Gedefaye Nibret Mihretie, Tewachew Muche Liyeh, Alemu Degu Ayele, Bekalu Getnet Kassa, Habtamu Gebrehana Belay, Tigabu Munye Aytenew, Dagne Addisu Sewuye, Binyam Minuye Birhane, Agenesh Dereje Misk, Bekalu Kassie Alemu
Knowledge and skills of newborn resuscitation among health care professionals in East Africa. A systematic review and meta-analysis
PloS one
accurate reliable noninvasive assessment patients diagnosed prostate cancer essential proper disease management quantitative assessment multiparametric mri artificial intelligence spectralstatistical approaches provide noninvasive objective determination prostate tumor aggressiveness without side effects potential poor sampling needle biopsy overdiagnosis prostate serum antigen measurements simplify expedite prostate tumor evaluation study examined efficacy autonomously extracting tumor spectral signatures spectralstatistical algorithms spatially registered biparametric mri spatially registered hypercubes digitally constructed resizing translating cropping image sequences apparent diffusion coefficient adc high bvalue t2 42 consecutive patients biparametric mri picai dataset prostate cancer blobs exceeded threshold applied registered set normalizing registered set image maximizes high bvalue minimizes adc t2 images appearing green color composite clinically significant blobs selected based size average normalized green value sliding window statistics within blob position within hypercube center mass maximized sliding window statistics within blobs identified voxels associated tumor signatures used correlation coefficients r pvalues evaluate linear regression fits zscore scr processed covariance matrix tumor aggressiveness well area curves auc receiver operator curves roc logistic probability fits clinically significant prostate cancer highest r r 045 auc 090 lowest pvalues 001 achieved using zscore modified registration applied covariance matrix tumor signatures selected greenest parts selected blob first autonomous tumor signature applied spatially registered biparametric mri shows promise determining prostate tumor aggressiveness