Public articles linked to the same research event.
Blood Advances This study retrained a T1-weighted Dixon whole-body MRI deep-learning segmentation pipeline, originally developed on healthy UK Biobank participants, on scans from patients with multiple myeloma to automatically generate 11 image-derived phenotypes of non-diseased tissue (volumes of abdominal subcutaneous adipose tissue, visceral adipose tissue, abdominal skeletal muscle, liver, spleen, both kidneys, both iliopsoas muscles and heart, plus liver relative fat fraction), measured baseline and longitudinal values in a 69-patient prospective observational cohort (iTIMM) undergoing induction therapy and autologous stem cell transplant, and explored associations with progression-free survival, reporting a mean Dice of 0.916 and mean Likert of 4.
This study retrained a T1-weighted Dixon whole-body MRI deep-learning segmentation pipeline, originally developed on healthy UK Biobank participants, on scans from patients with multiple myeloma to automatically generate 11 image-derived phenotypes of non-diseased tissue (volumes of abdominal subcutaneous adipose tissue, visceral adipose tissue, abdominal skeletal muscle, liver, spleen, both kidneys, both iliopsoas muscles and heart, plus liver relative fat fraction), measured baseline and longitudinal values in a 69-patient prospective observational cohort (iTIMM) undergoing induction therapy and autologous stem cell transplant, and explored associations with progression-free survival, reporting a mean Dice of 0.916 and mean Likert of 4.
This study retrained a T1-weighted Dixon whole-body MRI deep-learning segmentation pipeline, originally developed on healthy UK Biobank participants, on scans from patients with multiple myeloma to automatically generate 11 image-derived phenotypes of non-diseased tissue (volumes of abdominal subcutaneous adipose tissue, visceral adipose tissue, abdominal skeletal muscle, liver, spleen, both kidneys, both iliopsoas muscles and heart, plus liver relative fat fraction), measured baseline and longitudinal values in a 69-patient prospective observational cohort (iTIMM) undergoing induction therapy and autologous stem cell transplant, and explored associations with progression-free survival, reporting a mean Dice of 0.916 and mean Likert of 4.
This study retrained a T1-weighted Dixon whole-body MRI deep-learning segmentation pipeline, originally developed on healthy UK Biobank participants, on scans from patients with multiple myeloma to automatically generate 11 image-derived phenotypes of non-diseased tissue (volumes of abdominal subcutaneous adipose tissue, visceral adipose tissue, abdominal skeletal muscle, liver, spleen, both kidneys, both iliopsoas muscles and heart, plus liver relative fat fraction), measured baseline and longitudinal values in a 69-patient prospective observational cohort (iTIMM) undergoing induction therapy and autologous stem cell transplant, and explored associations with progression-free survival, reporting a mean Dice of 0.916 and mean Likert of 4.