BACKGROUND: The purpose of this study was to evaluate the role of dynamic contrast-enhanced magnetic resonance imaging (dMRI) in detecting bone marrow involvement in cancer patients. PATIENTS AND METHODS: We studied 50 consecutive patients with histologically confirmed malignant dissemination to the bone marrow, using dMRI of the lumbosacral spine. Time-signal intensity curves were generated from regions of interest (ROIs) obtained from areas of obvious bone marrow disease (group B). In 16 patients from group B with focal disease, ROIs were also placed on areas with apparently normal bone marrow on static magnetic resonance images (group C). Twenty-two patients with no history of malignancy were used as a control group (group A). Wash-in (WIN) and wash-out (WOUT) rates, time to peak (TTPK), time to maximum slope (TMSP) values and WIN/TMSP ratios were calculated for each patient. Mean values for the three groups were compared statistically. Six patients from group B had follow-up dMRI after chemotherapy: four patients achieved a clinical partial response and two had resistant disease. RESULTS: A significant difference was found between groups A and B for all values. Between groups A and C, in spite of the similar static MRI appearance, all values were significantly different. Between groups B and C, a significant difference was found for WIN, WOUT rates and WIN/TMSP ratio. Follow-up dMRI data analysis correlated well with clinical staging. CONCLUSIONS: dMRI can distinguish normal from malignant bone marrow. It may identify malignant bone marrow infiltration in patients with negative static MRI and serve as both a diagnostic and prognostic tool for patients with bone marrow malignancies.
BACKGROUND: The purpose of this study was to evaluate the role of dynamic contrast-enhanced magnetic resonance imaging (dMRI) in detecting bone marrow involvement in cancerpatients. PATIENTS AND METHODS: We studied 50 consecutive patients with histologically confirmed malignant dissemination to the bone marrow, using dMRI of the lumbosacral spine. Time-signal intensity curves were generated from regions of interest (ROIs) obtained from areas of obvious bone marrow disease (group B). In 16 patients from group B with focal disease, ROIs were also placed on areas with apparently normal bone marrow on static magnetic resonance images (group C). Twenty-two patients with no history of malignancy were used as a control group (group A). Wash-in (WIN) and wash-out (WOUT) rates, time to peak (TTPK), time to maximum slope (TMSP) values and WIN/TMSP ratios were calculated for each patient. Mean values for the three groups were compared statistically. Six patients from group B had follow-up dMRI after chemotherapy: four patients achieved a clinical partial response and two had resistant disease. RESULTS: A significant difference was found between groups A and B for all values. Between groups A and C, in spite of the similar static MRI appearance, all values were significantly different. Between groups B and C, a significant difference was found for WIN, WOUT rates and WIN/TMSP ratio. Follow-up dMRI data analysis correlated well with clinical staging. CONCLUSIONS:dMRI can distinguish normal from malignant bone marrow. It may identify malignant bone marrow infiltration in patients with negative static MRI and serve as both a diagnostic and prognostic tool for patients with bone marrow malignancies.
Authors: Atin Saha; Kyung K Peck; Eric Lis; Andrei I Holodny; Yoshiya Yamada; Sasan Karimi Journal: Spine (Phila Pa 1976) Date: 2014-11-15 Impact factor: 3.468
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Authors: N R Khadem; S Karimi; K K Peck; Y Yamada; E Lis; J Lyo; M Bilsky; H A Vargas; A I Holodny Journal: AJNR Am J Neuroradiol Date: 2012-05-03 Impact factor: 3.825
Authors: Ning Lang; Yang Zhang; Enlong Zhang; Jiahui Zhang; Daniel Chow; Peter Chang; Hon J Yu; Huishu Yuan; Min-Ying Su Journal: Magn Reson Imaging Date: 2019-02-28 Impact factor: 2.546