OBJECTIVE: The purpose of our study was to evaluate the reliability of software-calculated doubling times for discerning malignant versus benign nodules. MATERIALS AND METHODS: CT lung analysis volumetric software was used to retrospectively calculate the doubling times of 63 solid noncalcified nodules by comparing nodule volumes on baseline and follow-up CT scans obtained a median of 3.7 months apart. A final diagnosis based on validated criteria was available for all 63 nodules. All CT examinations were performed with 1.25-mm-thick slices on a four-detector unit. Taking 500 days as the upper value for malignancies, we evaluated whether the software-calculated doubling times could be used to distinguish malignant from benign solid nodules. We also examined whether the relative volume variation of benign nodules correlated with initial nodule size, interscan interval, or differences in contrast administration or exposure parameters between baseline and follow-up CT. RESULTS: There were 52 benign and 11 malignant nodules. Benign nodules had a median doubling time of 947 days and a mean relative volume variation of -4.4% (range, -50% to 38%). Malignant nodules had a median doubling time of 117 days and a mean relative volume variation of 102% (22-462%). The sensitivity, specificity, and negative and positive predictive values of the volumetric software for diagnosing malignancy were 91% (95% confidence interval [CI], 0.59-1.00), 90% (95% CI, 0.79-0.97), 98% (95% CI, 0.89-1.00), and 67% (95% CI, 0.38-0.88), respectively. No correlation was found between the relative volume variation of benign nodules and their initial size, the interscan interval, or differences in contrast administration or exposure parameters between the two CT examinations. CONCLUSION: Software-calculated pulmonary nodule doubling times of more than 500 days have a 98% negative predictive value for the diagnosis of solid malignant pulmonary nodules. This method may be useful for diagnosing malignant pulmonary nodules on follow-up CT.
OBJECTIVE: The purpose of our study was to evaluate the reliability of software-calculated doubling times for discerning malignant versus benign nodules. MATERIALS AND METHODS: CT lung analysis volumetric software was used to retrospectively calculate the doubling times of 63 solid noncalcified nodules by comparing nodule volumes on baseline and follow-up CT scans obtained a median of 3.7 months apart. A final diagnosis based on validated criteria was available for all 63 nodules. All CT examinations were performed with 1.25-mm-thick slices on a four-detector unit. Taking 500 days as the upper value for malignancies, we evaluated whether the software-calculated doubling times could be used to distinguish malignant from benign solid nodules. We also examined whether the relative volume variation of benign nodules correlated with initial nodule size, interscan interval, or differences in contrast administration or exposure parameters between baseline and follow-up CT. RESULTS: There were 52 benign and 11 malignant nodules. Benign nodules had a median doubling time of 947 days and a mean relative volume variation of -4.4% (range, -50% to 38%). Malignant nodules had a median doubling time of 117 days and a mean relative volume variation of 102% (22-462%). The sensitivity, specificity, and negative and positive predictive values of the volumetric software for diagnosing malignancy were 91% (95% confidence interval [CI], 0.59-1.00), 90% (95% CI, 0.79-0.97), 98% (95% CI, 0.89-1.00), and 67% (95% CI, 0.38-0.88), respectively. No correlation was found between the relative volume variation of benign nodules and their initial size, the interscan interval, or differences in contrast administration or exposure parameters between the two CT examinations. CONCLUSION: Software-calculated pulmonary nodule doubling times of more than 500 days have a 98% negative predictive value for the diagnosis of solid malignant pulmonary nodules. This method may be useful for diagnosing malignant pulmonary nodules on follow-up CT.
Authors: Michael M Slattery; Claire Foley; Dermot Kenny; Richard W Costello; P Mark Logan; Michael J Lee Journal: Eur Radiol Date: 2012-04-27 Impact factor: 5.315
Authors: Anthony P Reeves; Alberto M Biancardi; Tatiyana V Apanasovich; Charles R Meyer; Heber MacMahon; Edwin J R van Beek; Ella A Kazerooni; David Yankelevitz; Michael F McNitt-Gray; Geoffrey McLennan; Samuel G Armato; Claudia I Henschke; Denise R Aberle; Barbara Y Croft; Laurence P Clarke Journal: Acad Radiol Date: 2007-12 Impact factor: 3.173
Authors: M F Rinaldi; T Bartalena; L Braccaioli; N Sverzellati; S Mattioli; E Rimondi; G Rossi; M Zompatori; G Battista; R Canini Journal: Radiol Med Date: 2010-01-15 Impact factor: 3.469