The influence of image reconstruction methods on the diagnosis of pulmonary emphysema with convolutional neural network.

This study investigated the influence of iterative reconstruction (IR) methods on computed tomography (CT) images when training convolutional neural network (CNN) models to diagnose pulmonary emphysema. To evaluate the influence of the IR algorithm on CNN, the present study comprised two steps: the comparison of noise reduction by IR algorithms using phantom examinations and the change in performance of CNN with IR algorithms using patient data. We retrospectively analyzed 97 patients. Raw CT data were reconstructed using the filtered back-projection (FBP) and adaptive statistical iterative reconstruction V (ASIR-V) algorithms with blending levels of 30%, 50%, and 70%. The models were trained using reconstructed CT images and were named the FBP, ASIR-V30, ASIR-V50, and ASIR-V70 models. The mean and the standard deviation of the CT values were 11.3 ± 21.2 at FBP, 11.0 ± 17.3 at ASIR-V30, 11.0 ± 14.4 at ASIR-V50, and 11.0 ± 11.8 at ASIR-V70. For all the evaluation metrics, the best values were obtained with the FBP model applied to the ASIR-V70 test images. The worst values were obtained with the ASIR-V70 model applied to the FBP test images. The model trained with FBP images exhibited significantly better performance than the models trained using IR images. The reduction in image noise with the IR algorithm on the test images contributed to improving the accuracy of the classification of emphysema subtypes using CNN.

Evaluation of cell viability and metabolic activity of a 3D cultured human epidermal model using a dynamic autoradiographic technique with a PET radiopharmaceutical.

Quality control of tissues and organs for transplant is important to confirm their safety and effectiveness for regenerative medicine. However, quality evaluation is only carried out using a limited range of inspection criteria, because many of the available evaluation tests are invasive. In order to explore the potential of 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG)-bioradiography as a non-invasive test for estimation of the safety, soundness, and effectiveness of tissues for transplantation, [18F]FDG uptake and cell viability or metabolism were investigated using a reconstructed human epidermal model (RHEM). We developed an imaging system, and suitable bioradiographic image acquisition conditions and its effectiveness were investigated. [18F]FDG uptake increased in agreement with DNA content as a marker of cell numbers and for histological assessment during cell proliferation and keratinization. [18F]FDG uptake was significantly decreased in good agreement with the viability of tissues used with various hazardous chemical treatments. [18F]FDG uptake by the tissues was decreased by hypothermia treatment and increased by hypoxia treatment while maintaining cell viability in the tissue. Therefore, [18F]FDG-bioradiography can be useful to estimate cell viability or metabolism in this RHEM. This method might be utilized as a non-invasive test for quality evaluation of tissues for transplantation.