Feng Li1, Roger Engelmann, Kunio Doi, Heber MacMahon. 1. Kurt Rossmann Laboratories for Radiologic Image Research and the Department of Radiology, The University of Chicago, 5841 S Maryland Ave., MC-2026, Chicago, IL 60637, USA. feng@uchicago.edu
Abstract
OBJECTIVE: The objective of our study was to retrospectively evaluate whether the use of dual-energy subtraction chest radiographs can improve radiologists' performance for the detection of small previously missed lung cancers. MATERIALS AND METHODS: Dual-energy subtraction chest radiographs of 19 patients with previously missed nodular cancers, in which the radiology report did not mention a nodule that was visible in retrospect, were selected. Dual-energy subtraction radiographs of 19 patients with cancer and 16 patients without cancer were used for an observer study. Six radiologists indicated their confidence level regarding the presence of a lung cancer and, if they thought a cancer was present, also marked the most likely position for each lung, first using standard posteroanterior and lateral chest radiographs and then using both soft-tissue and bone dual-energy subtraction images along with standard radiographs. Receiver operating characteristic (ROC) curves were used to evaluate the observers' performance. The indicated locations of cancers and false-positives were also analyzed. RESULTS: The average area under the ROC curve (A(z)) value for the six radiologists was improved from 0.718 to 0.816, a statistically significant amount (p = 0.004), and the average sensitivity (correct localizations) for 19 previously missed cancers was also significantly improved from 40% to 59% (p = 0.008) with the aid of dual-energy subtraction images. The average number of false-positive (incorrect) localizations on 70 lungs was 10 without and nine with dual-energy subtraction images (p = 0.785). CONCLUSION: Dual-energy subtraction chest radiography has the potential to improve radiologists' performance for the detection of small missed lung cancers.
OBJECTIVE: The objective of our study was to retrospectively evaluate whether the use of dual-energy subtraction chest radiographs can improve radiologists' performance for the detection of small previously missed lung cancers. MATERIALS AND METHODS: Dual-energy subtraction chest radiographs of 19 patients with previously missed nodular cancers, in which the radiology report did not mention a nodule that was visible in retrospect, were selected. Dual-energy subtraction radiographs of 19 patients with cancer and 16 patients without cancer were used for an observer study. Six radiologists indicated their confidence level regarding the presence of a lung cancer and, if they thought a cancer was present, also marked the most likely position for each lung, first using standard posteroanterior and lateral chest radiographs and then using both soft-tissue and bone dual-energy subtraction images along with standard radiographs. Receiver operating characteristic (ROC) curves were used to evaluate the observers' performance. The indicated locations of cancers and false-positives were also analyzed. RESULTS: The average area under the ROC curve (A(z)) value for the six radiologists was improved from 0.718 to 0.816, a statistically significant amount (p = 0.004), and the average sensitivity (correct localizations) for 19 previously missed cancers was also significantly improved from 40% to 59% (p = 0.008) with the aid of dual-energy subtraction images. The average number of false-positive (incorrect) localizations on 70 lungs was 10 without and nine with dual-energy subtraction images (p = 0.785). CONCLUSION: Dual-energy subtraction chest radiography has the potential to improve radiologists' performance for the detection of small missed lung cancers.
Authors: Feng Li; Roger Engelmann; Lorenzo L Pesce; Kunio Doi; Charles E Metz; Heber Macmahon Journal: Radiology Date: 2011-09-23 Impact factor: 11.105
Authors: Pablo C Zambrano-Rodríguez; Sirio Bolaños-Puchet; Horacio J Reyes-Alva; Luis E García-Orozco; Mario E Romero-Piña; Angelina Martinez-Cruz; Gabriel Guízar-Sahagún; Luis A Medina Journal: Neuroradiology Date: 2019-01-28 Impact factor: 2.804
Authors: Naoki Niikura; Bruno C Odisio; Yutaka Tokuda; Fraser W Symmans; Gabriel N Hortobagyi; Naoto T Ueno Journal: Nat Rev Clin Oncol Date: 2013-10-22 Impact factor: 66.675