Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson's disease and schizophrenia

Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided

Applicability of Preoperative Nuclear Morphometry to Evaluating Risk for Cervical Lymph Node Metastasis in Oral Squamous Cell Carcinoma

Background: We previously reported the utility of preoperative nuclear morphometry for evaluating risk for cervical lymph node metastases in tongue squamous cell carcinoma. The risk for lymph node metastasis in oral squamous cell carcinoma, however, is known to differ depending on the anatomical site of the primary tumor, such as the tongue, gingiva, mouth floor, and buccal mucosa. In this study, we evaluated the applicability of this morphometric technique to evaluating the risk for cervical lymph node metastasis in oral squamous cell carcinoma. Methods: A digital image system was used to measure the mean nuclear area, mean nuclear perimeter, nuclear circular rate, ratio of nuclear length to width (aspect ratio), and nuclear area coefficient of variation (NACV). Relationships between these parameters and nodal status were evaluated by t-test and logistic regression analysis. Results: Eighty-eight cases of squamous cell carcinoma (52 of the tongue, 25 of the gingiva, 4 of the buccal mucosa, and 7 of the mouth floor) were included: 46 with positive node classification and 42 with negative node classification. Nuclear area and perimeter were significantly larger in node-positive cases than in nodenegative cases; however, there were no significant differences in circular rate, aspect ratio, or NACV. We derived two risk models based on the results of multivariate analysis: Model 1, which identified age and mean nuclear area and Model 2, which identified age and mean nuclear perimeter. It should be noted that primary tumor site was not associated the pN-positive status. There were no significant differences in pathological nodal status by aspect ratio, NACV, or primary tumor site. Conclusion: Our method of preoperative nuclear morphometry may contribute valuable information to evaluations of the risk for lymph node metastasis in oral squamous cell carcinoma

Cost-utility of sentinel lymph node biopsy in cT1-T2N0 oral cancer

© 2015 Elsevier Ltd. All rights reserved.All rights reserved. Objectives To calculate the cost-utility of different strategies for the detection of occult lymph node metastases in cT1-T2N0 oral cancer. Methods A decision tree followed by a Markov model was designed to compare the cost-utility of the following strategies: (a) USgFNAC (ultrasound guided fine needle aspiration cytology), (b) SLNB (sentinel lymph node biopsy), (c) USgFNAC and, if negative, SLNB (d) END (elective neck dissection). Data was collected from 62 patients in four Dutch head and neck centres. Utilities were measured with the EQ5D questionnaire and resource use was recorded from patient charts. Costs were calculated from a hospital perspective. Uncertainty was explored with scenario analyses and probabilistic sensitivity analyses. Results With a 5- or 10-year time horizon, SLNB results in the highest number of additional quality-adjusted life years (QALYs, 0.12 and 0.26, respectively) for the smallest additional costs (€56 and €74, respectively) compared to USgFNAC. With a lifetime horizon END results in the highest number of additional QALYs (0.55) for an additional €1.626 per QALY gained compared to USgFNAC. When we make different assumptions regarding the duration of disutilities (≥5 years) or the improvement (≥3%) of sensitivity of SLNB, SLNB is the most favourable strategy from all time horizons. Conclusion SLNB is a good diagnostic strategy to evaluate cT1-T2N0 oral cancer. SLNB is the preferred strategy in a 5- or 10-year time horizon. From a lifetime horizon, END may be preferred. SLNB may become the optimal strategy from all time horizons if its sensitivity can be slightly improved

Implications of a positive sentinel node in oral squamous cell carcinoma.

BACKGROUND: The role of sentinel node biopsy in head and neck cancer is currently being explored. Patients with positive sentinel nodes were investigated to establish if additional metastases were present in the neck, their distribution, and their impact on outcome. METHODS: In all, 109 patients (n = 109) from 15 European centers, with cT1/2,N0 tumors, and a positive sentinel lymph node were identified. Kaplan-Meier and univariate and multivariate logistic regression analysis were used to identify variables that predicted for additional positive nodes and their position within the neck. RESULTS: A total of 122 neck dissections were performed in 109 patients. Additional positive nodes were found in 34.4% of cases (42/122: 18 same, 21 adjacent, and 3 nonadjacent neck level). Additional nodes, especially if outside the sentinel node basin, had an impact on outcome. CONCLUSIONS: The results are preliminary but suggest that both the number and the position of positive sentinel nodes may identify different prognostic groups that may allow further tailoring of management plans. © 2012 Wiley Periodicals, Inc. Head Neck, 2012