@phdthesis{oai:hama-med.repo.nii.ac.jp:00003723,
 author = {土屋, 充輝},
 month = {Mar},
 note = {doctoral, 医学系研究科, To evaluate the improvement of radiologist performance in detecting bone metastases at follow up low-dose computed tomography (CT) by using a temporal subtraction (TS) technique based on an advanced nonrigid image registration algorithm.
Twelve patients with bone metastases (males, 5; females, 7; mean age, 64.8±7.6 years; range 51?81 years) and 12 control patients without bone metastases (males, 5; females, 7; mean age, 64.8±7.6 years; 51?81 years) were included, who underwent initial and follow-up CT examinations between December 2005 and July 2016. Initial CT images were registered to follow-up CT images by the algorithm, and TS images were created. Three radiologists independently assessed the bone metastases with and without the TS images. The reader averaged jackknife alternative free-response receiver operating characteristics figure of merit was used to compare the diagnostic accuracy.
The reader-averaged values of the jackknife alternative free-response receiver operating characteristics figures of merit (θ) significantly improved from 0.687 for the readout without TS and 0.803 for the readout with TS (P value=.031. F statistic=5.24). The changes in the absolute value of CT attenuations in true-positive lesions were significantly larger than those in false-negative lesions (P<.001). Using TS, segment-based sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the readout with TS were 66.7%, 98.9%, 94.4%, 90.9%, and 94.8%, respectively.
The TS images can significantly improve the radiologist’s performance in the detection of bone metastases on low-dose and relatively thick-slice CT.},
 school = {浜松医科大学},
 title = {Temporal subtraction of low-dose and relatively thick-slice CT images with large deformation diffeomorphic metric mapping and adaptive voxel matching for detection of bone metastases: A STARD-compliant article},
 year = {2020}
}