Neuroimaging of CNS infection in haematological malignancy: important signs and common diagnostic pitfalls

Application of iron oxide nanoparticles in the diagnosis and treatment of leukemia

Leukemia is a malignancy initiated by uncontrolled proliferation of hematopoietic stem cell from the B and T lineages, resulting in destruction of hematopoietic system. The conventional leukemia treatments induce severe toxic and a long series of unwanted side-effects which are caused by lack of specificity of anti-leukemic drugs. Recently, nanotechnology have shown tremendous application and clinical impact with respect to diagnosis and treatment of leukemia. According to considerable researches in the context of finding new nanotechnological platform, iron oxide nanoparticles have been gained increasing attention for the leukemia patients use. In this review, a short introduction of leukemia is described followed by the evaluation of the current approaches of iron oxide nanoparticles applied in the leukemia detection and treatment. The enormous advantages of iron oxide nanoparticles for leukemia have been discussed, which consist of the detection of magnetic resonance imaging (MRI) as efficient contrast agents, magnetic biosensors and targeted delivery of anti-leukemia drugs by coating different targeting moieties. In addition, this paper will briefly describe the application of iron oxide nanoparticles in the combined treatment of leukemia. Finally, the shortcomings of the current applications of iron-based nanoparticles in leukemia diagnosis and treatment will be discussed in particular.

Differentiating central nervous system infection from disease infiltration in hematological malignancy

Hematological malignancies place individuals at risk of CNS involvement from their hematological disease and opportunistic intracranial infection secondary to disease-/treatment-associated immunosuppression. Differentiating CNS infection from hematological disease infiltration in these patients is valuable but often challenging. We sought to determine if statistical models might aid discrimination between these processes. Neuroradiology, clinical and laboratory data for patients with hematological malignancy at our institution between 2007 and 2017 were retrieved. MRI were deep-phenotyped across anatomical distribution, presence of pathological enhancement, diffusion restriction and hemorrhage and statistically modelled with Bayesian-directed probability networks and multivariate logistic regression. 109 patients were studied. Irrespective of a diagnosis of CNS infection or hematological disease, the commonest anatomical distributions of abnormality were multifocal-parenchymal (34.9%), focal-parenchymal (29.4%) and leptomeningeal (11.9%). Pathological enhancement was the most frequently observed abnormality (46.8%), followed by hemorrhage (22.9%) and restricted diffusion (19.3%). Logistic regression could differentiate CNS infection from hematological disease infiltration with an AUC of 0.85 where, with OR > 1 favoring CNS infection and < 1 favoring CNS hematological disease, significantly predictive imaging features were hemorrhage (OR 24.61, p = 0.02), pathological enhancement (OR 0.17, p = 0.04) and an extra-axial location (OR 0.06, p = 0.05). In conclusion, CNS infection and hematological disease are heterogeneous entities with overlapping radiological appearances but a multivariate interaction of MR imaging features may assist in distinguishing them.