PURPOSE: To prospectively compare maximum intensity projection (MIP) and volume rendering (VR) of multidetector computed tomographic (CT) data for the detection of small intrapulmonary nodules. MATERIALS AND METHODS: This institutional review board-approved prospective study included 20 oncology patients (eight women and 12 men; mean age, 56 years +/- 16 [standard deviation]) who underwent clinically indicated standard-dose thoracic multidetector CT and provided informed consent. Transverse thin slabs of the chest (thickness, 7 mm; reconstruction increment, 3.5 mm) were created by using MIP and VR techniques to reconstruct CT data (collimation, 16 x 0.75 mm) and were reviewed in interactive cine mode. Mean, minimum, and maximum reading time per examination and per radiologist was documented. Three radiologists digitally annotated all nodules seen in a way that clearly determined their locations. The maximum number of nodules detected by the three observers and confirmed by consensus served as the reference standard. Descriptive statistics were calculated, with P < .05 indicating a significant difference. The Wilcoxon matched-pairs signed rank test and confidence intervals for differences between methods were used to compare the sensitivities of the two methods. RESULTS: VR performed significantly better than MIP with regard to both detection rate (P < .001) and reporting time (P < .001). The superiority of VR was significant for all three observers and for nodules smaller than 11 mm in diameter and was pronounced for perihilar nodules (P = .023). Sensitivities achieved with VR ranged from 76.5% to 97.3%, depending on nodule size. CONCLUSION: VR is the superior reading method compared with MIP for the detection of small solid intrapulmonary nodules.
PURPOSE: To prospectively compare maximum intensity projection (MIP) and volume rendering (VR) of multidetector computed tomographic (CT) data for the detection of small intrapulmonary nodules. MATERIALS AND METHODS: This institutional review board-approved prospective study included 20 oncology patients (eight women and 12 men; mean age, 56 years +/- 16 [standard deviation]) who underwent clinically indicated standard-dose thoracic multidetector CT and provided informed consent. Transverse thin slabs of the chest (thickness, 7 mm; reconstruction increment, 3.5 mm) were created by using MIP and VR techniques to reconstruct CT data (collimation, 16 x 0.75 mm) and were reviewed in interactive cine mode. Mean, minimum, and maximum reading time per examination and per radiologist was documented. Three radiologists digitally annotated all nodules seen in a way that clearly determined their locations. The maximum number of nodules detected by the three observers and confirmed by consensus served as the reference standard. Descriptive statistics were calculated, with P < .05 indicating a significant difference. The Wilcoxon matched-pairs signed rank test and confidence intervals for differences between methods were used to compare the sensitivities of the two methods. RESULTS: VR performed significantly better than MIP with regard to both detection rate (P < .001) and reporting time (P < .001). The superiority of VR was significant for all three observers and for nodules smaller than 11 mm in diameter and was pronounced for perihilar nodules (P = .023). Sensitivities achieved with VR ranged from 76.5% to 97.3%, depending on nodule size. CONCLUSION: VR is the superior reading method compared with MIP for the detection of small solid intrapulmonary nodules.
Authors: Savvas Andronikou; Benjamin Irving; Linda Tebogo Hlabangana; Tanyia Pillay; Paul Taylor; Pierre Goussard; Robert Gie Journal: Pediatr Radiol Date: 2013-02-16
Authors: Adriana C Gamboa; Cecilia G Ethun; Jeffrey M Switchenko; Joseph Lipscomb; George A Poultsides; Valerie Grignol; J Harrison Howard; T Clark Gamblin; Kevin K Roggin; Konstantinos Votanopoulos; Ryan C Fields; Shishir K Maithel; Keith A Delman; Kenneth Cardona Journal: J Am Coll Surg Date: 2019-08-01 Impact factor: 6.113
Authors: Douglas E Wood; Ella A Kazerooni; Scott L Baum; George A Eapen; David S Ettinger; Lifang Hou; David M Jackman; Donald Klippenstein; Rohit Kumar; Rudy P Lackner; Lorriana E Leard; Inga T Lennes; Ann N C Leung; Samir S Makani; Pierre P Massion; Peter Mazzone; Robert E Merritt; Bryan F Meyers; David E Midthun; Sudhakar Pipavath; Christie Pratt; Chakravarthy Reddy; Mary E Reid; Arnold J Rotter; Peter B Sachs; Matthew B Schabath; Mark L Schiebler; Betty C Tong; William D Travis; Benjamin Wei; Stephen C Yang; Kristina M Gregory; Miranda Hughes Journal: J Natl Compr Canc Netw Date: 2018-04 Impact factor: 11.908