, Sarah  ( University of Cincinnati College of Medicine , Cincinnati , Ohio , United States )
  • Woods, Jason  ( Cincinnati Children's Hospital Medical Center , Cincinnati , Ohio , United States )
  • Fleck, Robert  ( Cincinnati Children's Hospital Medical Center , Cincinnati , Ohio , United States )
Session Info:

Electronic Exhibits - Scientific

Thoracic Imaging

Scientific Exhibits - Scientific

More abstracts on this topic:
Tracheobronchomalacia on Dynamic Airway CT: Interreader Reliability

El-ali Alexander, Davis James, Otero Hansel, Biko David, Rapp Jordan

Antenatal US and MR features of Congenital High Airway Obstruction Sequence (CHAOS)

El Hawari Mohamad, Joshi Akash, Zarchan Adam, Dobbs-desilet Debbie, Ornelas Samuel

More abstracts from these authors:
Comparison of High Resolution CT to Bronchoscopy for the Diagnosis of Tracheomalacia in Children

Xia Christina, Das Prasnjeet, Thomen Robert, Woods Jason, Fleck Robert

Cardiac Magnetic Resonance Imaging Assessment of Interventricular Septal Geometry in Neonates with Bronchopulmonary Dysplasia Associated Pulmonary Hypertension

Critser Paul, Higano Nara, Kingma Paul, Fleck Robert, Lang Sean, Hirsch Russel, Taylor Michael, Woods Jason

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