Diagnosis Of Osteoporotic Vertebral Fractures Research Articles

Radiological diagnosis of prevalent osteoporotic vertebral fracture on radiographs: an interim consensus from a group of experts of the ESSR osteoporosis and metabolism subcommittee.

When a low-energy trauma induces an acute vertebral fracture (VF) with clinical symptoms, a definitive diagnosis of osteoporotic vertebral fracture (OVF) can be made. Beyond that, a "gold" radiographic standard to distinguish osteoporotic from non-osteoporotic VFs does not exist. Fracture-shaped vertebral deformity (FSVD) is defined as a deformity radiographically indistinguishable from vertebral fracture according to the best of the reading radiologist's knowledge. FSVD is not uncommon among young populations with normal bone strength. FSVD among an older population is called osteoporotic-like vertebral fracture (OLVF) when the FSVD is likely to be associated with compromised bone strength. In more severe grade deformities or when a vertebra is collapsed, OVF diagnosis can be made with a relatively high degree of certainty by experienced readers. In "milder" cases, OVF is often diagnosed based on a high probability rather than an absolute diagnosis. After excluding known mimickers, singular vertebral wedging in older women is statistically most likely an OLVF. For older women, three non-adjacent minimal grade OLVF (< 20% height loss), one minimal grade OLVF and one mild OLVF (20-25% height loss), or one OLVF with ≥ 25% height loss, meet the diagnosis of osteoporosis. For older men, a single OLVF with < 40% height loss may be insufficient to suggest the subject is osteoporotic. Common OLVF differential diagnoses include X-ray projection artifacts and scoliosis, acquired and developmental short vertebrae, osteoarthritic wedging, oncological deformities, deformity due to high-energy trauma VF, lateral hyperosteogeny of a vertebral body, Cupid's bow, and expansive endplate, among others.

Factors influencing vertebral collapse in osteoporotic vertebral fractures: a case-control study of symptomatic patients attended in the emergency department.

To identify risk factors for collapse of osteoporotic vertebral fractures (OVF) on computed tomography (CT) and conventional radiography (CR). This is a retrospective case-control study including a series of patients with OVF diagnosed at the emergency department of our institution from January to September 2019. Inclusion criteria were to have standing CR and supine CT within 2weeks after the diagnosis of OVF and a follow-up CR at 6months or later. We evaluated different imaging measurements at the initial diagnostic examinations, including vertebral height loss, local kyphosis, vertebral density, and fracture type according to the grading systems of Genant, Sugita, Association of Osteosynthesis (AO) Spine, and the German Society for Orthopaedics and Trauma. Vertebral collapse was defined as loss of ≥ 50% of vertebral area or height. Cases and controls were defined as OVFs which collapse and do not collapse, respectively, on follow-up. Fifty-six patients were included in the study, with a mean age of 72.6 ± 1.2years, including 48 women. Twenty-five (44.6%) OVFs developed collapse on follow-up. None of the fracture classification systems were found to be predictive of collapse. Multivariate analysis showed that older age, increased density ratio (≥ 2) between the fractured and non-fractured vertebral bodies, and a ≥ 6% difference in posterior vertebral height (PVH) loss between standing CR and supine CT exhibited 88% discriminative power in predicting vertebral collapse. Age over 72.5years, a density ratio ≥ 2 between the fractured and non-fractured vertebral bodies, and a difference equal to or higher than 6% in PVH loss between standing CR and supine CT, are risk factors for developing vertebral collapse after OVF.

Prediction of Progressive Collapse in Osteoporotic Vertebral Fractures Using Conventional Statistics and Machine Learning.

Retrospective cohort study. The objective of this study was to determine prognostic factors for the progression of osteoporotic vertebral fracture (OVF) following conservative treatment. Few studies have evaluated factors associated with progressive collapse (PC) of OVFs. Furthermore, machine learning has not been applied in this context. The study involved the PC and non-PC groups based on a compression rate of 15%. Clinical data, fracture site, OVF shape, Cobb angle, and anterior wedge angle of the fractured vertebra were evaluated. The presence of intravertebral cleft and the type of bone marrow signal change were analyzed using magnetic resonance imaging. Multivariate logistic regression analysis was performed to identify prognostic factors. In machine learning methods, decision tree and random forest models were used. There were no significant differences in clinical data between the groups. The proportion of fracture shape ( P <0.001) and bone marrow signal change ( P =0.01) were significantly different between the groups. Moderate wedge shape was frequently observed in the non-PC group (31.7%), whereas the normative shape was most common in the PC group (54.7%). The Cobb angle and anterior wedge angle at diagnosis of OVFs were higher in the non-PC group (13.2±10.9, P =0.001; 14.3±6.6, P <0.001) than in the PC group (10.3±11.8, 10.4±5.5). The bone marrow signal change at the superior aspect of the vertebra was more frequently found in the PC group (42.5%) than in the non-PC group (34.9%). Machine learning revealed that vertebral shape at initial diagnosis was a main predictor of progressive vertebral collapse. The initial shape of the vertebra and bone edema pattern on magnetic resonance imaging appear to be useful prognostic factors for progressive collapse in osteoporotic vertebral fractures.

Diagnostic value of SPECT/CT bone imaging in fresh osteoporotic vertebral compression fractures.

To investigate the diagnostic value of single photon emission computed tomography/computed tomography (SPECT/CT) bone imaging in fresh osteoporotic vertebral compression fractures. The imaging data of 30 patients with osteoporosis (10 males and 20 females; aged 50~93 years) who received SPECT/CT bone imaging and spinal magnetic resonance imaging (MRI) in our hospital from June 2018 to June 2021 were analyzed retrospectively. Single photon emission tomography/CT bone imaging and spinal MRI were analyzed by two experienced specialists. Kappa consistency test and pairing were used for the diagnostic results of the two groups χ2 test (McNemar test) for statistical analysis. Fifty one vertebral fractures were detected in 30 patients, including 41 fresh vertebral fractures and 10 old vertebral fractures by SPECT/CT bone imaging; MRI revealed 40 fresh vertebral fractures and 11 old vertebral fractures. Single photon emission tomography/CT bone imaging and spinal MRI had good consistency in the diagnosis of fresh osteoporotic vertebral compression fractures (Kappa=0.820, P<0.001), and there was no significant difference between the two imaging methods in the diagnosis of osteoporotic vertebral fractures (P=1.000). The value of SPECT/CT in the localization and characterization of osteoporotic fresh vertebral compression fractures is similar to that of MRI. At the same time, SPECT/CT can also find some bone lesions that cannot be displayed by conventional MRI. Especially when patients have MRI contraindications, SPECT/CT bone imaging can be used as the preferred imaging method.

"Opportunistic Diagnosis of Osteoporotic Vertebral Fractures on Imaging Studies performed for Alternative Clinical Indications"

"Opportunistic Diagnosis of Osteoporotic Vertebral Fractures on Imaging Studies performed for Alternative Clinical Indications"

Clinical diagnosis of vertebral fractures in osteoporosis (literature review)

Background. Osteoporosis is a common pathology among older age groups. Vertebral fractures are one of the most severe complications of osteoporosis, as they lead to a decrease in the quality of life, disability and increased mortality. The risk of vertebral fractures increases with age, especially in those who have already has a fracture of this localization. To improve the prognosis in this category of patients, early detection, treatment of patients with fractures, as well as prevention of new fractures, are important. At the same time, the diagnosis of osteoporotic vertebral fractures presents certain difficulties due to the variability of their clinical manifestations, which often leads to insufficient detection, wrong diagnosis and, as a consequence, to the lack of adequate treatment.Purpose of the review. To conduct a literature search to evaluate the clinical diagnosis of osteoporotic vertebral fractures.Conclusion. There was no single highly specific and at the same time sensitive clinical symptom of osteoporotic vertebral fractures. Back pain remains a relatively nonspecific symptom in vertebral fractures. The most specific symptoms: kyphosis and height loss have a high predictive value only when they are significantly changed. Thus, vertebral fractures should be suspected if height decreased more than 2.0 cm per year or more than 4.0 cm per life, if the patient does not reach the wall with his head or if the «rib to pelvis» distance is two fingers or less. The combination of clinical symptoms with the assessment of risk factors and bone mineral density has the greatest clinical significance. If a vertebral fracture is clinically suspected, it is advisable to perform an X-ray of the thoracic and lumbar spine, since the localization of pain indicated by the patient may not correspond to the localization of the fracture.

Using artificial intelligence to diagnose fresh osteoporotic vertebral fractures on magnetic resonance images

Background ContextAccurate diagnosis of osteoporotic vertebral fracture (OVF) is important for improving treatment outcomes; however, the gold standard has not been established yet. A deep-learning approach based on convolutional neural network (CNN) has attracted attention in the medical imaging field. PurposeTo construct a CNN to detect fresh OVF on magnetic resonance (MR) images. Study Design/SettingRetrospective analysis of MR images Patient SampleThis retrospective study included 814 patients with fresh OVF. For CNN training and validation, 1624 slices of T1-weighted MR image were obtained and used. Outcome MeasureWe plotted the receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) in order to evaluate the performance of the CNN. Consequently, the sensitivity, specificity, and accuracy of the diagnosis by CNN and that of the two spine surgeons were compared. MethodsWe constructed an optimal model using ensemble method by combining nine types of CNNs to detect fresh OVFs. Furthermore, two spine surgeons independently evaluated 100 vertebrae, which were randomly extracted from test data. ResultsThe ensemble method using VGG16, VGG19, DenseNet201, and ResNet50 was the combination with the highest AUC of ROC curves. The AUC was 0.949. The evaluation metrics of the diagnosis (CNN/surgeon 1/surgeon 2) for 100 vertebrae were as follows: sensitivity: 88.1%/88.1%/100%; specificity: 87.9%/86.2%/65.5%; accuracy: 88.0%/87.0%/80.0%. ConclusionsIn detecting fresh OVF using MR images, the performance of the CNN was comparable to that of two spine surgeons.

Opportunistic diagnosis of osteoporotic vertebral fractures on standard imaging performed for alternative indications.

Osteoporotic vertebral fractures (VFs) are the most common type of osteoporotic fracture. Patients with VF are at increased risk of hip fractures or additional VFs, both of which contribute to patient morbidity and mortality. Early diagnosis of VFs is essential so patients can be prescribed appropriate medical therapy.Most patients with clinical suspicion for VF have an X-ray of the spine. Many VFs are invisible on X-ray and require further imaging. CT can provide excellent bony detail but uses high doses of ionising radiation. MRI provides excellent soft tissue detail and can distinguish old from new fractures in addition to differentiating osteoporotic VFs from other causes of back pain. Bone scans have a limited role due to poor specificity.The literature suggests that radiologists frequently miss or do not report VFs when imaging is requested for an alternative clinical indication and when there is no clinical suspicion of VF. Common examples include failure to identify VFs on lateral chest X-rays, sagittal reformats of CT thorax and abdomen, lateral localizers on MRI and scout views on CT.Failure to diagnose a VF is a missed opportunity to improve management of osteoporosis and reduce risk of further fractures. This article discusses the role of radiographs, CT, MRI and bone scintigraphy in the assessment and recognition of osteoporotic fractures. This article focuses on opportunistic diagnosis of VFs on imaging studies that are performed for other clinical indications. It does not discuss use of dual energy X-ray absorptiometry which is a specific imaging modality for osteoporosis.

The impact of magnetic resonance imaging in the diagnostic and classification process of osteoporotic vertebral fractures

IntroductionStandard radiographs are still considered as the gold standard for the early assessment of thoraco-lumbar osteoporotic vertebral fractures (OVFs), although several studies demonstrated superior accuracy of magnetic resonance imaging (MRI) in the diagnostic process of OVFs. The aim of this study was to quantify the misdiagnosis rate of OVFs and analyse the impact of MRI on early diagnosis and classification, compared to standard radiographs alone. Materials and methodsA total of 173 patients were enrolled in this study. All participants were 55 years of age or older (60 years for men) and complained acute back pain with suspected thoracolumbar OVFs without history of high-energy trauma. Diagnosis of OVF was initially performed on standard radiographs obtained in the emergency room. Then, all the patients underwent MRI scan with short-tau inversion recovery (STIR) sequencing within 7 days. We compared the level and number of fractures identified on standard radiographs with the MRI scan results. The discordance between radiographic and MRI diagnosis was quantified. Fractures were classified according to AO Spine Classification. ResultsMean age of the study participant was 74.2 years (range 55–92). They were 100 males and 73 females. MRI modified initial diagnosis in 52% (90/173) of our patients: in 43.9% of patients MRI identified one or more new thoracolumbar fracture. In 14 cases (8.1%) MRI disproved the evidence of any thoracolumbar fracture, even those recognized at plain X-rays. Bone bruise was detected by MRI in 19 vertebral bodies in 8 patients (4.6%) at levels that were classified as unremarkable on X-ray alone. In addition, 63 patients (36.4%) presented a total of 93 old fractures. The classification of fracture pattern after MRI changed in 28.90% of the patients (changes mostly involved AO type A1 patterns). ConclusionsUnderdiagnosis of osteoporotic vertebral fractures is a common problem due to a lack of radiographic detection. Our results showed that the extensive use of MRI imaging allows better accuracy in the diagnostic process and in the classification assessment, compared to conventional radiographs. Further investigation should provide additional information about the impact of early MRI on treatment and management of elderly patients with suspected OVFs, including the decision to hospitalize or not, and how it could affect clinical outcome and social costs.

CT-scout based, semi-automated vertebral morphometry after digital image enhancement

IntroductionRadiographic diagnosis of osteoporotic vertebral fracture is necessary to reduce its substantial associated morbidity. Computed tomography (CT) scout has recently been demonstrated as a reliable technique for vertebral fracture diagnosis. Software assistance may help to overcome some limitations of that diagnostics. We aimed to evaluate whether digital image enhancement improved the capacity of one of the existing software to detect fractures semi-automatically. MethodsCT scanograms of patients suffering from osteoporosis, with or without vertebral fractures were analyzed. The original set of CT scanograms were triplicated and digitally modified to improve edge detection using three different techniques: SHARPENING, UNSHARP MASKING, and CONVOLUTION. ResultsThe manual morphometric analysis identified 1485 vertebrae, 200 of which were classified as fractured. Unadjusted morphometry (AUTOMATED with no digital enhancement) found 63 fractures, 33 of which were true positive (i.e., it correctly identified 52% of the fractures); SHARPENING detected 57 fractures (30 true positives, 53%); UNSHARP MASKING yielded 30 (13 true positives, 43%); and CONVOLUTION found 24 fractures (9 true positives, 38%). The intra-reader reliability for height ratios did not significantly improve with image enhancement (kappa ranged 0.22–0.41 for adjusted measurements and 0.16–0.38 for unadjusted). Similarly, the inter-reader agreement for prevalent fractures did not significantly improve with image enhancement (kappa 0.29–0.56 and −0.01 to 0.23 for adjusted and unadjusted measurements, respectively). ConclusionsOur results suggest that digital image enhancement does not improve software-assisted vertebral fracture detection by CT scout.

META: an MRI-based scoring system differentiating metastatic from osteoporotic vertebral fractures

Background contextMagnetic resonance imaging (MRI) is useful for the differential diagnosis of osteoporotic vertebral fractures (OVFs) and metastatic vertebral fractures (MVFs), but no single finding is absolutely conclusive. PurposeThe purpose of the present study was to create a scoring system to facilitate the correct diagnosis of MVFs by integrating several MRI findings. Study designThis is a retrospective and single-center observational study that attempts to create a diagnostic scoring system by discriminant analysis. Patients sampleWe included 100 OVFs and 100 MVFs in thoracolumbar vertebrae of which MR images were obtained within 60 days from the suspected time of fractures. Outcome measuresThe sensitivity and specificity of known important MRI findings were assessed, and the classification accuracy of the scoring system was investigated. MethodsSeven MRI findings of these fractures were analyzed to evaluate their sensitivity and specificity. Using these findings as variables, discriminant analysis was performed in 140 fractures as a training set, and the classification accuracy was calculated in the remaining 60 fractures as a test set. Additionally, the images of these 60 fractures were reviewed by another blinded reviewer to investigate the interobserver reliability of each finding. ResultsAll findings had high specificity with low-to-moderate sensitivity. Eight variables were selected in the final discriminant function. A simpler scoring system (MRI Evaluation Totalizing Assessment [META]) was created by approximating the coefficients and the constant term by integral numbers. The classification accuracy was calculated to be 96.6% in the test set. The interobserver reliability of the key findings varied, but the final discrimination conducted by META had the high agreement between the two reviewers (κ=0.93). ConclusionsThis novel scoring system, META, could prove to be a useful tool for the differential diagnosis of OVFs and MVFs. It is simple and physician friendly, yet highly accurate.

Is short vertebral height always an osteoporotic fracture? The Osteoporosis and Ultrasound Study (OPUS)

Introduction and hypothesis: Diagnosis of prevalent osteoporotic vertebral fracture is complicated by normal or developmental variation in vertebral shape or size and non-osteoporotic deformities that appear to have ‘reduced’ height. Using our visual approach, the algorithm-based qualitative method (ABQ) a vertebra with apparent “reduced” height without evidence of osteoporotic endplate depression is classified as non-osteoporotic short vertebral height (SVH). We aimed to determine whether ABQ classification of SVH represents true or false negative diagnosis of osteoporotic vertebral fracture, by testing the associations with clinical outcomes of osteoporosis or vertebral fracture. Methods: The ABQ method was used to assess spinal radiographs acquired at baseline for a subset of 904 postmenopausal women participating in the Osteoporosis and Ultrasound Study (OPUS). The sample was enriched with vertebral fracture cases. Subjects were categorized by ABQ diagnosis as (i) normal, (ii) non-osteoporotic short vertebral height (SVH) or (iii) osteoporotic vertebral fracture. Results: Women were classified by ABQ as follows: osteoporotic vertebral fracture, n = 231; SVH, n = 376 and normal, n = 297. Women with vertebral fracture were older, with lower height, weight and height loss than those classified as SVH or normal. Women with SVH were heavier and older, with greater historical height loss than normal women. Age-adjusted SD units ( z-scores) for BMD were lower than expected among women with osteoporotic vertebral fracture, but not among those with SVH. There was a significant association between diagnosis of osteoporotic vertebral fracture and history of low-trauma non-vertebral and vertebral fracture ( p < 0.001, odds ratios = 3.2 and 20.6, respectively). There was also an association between diagnosis of SVH and previous low-trauma non-vertebral fracture ( p < 0.05, odds ratio = 1.7). Conclusions: Short vertebral height without evidence of central endplate fracture in postmenopausal women is largely unrelated to osteoporosis. Quantitative morphometry should not be used alone for the assessment of vertebral fracture in clinical decision making: we recommend differential diagnosis of morphometric vertebral deformities by an expert reader to rule out non-osteoporotic deformities with short vertebral height.

“Occult” Osteoporotic Vertebral Fractures

Retrospective observational study. We report our experience with patients who presented with osteoporotic vertebral fractures with no visible deformation of vertebral body. The diagnosis of osteoporotic vertebral fractures largely relies on the observation of vertebral deformations on plain radiographs, termed vertebral collapses. There are no data on the characteristics, or indeed of the reality, of osteoporotic vertebral fractures with no significant deformation of the vertebral body. We retrospectively analyzed cases that presented with acute back pain with no initial deformation of the vertebral body on plain radiographs, and later proved to be fresh osteoporotic vertebral body fractures. All cases met each of the following criteria: 1) The incriminated vertebra appeared normal on initial radiographs (Genant's Grade 0 deformation). 2) The diagnosis of fresh vertebral body fracture was confirmed by MRI. 3) The diagnosis of osteoporosis was made by the combination of established osteoporosis, ruling out of underlying disease, and follow-up. We observed 21 fractures in 16 patients (11 female/5 male; mean age, 72 years). Most of these fractures affected the lumbar spine (14 of 21 occurred at L2-L5). Osteoporosis was known beforehand in 9 patients and newly diagnosed in 7 patients. At follow-up, radiographs were obtained for 19 of 21 fractures: in 15 cases, the vertebral fracture developed a vertebral collapse (Genant's Grade > or = 0.5) in a mean of 12.5 weeks (range, 4-24 weeks); in the 4 remaining cases, the vertebra remained normal. All cases had a clinically favorable outcome. Osteoporotic vertebral fractures with no sign of vertebral collapse on initial radiographs do indeed exist. They are analogous to occult stress fractures well known in other skeletal sites. They must not be misdiagnosed as malignant lesions.

Diagnosis of osteoporotic vertebral fractures: importance of recognition and description by radiologists.

Diagnosis of osteoporotic vertebral fractures: importance of recognition and description by radiologists.