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Adult Advanced Chronic Lymphocytic Leukemia: Computational Analysis of Whole-Body CT Documents a Bone Structure Alteration.

Articolo
Data di Pubblicazione:
2014
Abstract:
Purpose To assess the presence of alteration of bone structure and bone marrow metabolism in adult patients who were suspected of having advanced chronic lymphocytic leukemia (ACLL) by using a computational prognostic model that was based on computational analysis of positron emission tomography (PET)/computed tomography (CT) images. Materials and Methods In this retrospective study, all patients signed written informed consent as a requisite to undergo PET/CT examination. However, due to its observational nature, approval from the ethical committee was not deemed necessary. Twenty-two previously untreated chronic lymphocytic leukemia patients underwent PET/CT for disease progression. PET/CT images were analyzed by using dedicated software, capable of recognizing an external 2-pixel bone ring whose Hounsfield coefficient served as cutoff to recognize trabecular and compact bone. PET/CT data from 22 age- and sex-matched control subjects were used as comparison. All data are reported as means ± standard deviations. The Student t test, log-rank, or Cox proportional hazards model were used as appropriate, considering a difference with a P value of less than .05 as significant. Results Trabecular bone was expanded in ACLL patients and occupied a larger fraction of the skeleton with respect to control subjects (mean, 39% ± 5 [standard deviation] vs 31% ± 7; ie, 32 of 81 mL/kg of ideal body weight vs 27 of 86 mL/kg of ideal body weight, respectively; P < .001). After stratification according to median value, patients with a ratio of trabecular to skeletal bone volume of more than 37.3% showed an actuarial 2-year survival of 18%, compared with 82% for those with a ratio of less than 37.3% (P < .001), independent from age, sex, biological markers, and disease duration. Conclusion These data suggest that computational assessment of skeletal alterations might represent a new window for prediction of the clinical course of the disease.
Tipologia CRIS:
01.01 Articolo in rivista
Elenco autori:
Marini, Cecilia
Autori di Ateneo:
MARINI CECILIA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/254713
Pubblicato in:
RADIOLOGY (ONLINE)
Journal
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