PDF(Pubmed)
Abstract：
OBJECTIVE: An increasing number of commercial deep learning computer-aided detection (DL-CAD) systems are available but their cost-saving potential is largely unknown. This study aimed to gain insight into appropriate pricing for DL-CAD in different reading modes to be cost-saving and to determine the potentially most cost-effective reading mode for lung cancer screening.
METHODS: In three representative settings, DL-CAD was evaluated as a concurrent, pre-screening, and second reader. Scoping review was performed to estimate radiologist reading time with and without DL-CAD. Hourly cost of radiologist time was collected for the USA (€196), UK (€127), and Poland (€45), and monetary equivalence of saved time was calculated. The minimum number of screening CTs to reach break-even was calculated for one-time investment of €51,616 for DL-CAD.
RESULTS: Mean reading time was 162 (95% CI: 111-212) seconds per case without DL-CAD, which decreased by 77 (95% CI: 47-107) and 104 (95% CI: 71-136) seconds for DL-CAD as concurrent and pre-screening reader, respectively, and increased by 33-41 s for DL-CAD as second reader. This translates into €1.0-4.3 per-case cost for concurrent reading and €0.8-5.7 for pre-screening reading in the USA, UK, and Poland. To achieve break-even with a one-time investment, the minimum number of CT scans was 12,300-53,600 for concurrent reader, and 9400-65,000 for pre-screening reader in the three countries.
CONCLUSIONS: Given current pricing, DL-CAD must be priced substantially below €6 in a pay-per-case setting or used in a high-workload environment to reach break-even in lung cancer screening. DL-CAD as pre-screening reader shows the largest potential to be cost-saving.
UNASSIGNED: Deep-learning computer-aided lung nodule detection (DL-CAD) software must be priced substantially below 6 euro in a pay-per-case setting or must be used in high-workload environments with one-time investment in order to achieve break-even. DL-CAD as a pre-screening reader has the greatest cost savings potential.
CONCLUSIONS: • DL-CAD must be substantially below €6 in a pay-per-case setting to reach break-even. • DL-CAD must be used in a high-workload screening environment to achieve break-even. • DL-CAD as a pre-screening reader shows the largest potential to be cost-saving.
METHODS: In three representative settings, DL-CAD was evaluated as a concurrent, pre-screening, and second reader. Scoping review was performed to estimate radiologist reading time with and without DL-CAD. Hourly cost of radiologist time was collected for the USA (€196), UK (€127), and Poland (€45), and monetary equivalence of saved time was calculated. The minimum number of screening CTs to reach break-even was calculated for one-time investment of €51,616 for DL-CAD.
RESULTS: Mean reading time was 162 (95% CI: 111-212) seconds per case without DL-CAD, which decreased by 77 (95% CI: 47-107) and 104 (95% CI: 71-136) seconds for DL-CAD as concurrent and pre-screening reader, respectively, and increased by 33-41 s for DL-CAD as second reader. This translates into €1.0-4.3 per-case cost for concurrent reading and €0.8-5.7 for pre-screening reading in the USA, UK, and Poland. To achieve break-even with a one-time investment, the minimum number of CT scans was 12,300-53,600 for concurrent reader, and 9400-65,000 for pre-screening reader in the three countries.
CONCLUSIONS: Given current pricing, DL-CAD must be priced substantially below €6 in a pay-per-case setting or used in a high-workload environment to reach break-even in lung cancer screening. DL-CAD as pre-screening reader shows the largest potential to be cost-saving.
UNASSIGNED: Deep-learning computer-aided lung nodule detection (DL-CAD) software must be priced substantially below 6 euro in a pay-per-case setting or must be used in high-workload environments with one-time investment in order to achieve break-even. DL-CAD as a pre-screening reader has the greatest cost savings potential.
CONCLUSIONS: • DL-CAD must be substantially below €6 in a pay-per-case setting to reach break-even. • DL-CAD must be used in a high-workload screening environment to achieve break-even. • DL-CAD as a pre-screening reader shows the largest potential to be cost-saving.
摘要：
目的：越来越多的商用深度学习计算机辅助检测（DL-CAD）系统可用，但其节省成本的潜力在很大程度上是未知的。本研究旨在深入了解DL-CAD在不同阅读模式下的适当定价，以节省成本，并确定潜在的最具成本效益的肺癌筛查阅读模式。
方法：在三个代表性设置中，DL-CAD被评估为并发，预筛查,第二个读者。进行范围审查以估计有和没有DL-CAD的放射科医生阅读时间。在美国收集了放射科医生的每小时费用（196欧元），英国（127欧元），波兰（45欧元）并计算了节约时间的货币当量。对于DL-CAD，一次性投资51,616欧元，计算出达到收支平衡的筛查CT的最低数量。
结果：每例无DL-CAD的平均读取时间为162（95％CI：111-212）秒，作为并发和预筛选读取器，DL-CAD减少了77（95％CI：47-107）和104（95％CI：71-136）秒，分别,DL-CAD作为第二读者增加了33-41秒。在美国，并发阅读的每例费用为1.0-4.3欧元，筛查前阅读的费用为0.8-5.7欧元，英国,和波兰。以一次性投资实现盈亏平衡,并行阅读器的CT扫描最少数量为12,300-53,600,以及9400-65,000个国家/地区的预筛选读者。
结论：鉴于当前定价，DL-CAD必须在按病例付费的情况下定价低于6欧元，或在高工作量环境中使用，以在肺癌筛查中达到收支平衡。DL-CAD作为预筛选阅读器显示出最大的节省成本的潜力。
■深度学习计算机辅助肺结节检测（DL-CAD）软件必须在按案例付费的情况下定价低于6欧元，或者必须在高工作量环境中使用一次性投资，以实现收支平衡。DL-CAD作为预筛选阅读器具有最大的成本节约潜力。
结论：•DL-CAD在按案例付费的情况下必须大大低于6欧元才能达到收支平衡。•必须在高工作量筛选环境中使用DL-CAD以实现收支平衡。•DL-CAD作为预筛选阅读器显示出最大的节省成本的潜力。
方法：在三个代表性设置中，DL-CAD被评估为并发，预筛查,第二个读者。进行范围审查以估计有和没有DL-CAD的放射科医生阅读时间。在美国收集了放射科医生的每小时费用（196欧元），英国（127欧元），波兰（45欧元）并计算了节约时间的货币当量。对于DL-CAD，一次性投资51,616欧元，计算出达到收支平衡的筛查CT的最低数量。
结果：每例无DL-CAD的平均读取时间为162（95％CI：111-212）秒，作为并发和预筛选读取器，DL-CAD减少了77（95％CI：47-107）和104（95％CI：71-136）秒，分别,DL-CAD作为第二读者增加了33-41秒。在美国，并发阅读的每例费用为1.0-4.3欧元，筛查前阅读的费用为0.8-5.7欧元，英国,和波兰。以一次性投资实现盈亏平衡,并行阅读器的CT扫描最少数量为12,300-53,600,以及9400-65,000个国家/地区的预筛选读者。
结论：鉴于当前定价，DL-CAD必须在按病例付费的情况下定价低于6欧元，或在高工作量环境中使用，以在肺癌筛查中达到收支平衡。DL-CAD作为预筛选阅读器显示出最大的节省成本的潜力。
■深度学习计算机辅助肺结节检测（DL-CAD）软件必须在按案例付费的情况下定价低于6欧元，或者必须在高工作量环境中使用一次性投资，以实现收支平衡。DL-CAD作为预筛选阅读器具有最大的成本节约潜力。
结论：•DL-CAD在按案例付费的情况下必须大大低于6欧元才能达到收支平衡。•必须在高工作量筛选环境中使用DL-CAD以实现收支平衡。•DL-CAD作为预筛选阅读器显示出最大的节省成本的潜力。
