BACKGROUND AND OBJECTIVE: We present a fully automatic system based on learning approaches, which aims to localization and identification (labeling) of vertebrae in 3D computed tomography (CT) scans of possibly incomplete spines in patients with bone metastases and vertebral compressions. METHODS: The framework combines a set of 3D algorithms for i) spine detection using a convolution neural network (CNN) ii) spinal cord tracking based on combination of a CNN and a novel growing sphere method with a population optimization, iii) intervertebral discs localization using a novel approach of spatially variant filtering of intensity profiles and iv) vertebra labeling using a CNN-based classification combined with global dynamic optimization. RESULTS: The proposed algorithm has been validated in testing databases, including also a publicly available dataset. The mean error of intervertebral discs localization is 4.4 mm, and for vertebra labeling, the average rate of correctly identified vertebrae is 87.1%, which can be considered a good result with respect to the large share of highly distorted spines and incomplete spine scans. CONCLUSIONS: The proposed framework, which combines several advanced methods including also three CNNs, works fully automatically even with incomplete spine scans and with distorted pathological cases. The achieved results allow including the presented algorithms as the first phase to the fully automated computer-aided diagnosis (CAD) system for automatic spine-bone lesion analysis in oncological patients.

• MeSH
• algoritmy MeSH
• databáze faktografické MeSH
• diagnóza počítačová MeSH
• lidé MeSH
• metastázy nádorů MeSH
• meziobratlová ploténka diagnostické zobrazování   patologie   MeSH
• nádory kostí diagnostické zobrazování   patologie   MeSH
• nemoci páteře diagnostické zobrazování   MeSH
• neuronové sítě MeSH
• páteř diagnostické zobrazování   patologie   MeSH
• počítačová rentgenová tomografie * MeSH
• počítačové zpracování obrazu MeSH
• reprodukovatelnost výsledků MeSH
• rozpoznávání automatizované MeSH
• software MeSH
• zobrazování trojrozměrné metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

OBJECTIVE: The aim of this study was to document the prevalence of degenerative intervertebral disc changes in the patients who previously reported symptoms of neck pain and to determine the influence of education level on degenerative intervertebral disc changes and subsequent chronic neck pain. METHODS: One hundred and twelve patients were randomly selected from the University Hospital in Mostar, Bosna and Herzegovina, (aged 48.5±12.7 years) and submitted to magnetic resonance imaging (MRI) of the cervical spine. MRI of 3.0 T (Siemens, Skyrim, Erlangen, Germany) was used to obtain cervical spine images. Patients were separated into two groups based on their education level: low education level (LLE) and high education level (HLE). Pfirrmann classification was used to document intervertebral disc degeneration, while self-reported chronic neck pain was evaluated using the previously validated Oswestry questionnaire. RESULTS: The entire logistic regression model containing all predictors was statistically significant, (χ2(3)=12.2, p=0.02), and was able to distinguish between respondents who had chronic neck pain and vice versa. The model explained between 10.0% (Cox-Snell R2) and 13.8% (Nagelkerke R2) of common variance with Pfirrmann classification, and it had the strength to discriminate and correctly classify 69.6% of patients. The probability of a patient being classified in the high or low group of degenerative disc changes according to the Pfirrmann scale was associated with the education level (Wald test: 5.5, p=0.02). Based on the Pfirrmann assessment scale, the HLE group was significantly different from the LLE group in the degree of degenerative changes of the cervical intervertebral discs (U=1,077.5, p=0.001). CONCLUSION: A moderate level of intervertebral disc degenerative changes (grade II and III) was equally matched among all patients, while the overall results suggest a higher level of education as a risk factor leading to cervical disc degenerative changes, regardless of age differences among respondents.

• MeSH
• bolest krku epidemiologie   MeSH
• chronická bolest epidemiologie   MeSH
• degenerace meziobratlové ploténky diagnostické zobrazování   epidemiologie   MeSH
• komorbidita MeSH
• lidé středního věku MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• meziobratlová ploténka diagnostické zobrazování   MeSH
• prevalence MeSH
• rizikové faktory MeSH
• stupeň vzdělání * MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Bosna a Hercegovina epidemiologie   MeSH