TY - JOUR
T1 - Computer-aided detection of peripheral lung cancers missed at CT
T2 - ROC analyses without and with localization
AU - Li, Feng
AU - Arimura, Hidetaka
AU - Suzuki, Kenji
AU - Shiraishi, Junji
AU - Li, Qiang
AU - Abe, Hiroyuki
AU - Engelmann, Roger
AU - Sone, Shusuke
AU - MacMahon, Heber
AU - Doi, Kunio
PY - 2005/11
Y1 - 2005/11
N2 - PURPOSE: To retrospectively evaluate whether a difference-image computer-aided detection (CAD) scheme can help radiologists detect peripheral lung cancers missed at low-dose computed tomography (CT). MATERIALS AND METHODS: Institutional review board approval and informed patient and observer consent were obtained. Seventeen patients (eight men and nine women; mean age, 60 years) with a missed peripheral lung cancer and 10 control subjects (five men and five women; mean age, 63 years) without cancer at low-dose CT were included in an observer study. Fourteen radiologists were divided into two groups on the basis of different image display formats: Six radiologists (group 1) reviewed CT scans with a multiformat display, and eight radiologists (group 2) reviewed images with a "stacked" cine-mode display. The radiologists, first without and then with the CAD scheme, indicated their confidence level regarding the presence (or absence) of cancer and the most likely position of a lesion on each CT scan. Receiver operating characteristic (ROC) curves were calculated without and with localization to evaluate the observers' performance. RESULTS: With the CAD scheme, the average area under the ROC curve improved from 0.763 to 0.854 for all radiologists (P = .002), from 0.757 to 0.862 for group 1 (P = .04), and from 0.768 to 0.848 for group 2 (P = .01). The average sensitivity in the detection of 17 cancers improved from 52% (124 of 238 observations) to 68% (163 of 238 observations) for all radiologists (P < .001), from 49% (50 of 102 observations) to 71% (72 of 102 observations) for group 1 (P = .02), and from 54% (74 of 136 observations) to 67% (91 of 136 observations) for group 2 (P = .006). The localization ROC curve also improved. CONCLUSION: Lung cancers missed at low-dose CT were very difficult to detect, even in an observer study. The use of CAD, however, can improve radiologists' performance in the detection of these subtle cancers.
AB - PURPOSE: To retrospectively evaluate whether a difference-image computer-aided detection (CAD) scheme can help radiologists detect peripheral lung cancers missed at low-dose computed tomography (CT). MATERIALS AND METHODS: Institutional review board approval and informed patient and observer consent were obtained. Seventeen patients (eight men and nine women; mean age, 60 years) with a missed peripheral lung cancer and 10 control subjects (five men and five women; mean age, 63 years) without cancer at low-dose CT were included in an observer study. Fourteen radiologists were divided into two groups on the basis of different image display formats: Six radiologists (group 1) reviewed CT scans with a multiformat display, and eight radiologists (group 2) reviewed images with a "stacked" cine-mode display. The radiologists, first without and then with the CAD scheme, indicated their confidence level regarding the presence (or absence) of cancer and the most likely position of a lesion on each CT scan. Receiver operating characteristic (ROC) curves were calculated without and with localization to evaluate the observers' performance. RESULTS: With the CAD scheme, the average area under the ROC curve improved from 0.763 to 0.854 for all radiologists (P = .002), from 0.757 to 0.862 for group 1 (P = .04), and from 0.768 to 0.848 for group 2 (P = .01). The average sensitivity in the detection of 17 cancers improved from 52% (124 of 238 observations) to 68% (163 of 238 observations) for all radiologists (P < .001), from 49% (50 of 102 observations) to 71% (72 of 102 observations) for group 1 (P = .02), and from 54% (74 of 136 observations) to 67% (91 of 136 observations) for group 2 (P = .006). The localization ROC curve also improved. CONCLUSION: Lung cancers missed at low-dose CT were very difficult to detect, even in an observer study. The use of CAD, however, can improve radiologists' performance in the detection of these subtle cancers.
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U2 - 10.1148/radiol.2372041555
DO - 10.1148/radiol.2372041555
M3 - Article
C2 - 16244277
AN - SCOPUS:27144509110
SN - 0033-8419
VL - 237
SP - 684
EP - 690
JO - Radiology
JF - Radiology
IS - 2
ER -
