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Invasive aspergillosis (IA) represents a common form of fungal infection caused by various species of Aspergillus that most frequently affect immunocompromised patients. Typically, this disease occurs preferentially in high-risk groups including patients infected with the human immunodeficiency virus (HIV), patients with leukemia, patients with autoimmune diseases, and organ transplant patients undergoing medical immunosuppression. Considered the second most common cause of opportunistic fungal infection in humans after Candida albicans, this pathogen predominantly affects the lungs, but it may also spread by a hematogenous route to various organs and have a heterogeneous presentation. Owing to its high iodine levels, high perfusion, and enclosed capsule, the thyroid gland is considered to have a lower susceptibility to microbial invasion, and it is fairly uncommon to find associated infectious nodules. In metabolic imaging, 18F-FDG-PET/CT has become increasingly useful for detecting a wide range of infectious and inflammatory diseases and is already the gold standard for certain indications. According to the literature, no studies of hypermetabolic nodular thyroid aspergillosis on 18F-FDG-PET/CT confirmed on histology have yet been reported. Here, we report the first case of a patient with a heterogeneous presentation of IA and the presence of a hypermetabolic nodule in the thyroid with a surprising result.

Reaction-diffusion models have been proposed for decades to capture the growth of gliomas. Nevertheless, these models require an initial condition: the tumor cell density distribution over the whole brain at diagnosis time. Several works have proposed to relate this distribution to abnormalities visible on magnetic resonance imaging (MRI). In this work, we verify these hypotheses by stereotactic histological analysis of a non-operated brain with glioblastoma using a 3D-printed slicer. Cell density maps are computed from histological slides using a deep learning approach. The density maps are then registered to a postmortem MR image and related to an MR-derived geodesic distance map to the tumor core. The relation between the edema outlines visible on T2-FLAIR MRI and the distance to the core is also investigated. Our results suggest that (i) the previously proposed exponential decrease of the tumor cell density with the distance to the core is reasonable but (ii) the edema outlines would not correspond to a cell density iso-contour and (iii) the suggested tumor cell density at these outlines is likely overestimated. These findings highlight the limitations of conventional MRI to derive glioma cell density maps and the need for other initialization methods for reaction-diffusion models to be used in clinical practice.