京都大学 / 0048 / 新制・論文博士 / 博士(医学) / 乙第13270号 / 論医博第2184号 / 新制||医||1038(附属図書館) / 京都大学大学院医学研究科内科系専攻 / (主査)教授 溝脇 尚志, 教授 平井 豊博, 教授 伊達 洋至 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM

Yes / Digital image processing used in modern cardiac interventional x-ray systems may have the potential to enhance image quality such that it allows for lower radiation doses. The aim of this research was to quantify the reduction in radiation dose facilitated by image processing alone for percutaneous coronary intervention (PCI) patient angiograms, without reducing the perceived image quality required to confidently make a diagnosis. Incremental amounts of image noise were added to five PCI patient angiograms, simulating the angiogram having been acquired at corresponding lower dose levels (by 10-89% dose reduction). Sixteen observers with relevant and experience scored the image quality of these angiograms in three states - with no image processing and with two different modern image processing algorithms applied; these algorithms are used on state-of-the-art and previous generation cardiac interventional x-ray systems. Ordinal regression allowing for random effects and the delta method were used to quantify the dose reduction allowed for by the processing algorithms, for equivalent image quality scores. The dose reductions [with 95% confidence interval] from the state-of-the-art and previous generation image processing relative to no processing were 24.9% [18.8- 31.0%] and 15.6% [9.4-21.9%] respectively. The dose reduction enabled by the state-of-the-art image processing relative to previous generation processing was 10.3% [4.4-16.2%]. This demonstrates that statistically significant dose reduction can be facilitated with no loss in perceived image quality using modern image enhancement; the most recent processing algorithm was more effective in preserving image quality at lower doses. / The study was funded by Philips Healthcare (the Netherlands).

Yes / Dynamic X-ray imaging systems are used for interventional cardiac procedures to treat coronary heart disease. X-ray settings are controlled automatically by specially-designed X-ray dose control mechanisms whose role is to ensure an adequate level of image quality is maintained with an acceptable radiation dose to the patient. Current commonplace dose control designs quantify image quality by performing a simple technical measurement directly from the image. However, the utility of cardiac X-ray images is in their interpretation by a cardiologist during an interventional procedure, rather than in a technical measurement. With the long term goal of devising a clinically-relevant image quality metric for an intelligent dose control system, we aim to investigate the relationship of image noise with clinical professionals’ perception of dynamic image sequences. Computer-generated noise was added, in incremental amounts, to angiograms of five different patients selected to represent the range of adult cardiac patient sizes. A two alternative forced choice staircase experiment was used to determine the amount of noise which can be added to a patient image sequences without changing image quality as perceived by clinical professionals. Twenty-five viewing sessions (five for each patient) were completed by thirteen observers. Results demonstrated scope to increase the noise of cardiac X-ray images by up to 21% ± 8% before it is noticeable by clinical professionals. This indicates a potential for 21% radiation dose reduction since X-ray image noise and radiation dose are directly related; this would be beneficial to both patients and personnel. / This work was funded by Philips Healthcare, NL. Part of this work has been performed in the project PANORAMA, cofunded by grants from Belgium, Italy, France, the Netherlands, and the United Kingdom, and the ENIAC Joint Undertaking.

Esse trabalho apresenta uma nova metodologia para a correção do espectro de potência do ruído no processo de simulação de aquisições de imagens de tomossíntese digital mamária (Digital Breast Tomosynthesis - DBT) com doses reduzidas de radiação. A simulação é realizada por meio da inserção de ruído quântico dependente do sinal em imagens previamente adquiridas com a dose padrão de radiação. A DBT utiliza a mesma tecnologia de raios X que a mamografia digital, porém com a capacidade de prover ao médico exames do volume tridimensional da mama, minimizando o problema de superposição de tecidos. Apesar de ser o sucessor da mamografia, estudos têm mostrado que a otimização da relação entre a dose de radiação e a qualidade da imagem adquirida ainda não está bem estabelecida na DBT. Devido à impossibilidade de realizar diversas exposições de radiação a uma mesma paciente para os estudos de otimização da dose de radiação, é desejável que exista um método capaz de simular com exatidão diversas exposições tendo como base uma imagem clínica de referência. Embora existam diversos métodos para a simulação da redução de dose em exames mamográficos, o mesmo não pode ser dito quanto a imagens de DBT. O método desenvolvido para simulação da redução da dose de radiação em imagens de DBT se baseia em uma abordagem de inserção de ruído por meio de uma transformada de estabilização de variância, que já foi utilizada para simulação da redução de dose em exames de mamografia digital. Porém, esse trabalho propõe a inclusão da correção do espectro de potência do ruído para otimizar o desempenho do método de inserção de ruído para exames de DBT. Os resultados obtidos mostraram que, quando comparando a imagens de referência, a as imagens simuladas apresentaram erro menores que 1% para a análise do valor médio e desvio padrão e erro próximo de 5% para a análise do espectro de potência, apresentado resultados até 64% melhores que métodos não otimizados para DBT. / This work presents a new methodology for noise power spectrum correction in the simulation of digital breast tomosynthesis (DBT) images with reduced dose of radiation. The simulation is performed by inserting a signal-dependent quantum noise into previously acquired images with the standard dose of radiation. Using the same X-ray technology as a standard mammography, the DBT is capable of reconstructing the inner tissues of the patients\' breasts as a three-dimensional volume, providing more resources for cancer detection than its bi-dimensional counterpart and minimizing tissue overlapping. Despite being the successor to mammography, studies have shown that the optimization of the relationship between radiation dose and image quality is not well established in DBT yet. Due to the impossibility of exposing the same patient to multiple exams with different doses each, a simulation method able to mimic clinical images with high reliability is desirable. Despite the number of methods proposed for dose reduction simulation in mammography, scarcely any may be used in DBT. The method developed for simulation of radiation dose reduction in DBT images is based on a noise insertion approach using a variance-stabilizing transformation, which has already been used to simulate dose reduction in digital mammography exams. However, this work proposes the inclusion of the noise power spectrum correction to optimize the performance of the noise insertion method for DBT exams. The results showed that, when compared with reference images, the simulated images achieved less than 1% error for mean and standard deviation values and close to 5% error for power spectrum analysis, improving in up to 64% when compared with non-optimized for DBT simulation methods.

Esse trabalho apresenta uma nova metodologia para a correção do espectro de potência do ruído no processo de simulação de aquisições de imagens de tomossíntese digital mamária (Digital Breast Tomosynthesis - DBT) com doses reduzidas de radiação. A simulação é realizada por meio da inserção de ruído quântico dependente do sinal em imagens previamente adquiridas com a dose padrão de radiação. A DBT utiliza a mesma tecnologia de raios X que a mamografia digital, porém com a capacidade de prover ao médico exames do volume tridimensional da mama, minimizando o problema de superposição de tecidos. Apesar de ser o sucessor da mamografia, estudos têm mostrado que a otimização da relação entre a dose de radiação e a qualidade da imagem adquirida ainda não está bem estabelecida na DBT. Devido à impossibilidade de realizar diversas exposições de radiação a uma mesma paciente para os estudos de otimização da dose de radiação, é desejável que exista um método capaz de simular com exatidão diversas exposições tendo como base uma imagem clínica de referência. Embora existam diversos métodos para a simulação da redução de dose em exames mamográficos, o mesmo não pode ser dito quanto a imagens de DBT. O método desenvolvido para simulação da redução da dose de radiação em imagens de DBT se baseia em uma abordagem de inserção de ruído por meio de uma transformada de estabilização de variância, que já foi utilizada para simulação da redução de dose em exames de mamografia digital. Porém, esse trabalho propõe a inclusão da correção do espectro de potência do ruído para otimizar o desempenho do método de inserção de ruído para exames de DBT. Os resultados obtidos mostraram que, quando comparando a imagens de referência, a as imagens simuladas apresentaram erro menores que 1% para a análise do valor médio e desvio padrão e erro próximo de 5% para a análise do espectro de potência, apresentado resultados até 64% melhores que métodos não otimizados para DBT. / This work presents a new methodology for noise power spectrum correction in the simulation of digital breast tomosynthesis (DBT) images with reduced dose of radiation. The simulation is performed by inserting a signal-dependent quantum noise into previously acquired images with the standard dose of radiation. Using the same X-ray technology as a standard mammography, the DBT is capable of reconstructing the inner tissues of the patients\' breasts as a three-dimensional volume, providing more resources for cancer detection than its bi-dimensional counterpart and minimizing tissue overlapping. Despite being the successor to mammography, studies have shown that the optimization of the relationship between radiation dose and image quality is not well established in DBT yet. Due to the impossibility of exposing the same patient to multiple exams with different doses each, a simulation method able to mimic clinical images with high reliability is desirable. Despite the number of methods proposed for dose reduction simulation in mammography, scarcely any may be used in DBT. The method developed for simulation of radiation dose reduction in DBT images is based on a noise insertion approach using a variance-stabilizing transformation, which has already been used to simulate dose reduction in digital mammography exams. However, this work proposes the inclusion of the noise power spectrum correction to optimize the performance of the noise insertion method for DBT exams. The results showed that, when compared with reference images, the simulated images achieved less than 1% error for mean and standard deviation values and close to 5% error for power spectrum analysis, improving in up to 64% when compared with non-optimized for DBT simulation methods.