Objective To evaluate and reduce inter-observer variations in the detection and characterization of pulmonary nodules on digital radiograph （DR） chest images. Methods Two hundreds and thirty-two new posterior-anteri...Objective To evaluate and reduce inter-observer variations in the detection and characterization of pulmonary nodules on digital radiograph （DR） chest images. Methods Two hundreds and thirty-two new posterior-anterior DR chest images were collected from out-patient screening patients. Consensus was reached by two experienced radiologists on the marking, rating, and segmentation of small actionable nodules ranged from 5 to 15 mm in diameter using a computer-aided diagnosis （CAD） system. Both their own nodule findings and the computer＇s automatic nodule detection results were analyzed to make the consensus. Nodules identified together with corresponding likelihood rating and segmentation results were referred as ＂Gold Stand- ard＂. Two un-experienced radiologists were asked to first mark and characterize suspicious nodules independently, then were allowed to consult the computer nodule detection results and change their decisions. Results Large inter-observer variations in pulmonary nodule identification and characterization on DR chest images were observed between un-experienced radiologists. Un-expefienced radiologists could greatly benefit from the CAD system, including substantial decrease of inter-observer variation and improvement of nodule detection rates. Moreover, radiologists with different levels of skillfulness could achieve similar high level performance after using the CAD system. Conclusion The CAD system shows a high potential for providing a valuable assistance to the examination of DR chest images.展开更多
Objective： To investigate the enhancement basis and the mechanisms of solitary pulmonary nodules （SPNs） by comparing the differences in microvascular structure between benign and malignant lesions. Methods： Dynami...Objective： To investigate the enhancement basis and the mechanisms of solitary pulmonary nodules （SPNs） by comparing the differences in microvascular structure between benign and malignant lesions. Methods： Dynamic contrast-enhanced CT scan was performed on 53 patients with SPNs （diameter〈3 cm, 38 peripheral lung cancers, 5 hamartomas, 10 inflammatory lesions） using a Siemens Plus S or a Marconi MX8000 multi slices spiral CT scanner. The time-attenuation curves were interpreted. The microvascular density （MVD） and the continuity of the microvessels＇ basemental membrane in the dissected specimens were observed with the ABC （avldin-biotin complex） immuno-histochemical method in all patients. Results ：The CT enhancement values of lung cancer （49.05± 16.08 HU） and inflammatory lesions （49.59±21.30 HU） were significantly higher than those of hamartoma （8.98±4.56 HU） t=7.48, P〈0.051 t=8.35, P〈0.05）. But the enhancement of lung cancer was similar to that of inflammatory lesions （t=0.76, P±0. 05）. The time attenuation curve of inflammatory lesions tended to increase faster and reached a higher peak compared to the lung cancer, and both of them maintained a high plateau after crossing. The hamartoma showed a slight increase in the time-attenuation curve and demonstrated a lowplateau curve. The MVD of SPNs was positively correlated with CT enhancement （r=0. 8051）. The microvascular counts of peripheral lung cancer （48.45±10. 09） and inflammatory lesions （49. 60±19. 94） were significantly higher than those of hamartoma （8.70±7. 30） （t=11. 64, P〈0.001, t=6. 09, P〈0. 001 ）, but no significant difference was found between lung cancer and inflammatory lesions （t= -0.26, P=0.799）. There was no difference in the continuity of basement membrane between nodules with anen haneement less than 30 HU and those with an enhancement higher than 30HU （X^2=3. 13, P〉0.05 ）. Conclusion： The microvascular counts mainly contribute to the enhancement value of SPNs. The basement membrane is not related to nodule enhancement, but it might influence the pattern of the time-attenuation curve.展开更多
Objective To assess inter-observer variations of pulmonary nodule marking in routine clinical chest digital radiograph (DR) softcopy reading by using a lung nodule computer toolkit.Methods A total of 601 chest posteri...Objective To assess inter-observer variations of pulmonary nodule marking in routine clinical chest digital radiograph (DR) softcopy reading by using a lung nodule computer toolkit.Methods A total of 601 chest posterior-anterior DR images were randomly selected from routine outpatient screening in Peking Union Medical College Hospital. Two chest radiologists with experience more than ten years were first asked to read the images and mark all suspicious nodules independently by using computer toolkit IQQA-Chest, and to indicate the likelihood for each nodule detected. They were also asked to draw the boundary of the identified nodule manually on an enlarged region of interest, which was instantly analyzed by IQQA-Chest. Two sets of diagnostic reports, including the marked nodules, likelihood, manually drawn boundaries, quantitative measurements, and radiologists’ names, were automatically generated and stored by the computer system. One week later, the two radiologists read the same images together by using the same computer toolkit without referring to their previous reading results. Marking procedure was the same except that consensus was reached for each suspicious region. Statistical analysis tools provided in the IQQA-Chest were used to compare all the three sets of reading results.Results In the independent readings, Reader 1 detected 409 nodules with a mean diameter of 12.4 mm in 241 patients, and Reader 2 detected 401 nodules with a mean diameter of 12.6 mm in 253 patients. In the consensus reading, a total of 352 nodules with a mean diameter of 12.4 mm were detected in 220 patients. Totally, 42.3% of Reader 1’s and 45.1% of Reader 2’s marks were confirmed by the consensus reading. About 40% of each reader’s marks agreed with the other. There were only 130 (14.4%) out of the total 904 unique nodules were confirmed by both readers and the consensus reading. Moreover, 5.6% (51/904) of the marked regions were rated identical likelihood in all three readings. Statistical analysis showed significant differences between Readers 1 and 2, and between consensus and Reader 2 in determining the likelihood of the marks (P<0.01), but not between consensus and Reader 1. No significant difference in terms of size was observed in nodule segmentation between either two of the three readings. Conclusion Large variations in nodule marking and nodule-likelihood determination but not in nodule size were observed between experts as well as between single-person reading and consensus reading.展开更多
文摘Objective To evaluate and reduce inter-observer variations in the detection and characterization of pulmonary nodules on digital radiograph （DR） chest images. Methods Two hundreds and thirty-two new posterior-anterior DR chest images were collected from out-patient screening patients. Consensus was reached by two experienced radiologists on the marking, rating, and segmentation of small actionable nodules ranged from 5 to 15 mm in diameter using a computer-aided diagnosis （CAD） system. Both their own nodule findings and the computer＇s automatic nodule detection results were analyzed to make the consensus. Nodules identified together with corresponding likelihood rating and segmentation results were referred as ＂Gold Stand- ard＂. Two un-experienced radiologists were asked to first mark and characterize suspicious nodules independently, then were allowed to consult the computer nodule detection results and change their decisions. Results Large inter-observer variations in pulmonary nodule identification and characterization on DR chest images were observed between un-experienced radiologists. Un-expefienced radiologists could greatly benefit from the CAD system, including substantial decrease of inter-observer variation and improvement of nodule detection rates. Moreover, radiologists with different levels of skillfulness could achieve similar high level performance after using the CAD system. Conclusion The CAD system shows a high potential for providing a valuable assistance to the examination of DR chest images.
文摘Objective： To investigate the enhancement basis and the mechanisms of solitary pulmonary nodules （SPNs） by comparing the differences in microvascular structure between benign and malignant lesions. Methods： Dynamic contrast-enhanced CT scan was performed on 53 patients with SPNs （diameter〈3 cm, 38 peripheral lung cancers, 5 hamartomas, 10 inflammatory lesions） using a Siemens Plus S or a Marconi MX8000 multi slices spiral CT scanner. The time-attenuation curves were interpreted. The microvascular density （MVD） and the continuity of the microvessels＇ basemental membrane in the dissected specimens were observed with the ABC （avldin-biotin complex） immuno-histochemical method in all patients. Results ：The CT enhancement values of lung cancer （49.05± 16.08 HU） and inflammatory lesions （49.59±21.30 HU） were significantly higher than those of hamartoma （8.98±4.56 HU） t=7.48, P〈0.051 t=8.35, P〈0.05）. But the enhancement of lung cancer was similar to that of inflammatory lesions （t=0.76, P±0. 05）. The time attenuation curve of inflammatory lesions tended to increase faster and reached a higher peak compared to the lung cancer, and both of them maintained a high plateau after crossing. The hamartoma showed a slight increase in the time-attenuation curve and demonstrated a lowplateau curve. The MVD of SPNs was positively correlated with CT enhancement （r=0. 8051）. The microvascular counts of peripheral lung cancer （48.45±10. 09） and inflammatory lesions （49. 60±19. 94） were significantly higher than those of hamartoma （8.70±7. 30） （t=11. 64, P〈0.001, t=6. 09, P〈0. 001 ）, but no significant difference was found between lung cancer and inflammatory lesions （t= -0.26, P=0.799）. There was no difference in the continuity of basement membrane between nodules with anen haneement less than 30 HU and those with an enhancement higher than 30HU （X^2=3. 13, P〉0.05 ）. Conclusion： The microvascular counts mainly contribute to the enhancement value of SPNs. The basement membrane is not related to nodule enhancement, but it might influence the pattern of the time-attenuation curve.
文摘Objective To assess inter-observer variations of pulmonary nodule marking in routine clinical chest digital radiograph (DR) softcopy reading by using a lung nodule computer toolkit.Methods A total of 601 chest posterior-anterior DR images were randomly selected from routine outpatient screening in Peking Union Medical College Hospital. Two chest radiologists with experience more than ten years were first asked to read the images and mark all suspicious nodules independently by using computer toolkit IQQA-Chest, and to indicate the likelihood for each nodule detected. They were also asked to draw the boundary of the identified nodule manually on an enlarged region of interest, which was instantly analyzed by IQQA-Chest. Two sets of diagnostic reports, including the marked nodules, likelihood, manually drawn boundaries, quantitative measurements, and radiologists’ names, were automatically generated and stored by the computer system. One week later, the two radiologists read the same images together by using the same computer toolkit without referring to their previous reading results. Marking procedure was the same except that consensus was reached for each suspicious region. Statistical analysis tools provided in the IQQA-Chest were used to compare all the three sets of reading results.Results In the independent readings, Reader 1 detected 409 nodules with a mean diameter of 12.4 mm in 241 patients, and Reader 2 detected 401 nodules with a mean diameter of 12.6 mm in 253 patients. In the consensus reading, a total of 352 nodules with a mean diameter of 12.4 mm were detected in 220 patients. Totally, 42.3% of Reader 1’s and 45.1% of Reader 2’s marks were confirmed by the consensus reading. About 40% of each reader’s marks agreed with the other. There were only 130 (14.4%) out of the total 904 unique nodules were confirmed by both readers and the consensus reading. Moreover, 5.6% (51/904) of the marked regions were rated identical likelihood in all three readings. Statistical analysis showed significant differences between Readers 1 and 2, and between consensus and Reader 2 in determining the likelihood of the marks (P<0.01), but not between consensus and Reader 1. No significant difference in terms of size was observed in nodule segmentation between either two of the three readings. Conclusion Large variations in nodule marking and nodule-likelihood determination but not in nodule size were observed between experts as well as between single-person reading and consensus reading.
