RATIONALE AND OBJECTIVES: From dynamic contrast-enhanced magnetic resonance imaging, it is known that microcirculation patterns in multiple myeloma differ depending on the infiltration pattern. The purpose of this study was to evaluate histogram analysis of dynamic contrast-enhanced magnetic resonance imaging in MM to monitor early treatment response on the basis of microcirculation patterns. MATERIALS AND METHODS: A total of 51 patients with multiple myeloma requiring therapy were examined. Dynamic contrast-enhanced magnetic resonance imaging of the lumbar spine was performed before and after conventional or high-dose chemotherapy with autologous stem cell transplantation. Statistical analysis included 245 vertebrae and dynamic microcirculation parameters as displayed in histograms. Resulting parameters (amplitude, exchange rate constant, skewness, kurtosis, and left shift) were correlated with therapeutic response. RESULTS: More than 70% of histograms derived from the microcirculation parameters showed a difference between the maximum peak before and after therapy (left shift). However, there was no significant difference between the particular treatment. Significantly different skewness of amplitude in 98% and kurtosis of exchange rate constant (94.1% and 98%) were seen in the patients who responded to treatment (P for each < .05). CONCLUSIONS: Histogram analysis revealed early changes after therapy resulting in a shift toward more (kurtosis) and lower values (skewness) of microcirculation parameters. Therefore, histogram analysis can determine and describe if a chosen therapy works at all. However, there were no differences between the chosen therapies. This needs to be reevaluated in a larger number of treated patients. Histogram analysis can also be an adjunct to a subjective visual analysis but is hampered by heterogeneous infiltration pattern seen in multiple myeloma.
RATIONALE AND OBJECTIVES: From dynamic contrast-enhanced magnetic resonance imaging, it is known that microcirculation patterns in multiple myeloma differ depending on the infiltration pattern. The purpose of this study was to evaluate histogram analysis of dynamic contrast-enhanced magnetic resonance imaging in MM to monitor early treatment response on the basis of microcirculation patterns. MATERIALS AND METHODS: A total of 51 patients with multiple myeloma requiring therapy were examined. Dynamic contrast-enhanced magnetic resonance imaging of the lumbar spine was performed before and after conventional or high-dose chemotherapy with autologous stem cell transplantation. Statistical analysis included 245 vertebrae and dynamic microcirculation parameters as displayed in histograms. Resulting parameters (amplitude, exchange rate constant, skewness, kurtosis, and left shift) were correlated with therapeutic response. RESULTS: More than 70% of histograms derived from the microcirculation parameters showed a difference between the maximum peak before and after therapy (left shift). However, there was no significant difference between the particular treatment. Significantly different skewness of amplitude in 98% and kurtosis of exchange rate constant (94.1% and 98%) were seen in the patients who responded to treatment (P for each < .05). CONCLUSIONS: Histogram analysis revealed early changes after therapy resulting in a shift toward more (kurtosis) and lower values (skewness) of microcirculation parameters. Therefore, histogram analysis can determine and describe if a chosen therapy works at all. However, there were no differences between the chosen therapies. This needs to be reevaluated in a larger number of treated patients. Histogram analysis can also be an adjunct to a subjective visual analysis but is hampered by heterogeneous infiltration pattern seen in multiple myeloma.
Authors: Giuseppe Lucio Cascini; Carmela Falcone; Domenico Console; Antonino Restuccia; Marco Rossi; Antonello Parlati; Oscar Tamburrini Journal: Radiol Med Date: 2013-06-26 Impact factor: 3.469
Authors: K Duncan; T R Rosean; V S Tompkins; A Olivier; R Sompallae; F Zhan; G Tricot; M R Acevedo; L L B Ponto; S A Walsh; L T Tygrett; A J Berger; T Waldschmidt; H C Morse; J J Sunderland; S Janz Journal: Blood Cancer J Date: 2013-11-29 Impact factor: 11.037
Authors: Frederic E Lecouvet; Marie-Christiane Vekemans; Thomas Van Den Berghe; Koenraad Verstraete; Thomas Kirchgesner; Souad Acid; Jacques Malghem; Joris Wuts; Jens Hillengass; Vincent Vandecaveye; François Jamar; Olivier Gheysens; Bruno C Vande Berg Journal: Skeletal Radiol Date: 2021-08-07 Impact factor: 2.199