Skeletal radiology · 2011
Measuring femoral lesions despite CT metal artefacts: a cadaveric study.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Malan Daniel F, Botha Charl P, Kraaij Gert, Joemai Raoul M S, van der Heide Huub J L, Nelissen Rob G H H, Valstar Edward R
Аннотация
OBJECTIVE: Computed tomography is the modality of choice for measuring osteolysis but suffers from metal-induced artefacts obscuring periprosthetic tissues. Previous papers on metal artefact reduction (MAR) show qualitative improvements, but their algorithms have not found acceptance for clinical applications. We investigated to what extent metal artefacts interfere with the segmentation of lesions adjacent to a metal femoral implant and whether metal artefact reduction improves the manual segmentation of such lesions.
MATERIALS AND METHODS: We manually created 27 periprosthetic lesions in 10 human cadaver femora. We filled the lesions with a fibrotic interface tissue substitute. Each femur was fitted with a polished tapered cobalt-chrome prosthesis and imaged twice--once with the metal, and once with a substitute resin prosthesis inserted. Metal-affected CTs were processed using standard back-projection as well as projection interpolation (PI) MAR. Two experienced users segmented all lesions and compared segmentation accuracy.
RESULTS: We achieved accurate delineation of periprosthetic lesions in the metal-free images. The presence of a metal implant led us to underestimate lesion volume and introduced geometrical errors in segmentation boundaries. Although PI MAR reduced streak artefacts, it led to greater underestimation of lesion volume and greater geometrical errors than without its application.
CONCLUSION: CT metal artefacts impair image segmentation. PI MAR can improve subjective image appearance but causes loss of detail and lower image contrast adjacent to prostheses. Our experiments showed that PI MAR is counterproductive for manual segmentation of periprosthetic lesions and should be used with care.
MATERIALS AND METHODS: We manually created 27 periprosthetic lesions in 10 human cadaver femora. We filled the lesions with a fibrotic interface tissue substitute. Each femur was fitted with a polished tapered cobalt-chrome prosthesis and imaged twice--once with the metal, and once with a substitute resin prosthesis inserted. Metal-affected CTs were processed using standard back-projection as well as projection interpolation (PI) MAR. Two experienced users segmented all lesions and compared segmentation accuracy.
RESULTS: We achieved accurate delineation of periprosthetic lesions in the metal-free images. The presence of a metal implant led us to underestimate lesion volume and introduced geometrical errors in segmentation boundaries. Although PI MAR reduced streak artefacts, it led to greater underestimation of lesion volume and greater geometrical errors than without its application.
CONCLUSION: CT metal artefacts impair image segmentation. PI MAR can improve subjective image appearance but causes loss of detail and lower image contrast adjacent to prostheses. Our experiments showed that PI MAR is counterproductive for manual segmentation of periprosthetic lesions and should be used with care.