Search Results (9)

Robotic vertebral plate cutting poses significant challenges due to the complex bone structures of the lumbar spine, which consist of varying densities in cortical and cancellous regions. This study addresses these challenges by developing a predictive model for robotic vertebral plate cutting force and bone quality recognition through the fabrication of artificial vertebrae with controlled, consistent bone density. To address the variability in bone density between cortical and cancellous regions, CT data are utilized to predict target bone density, serving as a foundation for determining the optimal 3D printing process parameters. The proposed methodology integrates a Response Surface Methodology (RSM), Back Propagation (BP) neural network, and genetic algorithm (GA) to systematically evaluate the effects of key process parameters, such as the filling density, material flow rate, and layer thickness, on the printed vertebrae’s density. A one-factor experimental approach and RSM-based central composite design are applied to build an initial bone density prediction model, followed by Sobol’s sensitivity analysis to quantify the influence of each parameter. The GA-BP neural network model is then employed to rapidly and accurately identify optimal printing parameters for different bone layer densities. The resulting optimized models are used to fabricate personalized artificial lumbar vertebrae, which are subsequently validated through robotic cutting experiments. This research not only contributes to the advancement in personalized 3D printing technology but also provides a reliable framework for developing patient-specific surgical planning models in robot-assisted orthopedic surgery. Full article

The diagnosis of degenerative lumbar spine disease mainly relies on clinical manifestations and imaging examinations. However, the clinical manifestations are sometimes not obvious, and the diagnosis of medical imaging is usually time-consuming and highly relies on the doctor’s personal experiences. Therefore, a smart diagnostic technology that can assist doctors in manual diagnosis has become particularly urgent. Taking advantage of the development of artificial intelligence, a series of solutions have been proposed for the diagnosis of spinal diseases by using deep learning methods. The proposed methods produce appealing results, but the majority of these approaches are based on sagittal and axial images separately, which limits the capability of different deep learning methods due to the insufficient use of data. In this article, we propose a two-stage classification process that fully utilizes image data. In particular, in the first stage, we used the Mask RCNN model to identify the lumbar spine in the spine image, locate the position of the vertebra and disc, and complete rough classification. In the fine classification stage, a multi-angle view of the intervertebral disc is generated by splicing the sagittal and axial slices of the intervertebral disc up and down based on the key position identified in the first stage, which provides more pieces of information to the deep learning methods for classification. The experimental results reveal substantial performance enhancements with the synthesized multi-angle view, achieving an F1 score of 96.67%. This represents a performance increase of approximately 15% over the sagittal images at 84.48% and nearly 14% over the axial images at 83.15%. This indicates that the proposed paradigm is feasible and more effective in identifying spinal-related degenerative diseases through medical images. Full article

Background: Measures of lumbar lordosis (LL) and elliptical modeling variables have been shown to discriminate between normal and chronic low back pain (CLBP) patients. Pelvic morphology influences an individual’s sagittal lumbar alignment. Our purpose is to investigate the sensitivity and specificity of lumbar sagittal radiographic alignment and modeling variables to identify if these can discriminate between normal controls and CLBP patients. Methods: We conducted a computer analysis of digitized vertebral body corners on lateral lumbar radiographs of normal controls and CLBP patients. Fifty normal controls were attained from a required pre-employment physical examination (29 men; 21 women; mean age of 27.7 ± 8.5 years), with no history of low back pain, a normal spinal examination, no pathologies, anomalies, or instability. Additionally, 50 CLBP patients (29 men; 29.5 ± 8 years of age) were randomly chosen and matched to the characteristics of the controls. The inclusion criteria required no abnormalities on lumbar spine radiographs. The parameters included the following: ARA L1-L5 lordosis, ARA T12-S1 lordosis, Cobb T12-S1, b/a elliptical modelling ratio, sacral base angle (SBA), and S1 posterior tangent to vertical (PTS1). Two measures of pelvic morphology were determined for each person—the angle of pelvic incidence (API) and posterior tangent pelvic incidence angle (PTPIA)—and the relationships between API − ARA T12-S1, API − Cobb T12-S1, and API − ARA L1-5 was determined. Descriptive statistics and correlations among the primary variables were determined. The receiver operating characteristic curves (ROC curves) for primary variables were analyzed. Results: The mean values of LL were statistically different between the normal and CLBP groups (p < 0.001), indicating a hypo-lordotic lumbar spine for the CLBP group. The mean b/a ratio was lower in the chronic pain group (p = 0.0066). The pelvic morphology variables were similar between the groups (p > 0.05). API had a stronger correlation to the SBA and Cobb T12-S1 than PTPIA did, while PTPIA had a stronger correlation to the S1 tangent and ARA T12-S1 than API did. While CLBP patients had a stronger correlation of ARA T12-S1 and Cobb T12-S1 relative to the pelvic morphology, they also had a reduced correlation of ARA L1-L5 lordosis relative to their SBA and pelvic morphology measures. API − T12-S1, API − L1-L5, and API − Cobb T12-S1 were statistically different between the groups, p < 0.001. Using ROC curve analyses, it was identified that ARA L1-L5 lordosis of 36° and ARA T12-S1 of 68° have a good sensitivity and specificity to discriminate between normal and CLBP patients. ROC curve analyses identified that lordosis ARAT12-S1 < 68° (AUC = 0.83), lordosis ARAL1-L5 < 36° (AUC = 0.78), API − ARA T12-S1 < −18° (AUC = 0.75), API − ARAL1-L5 > 35° (AUC = 0.71), and API − Cobb T12-S1 < −5° (AUC = 0.69) had moderate to good discrimination between groups (AUC = 0.83, 0.78, 0.75, and 0.72). Conclusions: Pelvic morphology is similar between normal and CLBP patients. CLBP patients have an abnormal ‘fit’ of their API − ARAT12-S1 and L1-L5 lumbar lordosis relative to their pelvic morphology and sacral tilt shown as a hypolordosis. Full article

Background: Identifying skeletal remains has been and will remain a challenge for forensic experts and forensic anthropologists, especially in disasters with multiple victims or skeletal remains in an advanced stage of decomposition. This study examined the performance of two machine learning (ML) algorithms in predicting the person’s sex based only on the morphometry of L1–L5 lumbar vertebrae collected recently from Romanian individuals. The purpose of the present study was to assess whether by using the machine learning (ML) techniques one can obtain a reliable prediction of sex in forensic identification based only on the parameters obtained from the metric analysis of the lumbar spine. Method: This paper built and tuned predictive models with two of the most popular techniques for classification, RF (random forest) and XGB (xgboost). Both series of models used cross-validation and a grid search to find the best combination of hyper-parameters. The best models were selected based on the ROC_AUC (area under curve) metric. Results: The L1–L5 lumbar vertebrae exhibit sexual dimorphism and can be used as predictors in sex prediction. Out of the eight significant predictors for sex, six were found to be particularly important for the RF model, while only three were determined to be important by the XGB model. Conclusions: Even if the data set was small (149 observations), both RF and XGB techniques reliably predicted a person’s sex based only on the L1–L5 measurements. This can prove valuable, especially when only skeletal remains are available. With minor adjustments, the presented ML setup can be transformed into an interactive web service, freely accessible to forensic anthropologists, in which, after entering the L1–L5 measurements of a body/cadaver, they can predict the person’s sex. Full article

Pain generator-based lumbar spinal decompression surgery is the backbone of modern spine care. In contrast to traditional image-based medical necessity criteria for spinal surgery, assessing the severity of neural element encroachment, instability, and deformity, staged management of common painful degenerative lumbar spine conditions is likely to be more durable and cost-effective. Targeting validated pain generators can be accomplished with simplified decompression procedures associated with lower perioperative complications and long-term revision rates. In this perspective article, the authors summarize the current concepts of successful management of spinal stenosis patients with modern transforaminal endoscopic and translaminar minimally invasive spinal surgery techniques. They represent the consensus statements of 14 international surgeon societies, who have worked in collaborative teams in an open peer-review model based on a systematic review of the existing literature and grading the strength of its clinical evidence. The authors found that personalized clinical care protocols for lumbar spinal stenosis rooted in validated pain generators can successfully treat most patients with sciatica-type back and leg pain including those who fail to meet traditional image-based medical necessity criteria for surgery since nearly half of the surgically treated pain generators are not shown on the preoperative MRI scan. Common pain generators in the lumbar spine include (a) an inflamed disc, (b) an inflamed nerve, (c) a hypervascular scar, (d) a hypertrophied superior articular process (SAP) and ligamentum flavum, (e) a tender capsule, (f) an impacting facet margin, (g) a superior foraminal facet osteophyte and cyst, (h) a superior foraminal ligament impingement, (i) a hidden shoulder osteophyte. The position of the key opinion authors of the perspective article is that further clinical research will continue to validate pain generator-based treatment protocols for lumbar spinal stenosis. The endoscopic technology platform enables spine surgeons to directly visualize pain generators, forming the basis for more simplified targeted surgical pain management therapies. Limitations of this care model are dictated by appropriate patient selection and mastering the learning curve of modern MIS procedures. Decompensated deformity and instability will likely continue to be treated with open corrective surgery. Vertically integrated outpatient spine care programs are the most suitable setting for executing such pain generator-focused programs. Full article

In many fields of spinal health care, efforts have been made to offer individualized products and therapy tailored to the patient. Therefore, the prevailing alignment of the spine must be considered, which varies from person to person and depends on the movement and loading situation. With the help of patient-specific simulation models of the spine, the geometrical parameters in a specific body position can be analyzed, and the load situation of the spinal structures during dynamic processes can be assessed. However, to enable the future usability of such simulation models in medical reality, as many patient-specific conditions as possible need to be considered. Another critical requirement is that simulation models must be quickly and easily created for use in clinical routine. Building new or adapting existing spine multibody simulation (MBS) models is time-consuming due to their complex structure. To overcome this limitation, we developed a simple, efficient method by which to automatically adjust the lumbar curvature orientation of the spine model. The method extracts a new 3D lordosis curve from patient-specific data in the preprocessing step. Then the vertebrae and all linked spinal structures of an existing spinal simulation model are transformed so that the lumbar lordosis follows the curve obtained in the first part of the method. To validate the proposed approach, three independent experts measured the Cobb angle in the source and the generated spine alignments. We calculated a mean absolute error of 1.29° between the generated samples and the corresponded ground truth. Furthermore, the minor deviation in the root mean square error (RMSE) of 0.0012 m² between the areas under the alignment curves in the original and target lordosis curvatures indicated the accuracy of the proposed method. The proposed method demonstrated that a new patient-specific simulation model can be generated in a short time from any suitable data source. Full article

Background: Endoscopically visualized spine surgery has become an essential tool that aids in identifying and treating anatomical spine pathologies that are not well demonstrated by traditional advanced imaging, including MRI. These pathologies may be visualized during endoscopic lumbar decompression (ELD) and categorized into primary pain generators (PPG). Identifying these PPGs provides crucial information for a successful outcome with ELD and forms the basis for our proposed personalized spine care protocol (SpineScreen). Methods: a prospective study of 412 patients from 7 endoscopic practices consisting of 207 (50.2%) males and 205 (49.8%) females with an average age of 63.67 years and an average follow-up of 69.27 months was performed to compare the durability of targeted ELD based on validated primary pain generators versus image-based open lumbar laminectomy, and minimally invasive lumbar transforaminal interbody fusion (TLIF) using Kaplan-Meier median survival calculations. The serial time was determined as the interval between index surgery and when patients were censored for additional interventional and surgical treatments for low back-related symptoms. A control group was recruited from patients referred for a surgical consultation but declined interventional and surgical treatment and continued on medical care. Control group patients were censored when they crossed over into any surgical or interventional treatment group. Results: of the 412 study patients, 206 underwent ELD (50.0%), 61 laminectomy (14.8%), and 78 (18.9%) TLIF. There were 67 patients in the control group (16.3% of 412 patients). The most common surgical levels were L4/5 (41.3%), L5/S1 (25.0%), and L4-S1 (16.3%). At two-year f/u, excellent and good Macnab outcomes were reported by 346 of the 412 study patients (84.0%). The VAS leg pain score reduction was 4.250 ± 1.691 (p < 0.001). No other treatment during the available follow-up was required in 60.7% (125/206) of the ELD, 39.9% (31/78) of the TLIF, and 19.7% (12/61 of the laminectomy patients. In control patients, only 15 of the 67 (22.4%) control patients continued with conservative care until final follow-up, all of which had fair and poor functional Macnab outcomes. In patients with Excellent Macnab outcomes, the median durability was 62 months in ELD, 43 in TLIF, and 31 months in laminectomy patients (p < 0.001). The overall survival time in control patients was eight months with a standard error of 0.942, a lower boundary of 6.154, and an upper boundary of 9.846 months. In patients with excellent Macnab outcomes, the median durability was 62 months in ELD, 43 in TLIF, and 31 months in laminectomy patients versus control patients at seven months (p < 0.001). The most common new-onset symptom for censoring was dysesthesia ELD (9.4%; 20/206), axial back pain in TLIF (25.6%;20/78), and recurrent pain in laminectomy (65.6%; 40/61) patients (p < 0.001). Transforaminal epidural steroid injections were tried in 11.7% (24/206) of ELD, 23.1% (18/78) of TLIF, and 36.1% (22/61) of the laminectomy patients. The secondary fusion rate among ELD patients was 8.8% (18/206). Among TLIF patients, the most common additional treatments were revision fusion (19.2%; 15/78) and multilevel rhizotomy (10.3%; 8/78). Common follow-up procedures in laminectomy patients included revision laminectomy (16.4%; 10/61), revision ELD (11.5%; 7/61), and multilevel rhizotomy (11.5%; 7/61). Control patients crossed over into ELD (13.4%), TLIF (13.4%), laminectomy (10.4%) and interventional treatment (40.3%) arms at high rates. Most control patients treated with spinal injections (55.5%) had excellent and good functional outcomes versus 40.7% with fair and poor (3.7%), respectively. The control patients (93.3%) who remained in medical management without surgery or interventional care (14/67) had the worst functional outcomes and were rated as fair and poor. Conclusions: clinical outcomes were more favorable with lumbar surgeries than with non-surgical control groups. Of the control patients, the crossover rate into interventional and surgical care was 40.3% and 37.2%, respectively. There are longer symptom-free intervals after targeted ELD than with TLIF or laminectomy. Additional intervention and surgical treatments are more often needed to manage new-onset postoperative symptoms in TLIF- and laminectomy compared to ELD patients. Few ELD patients will require fusion in the future. Considering the rising cost of surgical spine care, we offer SpineScreen as a simplified and less costly alternative to traditional image-based care models by focusing on primary pain generators rather than image-based criteria derived from the preoperative lumbar MRI scan. Full article

Background: The aim of the study was to assess the influence of both physical activity, such as running and dancing, and the personal characteristics of the studied women on the occurrence and progression of premenstrual disorder (PMD). Methods: We surveyed 414 women aged 22–48 who were experiencing the menstrual cycle but not using hormonal contraception. There were two physically active groups, runners (N = 215) and Argentine tango dancers (N = 94), and there was one group not undertaking any physical activity—the control group (N = 104). The research was conducted using the researchers’ own questionnaire. Results: The number of days of PMD symptoms in the tango vs. runner vs. control groups are as follows: pre-bleeding (mean: 4.14 vs. 4.86 vs. 4.85; p = 0.024), after the onset of bleeding (mean: 1.76 vs. 2.39 vs. 2.16; p = 0.001), and in total (mean: 5.94 vs. 7.25 vs. 7.01; p < 0.001). The regression analysis results without grouping results are as follows: the number of days of symptoms before bleeding and menarche (B: −0.16; 95% CIs: from −0.29 to −0.04; p = 0.011), the total duration of symptoms and menarche (B: −0.17; 95% CIs: from −0.32 to −0.01; p = 0.036), lower abdominal pain and age (B: −0.05; 95% CIs: 0.92–0.98; p = 0.002), diarrhoea (B: −0.08; 95% CIs: 0.88–0.97; p < 0.001), tearfulness, depressive states and age (B: −0.06; 95% CIs: 0.91–0.97; p < 0.001), skin problems and age (B: −0.05; 95% CIs: 0.92–0.98; p = 0.004), joint pain and age (B: −0.09; 95% CIs: 0.86–0.96; p = 0.001), pain in the lumbar spine (B: −0.06, 95% CIs: 0.91–0.98; p = 0.001), water retention and BMI (B: 0.09; 95% CIs: 0.92–0.98; p = 0.007), and water retention and menarche (B: −0.19; 95% CIs: 0.73–0.94; p = 0.003). Information: generally there is one regression model, we have several here, we have a bit the description. Conclusions: Physical activity such as dancing (tango) shortens the duration of PMD symptoms but does not completely eliminate them. Running does not have as beneficial an effect on symptom relief as dancing. Current age, age when menstruation began (menarche), and BMI were revealed to be important factors influencing the symptoms of premenstrual disorders. Full article

Finite element (FE) modeling of the passive ligamentous spine is widely used to assess various biomechanical behaviors. Currently, FE models that incorporate the vertebrae, ligaments, and the personalized geometry of the bony spine may be used in conjunction with external loads from the muscles. However, while the muscles place a load (moment) on the spine and support it simultaneously, the effect of the passive support from the adjacent spinal muscles has not been considered. This study thus aims to investigate the effect of passive support from the psoas major, quadratus lumborum, and erector muscles on the range of motion (RoM) and intradiscal pressure (IDP) of the lumbar spine. Various L2-sacrum spinal models that differed only in their muscle properties were constructed and loaded with a pure moment (2.5–15.0 Nm) alone or combined with a compressive (440 or 1000 N) follower load. The RoM and IDP of the model that excluded the effect of muscles closely matched previous FE results under the corresponding load conditions. When the muscles (40–160 kPa) were included in the FE model, the RoM at L2 was reduced by up to 6.57% under a pure moment (10 Nm). The IDP was reduced by up to 6.45% under flexion and 6.84% under extension. It was also found that the erector muscles had a greater effect than the psoas major and quadratus muscles. Full article