title: [Endobronchial ultrasonography (EBUS) for evaluation of the depth of invasion of central type early lung cancer].
abstract: It may be essential for taking appropriate therapeutic decisions in cases with early central-type lung cancer, to know the depth of tumor invasion of the bronchial wall at the laminar level. When a tumor penetrates the cartilaginous layer, photodynamic therapy (PDT) may no longer effective. For optimal therapeutic outcome, the physicians should know accurately whether or not the lesion has invaded the cartilaginous layer. Endobronchial ultrasonography (EBUS) is the sole tool available currently for depicting the laminar structure of the bronchial wall in clinical use. But mastery is required for judging the extent of tumor invasion of the bronchial wall from the ultrasonogram. Even experienced interpreters have to depend on their subjective judgment. We employed image analysis software to digitize the EBUS image. This allowed us to draw a plot of the EBUS data from the bronchial wall and perform statistical analysis for an objective assessment. In this study, we examined the ultrasound images of the bronchial wall structure using 20 MHz and 30 MHz transducers. The results showed that the 30 MHz transducer was significantly more useful for delineating the bronchial wall layers than the 20 MHz probe. Our image analysis is an objective evaluation, and any examiner should arrive at the same results.
authors.affiliation: Department of Thoracic Surgery, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
authors.forename: Chiaki
authors.initials: C
authors.lastname: Endo
mesh_terms: D001980:Bronchi / Q000000981:diagnostic imaging* / Q000473:pathology; D001999:Bronchoscopy; D019160:Endosonography / Q000379:methods / Q000592:standards*; D005069:Evaluation Studies as Topic; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging; D012680:Sensitivity and Specificity; D012984:Software