A comparative evaluation of three consecutive artificial intelligence algorithms released by Techcyte for identification of blasts and white blood cells in abnormal peripheral blood films.

INTRODUCTION: Digital pathology artificial intelligence (AI) platforms have the capacity to improve over time through "deep machine learning." We have previously reported on the accuracy of peripheral white blood cell (WBC) differential and blast identification by Techcyte (Techcyte, Inc., Orem, UT, USA), a digital scanner-agnostic web-based system for blood film reporting. The aim of the current study was to compare AI protocols released over time to assess improvement in cell identification. METHODS: WBC differentials were performed using Techcyte's online AI software on the same 124 digitized abnormal peripheral blood films (including 64 acute and 22 chronic leukaemias) in 2019 (AI1), 2020 (AI2), and 2022 (AI3), with no reassignment by a morphologist at any time point. AI results were correlated to the "gold standard" of manual microscopy, and comparison of Lin's concordance coefficients (LCC) and sensitivity and specificity of blast identification were used to determine the superior AI version. RESULTS: AI correlations (r) with manual microscopy for individual cell types ranged from 0.50-0.90 (AI1), 0.66-0.86 (AI2) and 0.71-0.91 (AI3). AI3 concordance with manual microscopy was significantly improved compared to AI1 for identification of neutrophils (LCC AI3 = 0.86 vs. AI1 = 0.77, p = 0.03), total granulocytes (LCC AI3 = 0.92 vs. AI1 = 0.82, p = 0.0008), immature granulocytes (LCC AI3 = 0.67 vs. AI1 = 0.38, p = 0.0014), and promyelocytes (LCC AI3 = 0.53 vs. AI1 = 0.16, p = 0.0008). Sensitivity for blast identification (n = 65 slides) improved from 97% (AI1), to 98% (AI2), to 100% (AI3), while blast specificity decreased from 24% (AI1), to 14% (AI2) to 12% (AI3). CONCLUSION: Techcyte AI has shown significant improvement in cell identification over time and maintains high sensitivity for blast identification in malignant films.

The role of inflammatory cytokines on the aetiopathogenesis of depression.

OBJECTIVE: The primary focus of this review is to provide an overview of the role of inflammation in the development of depression. The article will describe how inflammatory cytokines contribute to depression via action on three major pathways in the brain: the neuroendocrine; neurotransmitter depletion; and neuroprogression pathways. METHODS: An online literature search was carried out in July 2012. Original articles and reviews were selected if they discussed the role of inflammation on the development of depression. RESULTS: There is a large body of current research on the role of inflammatory cytokines on the development of depression. Cytokines have been found to interact with different pathways in the brain, and may contribute to the development of depression. Cytokines cause hypercortisolaemia by dysregulation of the hypothalamic-pituitary-adrenal axis directly by activating it and indirectly by modifying glucocorticoid receptor sensitivity to cortisol leading to cortisol hypersecretion. Cytokines deplete central synaptic serotonin levels by reducing its synthesis and increasing its reuptake. They may also deplete neurotrophic factors which are believed to play a neuroprotective role against depression. Cytokines activate cellular cascades that cause excitotoxicity and apoptosis and inhibit neurogenesis in the hippocampus. CONCLUSION: There is a growing body of correlative studies that suggest inflammatory cytokines may be a central factor that can affect multiple neuronal pathways and have an additive effect on the development of depression. However, the fact that not all people with inflammatory conditions suffer from depression suggests that depression is not purely a result of elevated inflammatory cytokines. Depression may be a result of a complex pathology that remains an area of growing interest and importance.

White blood cell evaluation in haematological malignancies using a web-based digital microscopy platform.

INTRODUCTION: Digital microscopy systems are beginning to replace traditional light microscopes for morphologic analysis of blood films, but these are geographically restricted to individual computers and technically limited by manufacturer's constraints. We explored the use of a scanner-agnostic web-based artificial intelligence (AI) system to assess the accuracy of white blood cell (WBC) differentials and blast identification in haematological malignancies. METHODS: Digitized images of 20 normal and 124 abnormal peripheral blood films were uploaded to the web-based platform (Techcyte©) and WBC differentials performed using the online AI software. Digital images were viewed for accuracy and manual cell reassignment was performed where necessary. Results were correlated to the 'gold standard' of manual microscopy for each WBC class, and sensitivity and specificity of blast identification were calculated. RESULTS: The AI digital differential was very strongly correlated to microscopy (r > .8) for most normal cell types and did not require any manual reassignment. The AI digital differential was less reliable for abnormal blood films (r = .50-.87), but could be greatly improved by manual assessment of digital images for most cell types (r > .95) with the exception of immature granulocytes (r = .62). For blast identification, initial AI digital differentials showed 96% sensitivity and 25% specificity, which was improved to 99% and 84%, respectively, after manual digital review. CONCLUSIONS: The Techcyte platform allowed remote viewing and manual analysis of digitized slides that was comparable to microscopy. The AI software produced adequate WBC differentials for normal films and had high sensitivity for blast identification in malignant films.

The utility of serial blood film testing for the diagnosis of malaria.

Current guidelines on the diagnosis and exclusion of malaria stipulate that if there is an initial negative result on blood film, multiple blood film preparations should be taken to sufficiently exclude malaria.We looked at a state-wide database of blood results retrospectively for a period of 14 years to identify subjects who had been tested for malaria.Most (93%) of patients were diagnosed on the first blood smear. Almost 7% of patients had an initial negative blood film result but subsequently went on to have a positive result. The majority of patients diagnosed with malaria on the first blood film had Plasmodium falciparum (66%) whilst the majority of patients with an initial negative blood film result were later diagnosed with P. vivax (78%).Most of the subjects in the 7% group were members of the Australian Defence Force and would have received chemoprophylaxis against malaria.The majority of malaria diagnoses are confirmed on a single blood film result. However, a significant proportion of malaria diagnoses would be missed if only one blood film were examined. Currently there is insufficient clinical and epidemiological information to predict which subjects would require one versus three blood film examinations. As such, three blood films should be obtained for patients suspected of having malaria.