Robust identification of Parkinson's disease subtypes using radiomics and hybrid machine learning

Objectives: It is important to subdivide Parkinson's disease (PD) into subtypes, enabling potentially earlier disease recognition and tailored treatment strategies. We aimed to identify reproducible PD subtypes robust to variations in the number of patients and features. Methods: We applied multiple feature-reduction and cluster-analysis methods to cross-sectional and timeless data, extracted from longitudinal datasets (years 0, 1, 2 & 4; Parkinson's Progressive Marker Initiative; 885 PD/163 healthy-control visits; 35 datasets with combinations of non-imaging, conventional-imaging, and radiomics features from DAT-SPECT images). Hybrid machine-learning systems were constructed invoking 16 feature-reduction algorithms, 8 clustering algorithms, and 16 classifiers (C-index clustering evaluation used on each trajectory). We subsequently performed: i) identification of optimal subtypes, ii) multiple independent tests to assess reproducibility, iii) further confirmation by a statistical approach, iv) test of reproducibility to the size of the samples. Results: When using no radiomics features, the clusters were not robust to variations in features, whereas, utilizing radiomics information enabled consistent generation of clusters through ensemble analysis of trajectories. We arrived at 3 distinct subtypes, confirmed using the training and testing process of k-means, as well as Hotelling's T2 test. The 3 identified PD subtypes were 1) mild; 2) intermediate; and 3) severe, especially in terms of dopaminergic deficit (imaging), with some escalating motor and non-motor manifestations. Conclusion: Appropriate hybrid systems and independent statistical tests enable robust identification of 3 distinct PD subtypes. This was assisted by utilizing radiomics features from SPECT images (segmented using MRI). The PD subtypes provided were robust to the number of the subjects, and features. © 2020 Elsevier Lt

Efficacy of a topical formulation of henna (Lawsonia inermis L.) in contact dermatitis in patients using prosthesis: A double-blind randomized placebo-controlled clinical trial

Background: Contact dermatitis is a common complication in prosthetic limb users. There are no effective, available and cheap treatments for skin problems of these patients. In traditional Iranian medicine, henna (Lawsonia inermis L.) is a plant that has anti-inflammatory, antimicrobial and skin-enhancing properties, all of which are beneficial for people with artificial limbs. The aim of this study was to assess the efficacy of a topical henna preparation in management of contact dermatitis in patients using lower limb prosthetics. Methods: The current randomized, double-blind, placebo-controlled clinical trial was conducted on ninety-five participants with lower extremity amputation using limb prosthetics, aged 12�70 years who complained of contact dermatitis. They were randomly assigned to receive either two weeks of topical henna preparation every night as the intervention group, or topical placebo as the control group. Participants were instructed to spread henna preparation on the surfaces of the amputated limb that were in contact with the prosthesis. Severity of contact dermatitis symptoms was set as the primary outcome measure. Edema, papules and erythema were evaluated by a physician using standard color atlas. Secondary outcomes included symptoms such as burning, itching, pain, thickness and skin sweating evaluated by a self-administered questionnaire. Results: A significant improvement was observed in the symptoms of contact dermatitis including skin edema, itching, sweating, skin thinning and pain (p-value<0.05) in the henna group compared to the placebo group. Skin burning decreased more in the henna group compared to the placebo group, but this was not statistically significant (p-value = 0.052). Moreover, skin redness significantly increased in the henna group (p-value = 0.001). Conclusion: Topical formulation of henna might be a complementary choice for improving contact dermatitis in patients using lower limb prosthetics. © 2020 Elsevier Lt