Computed tomography reading strategies in lung cancer screening

Numerous studies investigating low-dose computed tomography (LDCT) as a screening tool for lung cancer have either recently been completed or are ongoing. However, the optimum strategy for detecting nodules in a CT screening programme is still unknown. To date screening trials have varied substantia...

Full description

Bibliographic Details
Main Author: Nair, Arjun
Published: University of Edinburgh 2014
Subjects:
Online Access:https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.726498
id ndltd-bl.uk-oai-ethos.bl.uk-726498
record_format oai_dc
spelling ndltd-bl.uk-oai-ethos.bl.uk-7264982019-04-03T06:15:32ZComputed tomography reading strategies in lung cancer screeningNair, Arjun2014Numerous studies investigating low-dose computed tomography (LDCT) as a screening tool for lung cancer have either recently been completed or are ongoing. However, the optimum strategy for detecting nodules in a CT screening programme is still unknown. To date screening trials have varied substantially in their reading strategies. Each of these strategies may lead to different rates of true and false positive detection. The ideal strategy would maximise detection of lung cancers while minimising unnecessary costly and potentially harmful investigations. The type of strategy chosen also has significant implications for the number of radiologists required for a screening programme, and their workload. The investigations contained in this thesis are aimed at identifying an optimal and pragmatic reading strategy for LDCT screening. First, the potential role of radiographers as readers for LDCT screening was investigated. Following training and an assessment of continuous feedback learning, the performance of radiographers reading LDCT screening examinations was prospectively compared against radiologists; the performance of these radiographers was comparable to that of radiologists in the published literature, but inferior to that of radiologists reading the same scans. However, using radiographers as concurrent readers helped to improve radiologists' sensitivities in nodule detection, with an increase in false positive detections that is still below that reported for computeraided detection (CAD) systems. When evaluated as first readers against a clinically-approved CAD system, radiographers showed that they could achieve sensitivities comparable to or exceeding that of CAD, with a lower number of average false positive detections for the majority. The impact of double- and triple-reading strategies using different methods of arbitration for discordant findings was compared. Using more than one reader did not invariably improve pulmonary nodule detection accuracy for experienced thoracic radiologists, and resulted in increased false positive detections when double-reading with independent arbitration or triple-reading were used.616.99University of Edinburghhttps://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.726498http://hdl.handle.net/1842/25017Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 616.99
spellingShingle 616.99
Nair, Arjun
Computed tomography reading strategies in lung cancer screening
description Numerous studies investigating low-dose computed tomography (LDCT) as a screening tool for lung cancer have either recently been completed or are ongoing. However, the optimum strategy for detecting nodules in a CT screening programme is still unknown. To date screening trials have varied substantially in their reading strategies. Each of these strategies may lead to different rates of true and false positive detection. The ideal strategy would maximise detection of lung cancers while minimising unnecessary costly and potentially harmful investigations. The type of strategy chosen also has significant implications for the number of radiologists required for a screening programme, and their workload. The investigations contained in this thesis are aimed at identifying an optimal and pragmatic reading strategy for LDCT screening. First, the potential role of radiographers as readers for LDCT screening was investigated. Following training and an assessment of continuous feedback learning, the performance of radiographers reading LDCT screening examinations was prospectively compared against radiologists; the performance of these radiographers was comparable to that of radiologists in the published literature, but inferior to that of radiologists reading the same scans. However, using radiographers as concurrent readers helped to improve radiologists' sensitivities in nodule detection, with an increase in false positive detections that is still below that reported for computeraided detection (CAD) systems. When evaluated as first readers against a clinically-approved CAD system, radiographers showed that they could achieve sensitivities comparable to or exceeding that of CAD, with a lower number of average false positive detections for the majority. The impact of double- and triple-reading strategies using different methods of arbitration for discordant findings was compared. Using more than one reader did not invariably improve pulmonary nodule detection accuracy for experienced thoracic radiologists, and resulted in increased false positive detections when double-reading with independent arbitration or triple-reading were used.
author Nair, Arjun
author_facet Nair, Arjun
author_sort Nair, Arjun
title Computed tomography reading strategies in lung cancer screening
title_short Computed tomography reading strategies in lung cancer screening
title_full Computed tomography reading strategies in lung cancer screening
title_fullStr Computed tomography reading strategies in lung cancer screening
title_full_unstemmed Computed tomography reading strategies in lung cancer screening
title_sort computed tomography reading strategies in lung cancer screening
publisher University of Edinburgh
publishDate 2014
url https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.726498
work_keys_str_mv AT nairarjun computedtomographyreadingstrategiesinlungcancerscreening
_version_ 1719012461472907264