OBJECTIVES: Accurate @entity5 localization and negative resection margins are necessary for successful segmentectomy. In this study, we evaluate a newly developed software package that permits @entity358 , allowing 3-dimensional assessment of @entity5 size, location, and estimates of surgical margins. METHODS: A pilot study using a newly developed 3-dimensional computed tomography analytic software package was performed to retrospectively evaluate preoperative computed tomography images of @entity1 who underwent segmentectomy (n  =  36) or lobectomy (n  =  15) for stage 1 @entity1149 . The software accomplishes an automated reconstruction of anatomic pulmonary segments of the lung based on bronchial arborization. Estimates of anticipated surgical margins and @entity358 were made on the basis of 3-dimensional reconstruction. RESULTS: Autosegmentation was achieved in 72.7% (32/44) of preoperative computed tomography images with slice thicknesses of 3  mm or less. Reasons for segmentation failure included local severe @entity2415 or @entity55 , and lower computed tomography resolution. @entity5 segmental localization was achieved in all autosegmented studies. The 3-dimensional computed tomography analysis provided a positive predictive value of 87% in predicting a marginal clearance greater than 1  cm and a 75% positive predictive value in predicting a margin to @entity5 diameter ratio greater than 1 in relation to the surgical pathology assessment. CONCLUSIONS: This preoperative 3-dimensional computed tomography analysis of segmental anatomy can confirm the @entity5 location within an anatomic segment and aid in predicting surgical margins. This 3-dimensional computed tomography information may assist in the preoperative assessment regarding the suitability of segmentectomy for @entity2 .

Preoperative (3-dimensional) computed tomography lung reconstruction before anatomic segmentectomy or lobectomy for stage I XXXX .

@entity1 :: ('9606', 'Species') :: ['patients'] @entity55 :: ('MESH:D011014', 'Disease') :: ['pneumonitis'] @entity5 :: ('MESH:D009369', 'Disease') :: ['tumor', 'cancer', 'Tumor'] @entity1149 :: ('MESH:D002289', 'Disease') :: ['non-small cell lung cancer'] @entity2 :: ('MESH:D008175', 'Disease') :: ['peripheral lung cancers'] @entity2415 :: ('MESH:D004646', 'Disease') :: ['emphysema'] @entity358 :: ('MESH:D008171', 'Disease') :: ['automated segmentation of the pulmonary parenchyma', 'pulmonary segmental volume']
@entity1149 :: (MESH:D002289,Disease) :: ['non-small cell lung cancer']
