A new surgical path planning framework for neurosurgery.

BACKGROUND: Despite using a variety of path-finding algorithms that use tracts, the most significant advancement in this study is considering the values of all brain areas by doing atlas-based segmentation for a more precise search. Our motivation comes from the literature's shortcomings in designing and implementing path-planning methods. Since planning paths with curvatures is a complex problem that requires considering many surgical and physiological constraints, most path-planning strategies focus on straight paths. There is also a lack of studies that focus on the complete structure of the brain with the tracks, veins, and segmented areas. Instrument dependence is another inadequacy of the methods proposed in the literature. AIMS: The aim of this study is to design a new surgical path planning framework that helps to plan the surgical path independently of the instrument, considers the entire structure of the brain, and allows curvilinear surgical paths. Thus, neurosurgeons can generate patient-specific possible optimal surgical pathways before the neurosurgical procedure. MATERIALS & METHODS: The proposed framework includes different path-finding algorithms (Dijkstra, A*, and their aggressive variants) that find optimal paths by taking the risk scores (surgeons assessed all the segmented regions, considering the extent of damage. In this evaluation, scores ranged from "0 to 10," with the most critical areas receiving a score of "10," while the least possible affected areas were assigned a score of "0") for sensitive brain areas into consideration. For the tract image processing the framework includes fractional anisotropy (FA), relative anisotropy (RA), spherical measure (SM), and linear measure (LM) methods. RESULTS: This is the first paper to handle tracts and atlas-based segmentation of the human brain altogether under a framework for surgical path planning. The framework has a dynamic structure that gives the flexibility to add different path-finding algorithms and generate different widths of surgical pathways. Moreover, surgeons can update the score table to guarantee minimally invasive surgery. The output file format of all the extracted surgical paths is NRRD, so it can be easily visualised, analysed, or processed over the third part software tools. DISCUSSION: In this study, we generated many possible surgical pathways then these pathways were evaluated by the surgeons the results were impressive because the framework could identify surgical pathways used in real-world surgery that correspond to the standard pathways such as anterior transsylvian, trans sulcal, transgyral, and sub-temporal. CONCLUSION: This study proposes a new surgical path planning framework for neurosurgery. Moreover, in the future by adding/adopting different parameters (such as operation time, and short and long-term complications after surgery) to the proposed framework, it would be possible to find new surgical pathways for difficult surgical conditions.

Machine Learning-Based Surgical Planning for Neurosurgery: Artificial Intelligent Approaches to the Cranium.

Objectives: Artificial intelligence (AI) applications in neurosurgery have an increasing momentum as well as the growing number of implementations in the medical literature. In recent years, AI research define a link between neuroscience and AI. It is a connection between knowing and understanding the brain and how to simulate the brain. The machine learning algorithms, as a subset of AI, are able to learn with experiences, perform big data analysis, and fulfill human-like tasks. Intracranial surgical approaches that have been defined, disciplined, and developed in the last century have become more effective with technological developments. We aimed to define individual-safe, intracranial approaches by introducing functional anatomical structures and pathological areas to artificial intelligence. Methods: Preoperative MR images of patients with deeply located brain tumors were used for planning. Intracranial arteries, veins, and neural tracts are listed and numbered. Voxel values of these selected regions in cranial MR sequences were extracted and labeled. Tumor tissue was segmented as the target. Q-learning algorithm which is a model-free reinforcement learning algorithm was run on labeled voxel values (on optimal paths extracted from the new heuristic-based path planning algorithm), then the algorithm was assigned to list the cortico-tumoral pathways that aim to remove the maximum tumor tissue and in the meantime that functional anatomical tissues will be least affected. Results: The most suitable cranial entry areas were found with the artificial intelligence algorithm. Cortico-tumoral pathways were revealed using Q-learning from these optimal points. Conclusions: AI will make a significant contribution to the positive outcomes as its use in both preoperative surgical planning and intraoperative technique equipment assisted neurosurgery, its use increased.

Evaluation in terms of dietary habits of rheumatic process: A clinical study.

OBJECTIVE: This study compared the dietary habits of patients with ankylosing spondylitis (AS) and rheumatoid arthritis (RA). METHODS: The nutritional status of 56 patients, seen at the Rheumatology Outpatient Clinic and diagnosed with RA based on the ACR-2010 criteria, was compared with that of 28 patients diagnosed with AS using the modified New York criteria. Nutritional status was determined using a form that was filled out during face-to-face interviews with all patients. Patient demographics, disease activity, smoking and alcohol use, concomitant diseases, disease duration and nutritional status were determined using a questionnaire. RESULTS: RA patients consumed butter on 2 days a week, and AS patients on 1 day per month. Yoghurt was consumed by RA patients daily and by AS patients 3 days a week. CONCLUSIONS: Compared to the diet of AS patients, the diet of RA patients was richer in protein and lipids. The impact of diet on these two diseases remains to be determined in large-scale studies.

Association between nutritional status and Modic classification in degenerative disc disease.

[Purpose] This study was conducted to examine the association between Modic classification and the eating habits in patients with degenerative disc disease (DDD) and to determine the influence of nutrition on disease severity. [Subjects and Methods] Sixty patients with DDD visiting a low back pain outpatient clinic were enrolled. Through face-to-face interviews, they completed questionnaires regarding their demographics, disease activity, smoking and alcohol use, concomitant diseases, disease duration, and nutritional status.Exclusion criteria were age <20 years or >65 years, other comorbidities, missing MRI data, and inability to speak Turkish. [Results] Forty patients were finally included in the study. The frequency with which they consumed water, salt, fast food, eggs, milk, yogurt, cheese, whole wheat bread, white bread, butter, and margarine was recorded. A weak negative correlation was observed between the Modic types and fish and egg consumption. [Conclusion] Modic changes, which indicate the severity of DDD, seem to be correlated to patients' dietary habits. However, studies with comparison groups and larger samples are needed to confirm our promising results before any cause-and-effect relationship can be proposed.

Functional independence measure scores of patients with hemiplegia followed up at home and in university hospitals.

[Purpose] Our purpose was to create awareness among of social rehabilitation at the university and in local governments, to identify gaps in social rehabilitation, and to increase the effectiveness of social rehabilitation. [Subjects and Methods] This study included stroke patients undergoing physical rehabilitation from the stroke outpatient clinic (43 patients) and the Istanbul Metropolitan Municipality Home Care Service (101 patients); face-to-face interviews were conducted to collect patient information regarding nutritional status. In addition, baseline functional independence measure (FIM) scores at baseline and during three months of follow-up were also compared. [Results] The average FIM motor scores at three months did not differ significantly between the home and hospital treatment groups. However, there were significant differences in baseline FIM motor and cognitive scores and three-month follow-up scores as well as average FIM total baseline scores between groups. In addition, month-to-month analysis of changes in FIM values between the two groups also revealed significant differences. [Conclusion] The results of our study were concordant with those of previous studies of stroke patients receiving rehabilitation, in demonstrating improved patient functional and cognitive capacity.