Discrimination between Malignant and Benign Vertebral Fractures Using Magnetic Resonance Imaging

An MRI-Based Radiomics Nomogram for Differentiation of Benign and Malignant Vertebral Compression Fracture

RATIONALE AND OBJECTIVES

This study aimed to develop and validate a magnetic resonance imaging (MRI)-based radiomics nomogram combining radiomics signatures and clinical factors to differentiate between benign and malignant vertebral compression fractures (VCFs).

MATERIALS AND METHODS

A total of 189 patients with benign VCFs (n = 112) or malignant VCFs (n = 77) were divided into training (n = 133) and validation (n = 56) cohorts. Radiomics features were extracted from MRI T1-weighted images and short-TI inversion recovery images to develop the radiomics signature, and the Rad score was constructed using least absolute shrinkage and selection operator regression. Demographic and MRI morphological characteristics were assessed to build a clinical factor model using multivariate logistic regression analysis. A radiomics nomogram was constructed based on the Rad score and independent clinical factors. Finally, the diagnostic performance of the radiomics nomogram, clinical model, and radiomics signature was validated using receiver operating characteristic and decision curve analysis (DCA).

RESULTS

Six features were used to build a combined radiomics model (combined-RS). Pedicle or posterior element involvement, paraspinal mass, and fluid sign were identified as the most important morphological factors for building the clinical factor model. The radiomics signature was superior to the clinical model in terms of the area under the curve (AUC), accuracy, and specificity. The radiomics nomogram integrating the combined-RS, pedicle or posterior element involvement, paraspinal mass, and fluid sign achieved favorable predictive efficacy, generating AUCs of 0.92 and 0.90 in the training and validation cohorts, respectively. The DCA indicated good clinical usefulness of the radiomics nomogram.

CONCLUSION

The MRI-based radiomics nomogram, combining the radiomics signature and clinical factors, showed favorable predictive efficacy for differentiating benign from malignant VCFs.

Geriatric spine fractures - Demography, changing trends, challenges and special considerations: A narrative review

The aim of this manuscript was to summarize the demography and changing trends of geriatric spinal injuries and to enumerate the challenges and special considerations in the care of geriatric spinal injuries. PubMed, Scopus and Embase databases were searched for literature on geriatric spine fractures using MeSH terms 'aged', 'aged, 80 and over', 'elderly', 'spinal fracture/epidemiology', spinal fracture/therapy∗' and keywords pertaining to the same. The search results were screened for appropriate articles and reviewed. There is a high community prevalence of elderly vertebral fractures ranging from 18% to as high as 51%. The proportion of older patients among the spinal injured is rising as well. There is a higher chance of missing spinal injuries in the elderly and clinical guidelines may not be applicable to this patient group. Classification and surgical treatment are different from younger adult counterparts as the elderly osteoporotic spine behaves differently biomechanically. There is a high incidence of respiratory complications both for surgically and conservatively managed groups. Older age generally is associated with a higher complication rate including mortality.

ACR Appropriateness Criteria® Management of Vertebral Compression Fractures: 2022 Update

Vertebral compression fractures (VCFs) can have a variety of etiologies, including trauma, osteoporosis, or neoplastic infiltration. Osteoporosis related fractures are the most common cause of VCFs and have a high prevalence among all postmenopausal women with increasing incidence in similarly aged men. Trauma is the most common etiology in those >50 years of age. However, many cancers, such as breast, prostate, thyroid, and lung, have a propensity to metastasize to bone, which can lead to malignant VCFs. Indeed, the spine is third most common site of metastases after lung and liver. In addition, primary tumors of bone and lymphoproliferative diseases such as lymphoma and multiple myeloma can be the cause of malignant VCFs. Although patient clinical history could help raising suspicion for a particular disorder, the characterization of VCFs is usually referred to diagnostic imaging. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances in which evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Imaging of Bone Marrow: From Science to Practice

The study of the bone marrow may pose important challenges, due to its changing features over the life span, metabolic stress, and in cases of disease or treatment. Bone marrow adipocytes serve as storage tissue, but they also have endocrine and paracrine functions, contributing to local and systemic metabolism.Among different techniques, magnetic resonance (MR) has the benefit of imaging bone marrow directly. The use of advanced MR techniques for bone marrow study has rapidly found clinical applications. Beyond the clinical uses, it has opened up pathways to assess and quantify bone marrow components, establishing the groundwork for further study of its implications in physiologic and pathologic conditions.We summarize the features of the bone marrow as an organ, address the different modalities available for its study, with a special focus on MR advanced techniques and their addition to analysis in recent years, and review some of the challenges in interpreting the appearance of bone marrow.

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet

PURPOSE

To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the ResNet50 algorithm to develop a decision support system.

METHODS

A total of 190 patients, 50 with malignant and 140 with benign fractures, were studied. The visual diagnosis was made by one senior MSK radiologist, one fourth-year resident, and one first-year resident. The MSK radiologist also gave the binary score for 15 qualitative imaging features. Deep learning was implemented using ResNet50, using one abnormal spinal segment selected from each patient as input. The T1W and T2W images of the lesion slice and its two neighboring slices were considered. The diagnostic performance was evaluated using tenfold cross-validation.

RESULTS

The overall reading accuracy was 98, 96, and 66% for the senior MSK radiologist, fourth-year resident, and first-year resident, respectively. Of the 15 imaging features, 10 showed a significant difference between benign and malignant groups with p <  = 0.001. The accuracy achieved by using the ResNet50 deep learning model for the identified abnormal vertebral segment was 92%. Compared to the first-year resident's reading, the model improved the sensitivity from 78 to 94% (p < 0.001) and the specificity from 61 to 91% (p < 0.001).

CONCLUSION

Our deep learning-based model may provide information to assist less experienced clinicians in the diagnosis of spinal fractures on MRI. Other findings away from the vertebral body need to be considered to improve the model, and further investigation is required to generalize our findings to real-world settings.

Risk factors for deep vein thrombosis even using low-molecular-weight heparin after total knee arthroplasty

Background

With an increase in deep vein thrombosis (DVT) following total knee arthroplasty (TKA) in the Asian population, most surgeons today use a form of prophylactic anticoagulant agents in patients after TKA. Nevertheless, DVT occasionally develops even in these patients with prophylaxis. The purpose of this study was to identify the risk factors for DVT after TKA in cases of postoperative low-molecular-weight heparin (LMWH) use.

Methods

We designed a retrospective study with 103 patients who underwent primary TKA. From the second postoperative day, 60 mg of LMWH was subcutaneously injected into the patients daily. On the seventh postoperative day, patients had computed tomography angiography to check whether they had DVT. Regarding risk factors, we investigated patients’ gender, age, surgical site (unilateral/bilateral), body mass index, method of anesthesia, preoperative hypertension, diabetes, hypercholesterolemia status, and prothrombin time/international normalized ratio from electronic medical records. We analyzed the statistical significance of these risk factors.

Results

Statistically significant factors in the single-variable analysis were surgical site (unilateral/bilateral), body mass index, preoperative hypertension status, and anesthesia method. Multiple logistic regression analysis with these factors revealed that the surgical site (unilateral/bilateral, p = 0.024) and anesthesia method (p = 0.039) were significant factors for the occurrence of postoperative DVT after TKA.

Conclusions

Patients undergoing simultaneous bilateral TKAs and patients undergoing TKA with general anesthesia need more attention regarding DVT even with chemoprophylaxis using LMWH after TKA.

Differential diagnosis of benign and malignant vertebral fracture on CT using deep learning

OBJECTIVES

To evaluate the performance of deep learning using ResNet50 in differentiation of benign and malignant vertebral fracture on CT.

METHODS

A dataset of 433 patients confirmed with 296 malignant and 137 benign fractures was retrospectively selected from our spinal CT image database. A senior radiologist performed visual reading to evaluate six imaging features, and three junior radiologists gave diagnostic prediction. A ROI was placed on the most abnormal vertebrae, and the smallest square bounding box was generated. The input channel into ResNet50 network was 3, including the slice with its two neighboring slices. The diagnostic performance was evaluated using 10-fold cross-validation. After obtaining the malignancy probability from all slices in a patient, the highest probability was assigned to that patient to give the final diagnosis, using the threshold of 0.5.

RESULTS

Visual features such as soft tissue mass and bone destruction were highly suggestive of malignancy; the presence of a transverse fracture line was highly suggestive of a benign fracture. The reading by three radiologists with 5, 3, and 1 year of experience achieved an accuracy of 99%, 95.2%, and 92.8%, respectively. In ResNet50 analysis, the per-slice diagnostic sensitivity, specificity, and accuracy were 0.90, 0.79, and 85%. When the slices were combined to ve per-patient diagnosis, the sensitivity, specificity, and accuracy were 0.95, 0.80, and 88%.

CONCLUSION

Deep learning has become an important tool for the detection of fractures on CT. In this study, ResNet50 achieved good accuracy, which can be further improved with more cases and optimized methods for future clinical implementation.

KEY POINTS

• Deep learning using ResNet50 can yield a high accuracy for differential diagnosis of benign and malignant vertebral fracture on CT. • The per-slice diagnostic sensitivity, specificity, and accuracy were 0.90, 0.79, and 85% in deep learning using ResNet50 analysis. • The slices combined with per-patient diagnostic sensitivity, specificity, and accuracy were 0.95, 0.80, and 88% in deep learning using ResNet50 analysis.

Differentiation Between Osteoporotic And Neoplastic Vertebral Fractures: State Of The Art And Future Perspectives

Vertebral fractures are a common condition, occurring in the context of osteoporosis and malignancy. These entities affect a group of patients in the same age range; clinical features may be indistinct and symptoms non-existing, and thus present challenges to diagnosis. In this article, we review the use and accuracy of different imaging modalities available to characterize vertebral fracture etiology, from well-established classical techniques, to the role of new and advanced imaging techniques, and the prospective use of artificial intelligence. We also address the role of imaging on treatment. In the context of osteoporosis, the importance of opportunistic diagnosis is highlighted. In the near future, the use of automated computer-aided diagnostic algorithms applied to different imaging techniques may be really useful to aid on diagnosis.

Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT

OBJECTIVES

To develop and validate a combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT.

METHODS

One hundred sixty-five patients with vertebral compression fractures were allocated to training (n = 110 [62 acute benign and 48 malignant fractures]) and validation (n = 55 [30 acute benign and 25 malignant fractures]) cohorts. Radiomics features (n = 144) were extracted from non-contrast-enhanced CT images. Radiomics score was constructed by applying least absolute shrinkage and selection operator regression to reproducible features. A combined radiomics-clinical model was constructed by integrating significant clinical parameters with radiomics score using multivariate logistic regression analysis. Model performance was quantified in terms of discrimination and calibration. The model was internally validated on the independent data set.

RESULTS

The combined radiomics-clinical model, composed of two significant clinical predictors (age and history of malignancy) and the radiomics score, showed good calibration (Hosmer-Lemeshow test, p > 0.05) and discrimination in both training (AUC, 0.970) and validation (AUC, 0.948) cohorts. Discrimination performance of the combined model was higher than that of either the radiomics score (AUC, 0.941 in training cohort and 0.852 in validation cohort) or the clinical predictor model (AUC, 0.924 in training cohort and 0.849 in validation cohort). The model stratified patients into groups with low and high risk of malignant fracture with an accuracy of 98.2% in the training cohort and 90.9% in the validation cohort.

CONCLUSIONS

The combined radiomics-clinical model integrating clinical parameters with radiomics score could predict malignancy in vertebral compression fractures on CT with high discriminatory ability.

KEY POINTS

• A combined radiomics-clinical model was constructed to predict malignancy of vertebral compression fractures on CT by combining clinical parameters and radiomics features. • The model showed good calibration and discrimination in both training and validation cohorts. • The model showed high accuracy in the stratification of patients into groups with low and high risk of malignant vertebral compression fractures.

Differential diagnosis between metastatic and osteoporotic vertebral fractures using sagittal T1-weighted magnetic resonance imaging

BACKGROUND

Magnetic resonance imaging (MRI) is the most helpful for determining the differential diagnosis between metastatic and osteoporotic vertebral fractures; especially whole spine MRI is effective if patients have multiple spinal metastases. However, it is time-consuming to obtain all planes for all metastatic vertebrae. If we can differentiate these metastatic and osteoporotic vertebral fractures based on only one section and signal intensity, it would save time and be effective for patients with pain. This study investigated the usefulness of sagittal T1-weighted MRI findings in differentiating metastatic and osteoporotic vertebral fractures.

METHODS

We retrospectively reviewed patients diagnosed with metastatic or osteoporotic vertebral fractures. Findings characteristic of metastatic fractures were considered: (a) pedicle or posterior element involvement; (b) convex posterior border of the vertebral body; (c) epidural infiltration; and (d) diffuse homogeneous low signal intensity; findings characteristic of osteoporotic compression fractures were also considered: (e) low-signal-intensity band and (f) posterior retropulsion. Chi-square test or Fisher's exact probability test was used to investigate the usefulness of each MRI finding. Intra- and inter-observer reliability analysis was performed.

RESULTS

This study comprised 43 patients with metastases (45 vertebrae) and 118 patients with osteoporotic fractures (156 vertebrae). All findings showed significant difference with each fracture (p-value: <0.01 to 0.03). Although each MRI finding exhibited high intra- and inter-observer reliability (κ: 0.66 to 1.00), finding (c) exhibited low reliability. Finding (a) showed high sensitivity (88.9%) and usefulness for screening, and findings (b), (d), (e), and (f) showed high specificity (90.4%-100%) and usefulness for definitive diagnosis.

CONCLUSIONS

Characteristic findings with sagittal T1-weighted MRI were useful in the differential diagnosis of metastatic and osteoporotic vertebral fractures. To prevent overlooking metastatic fractures with sagittal T1-weighted MRI, findings of the pedicle or posterior element involvement should be focused on because of its reliability and sensitivity.

"Less is better"-always true?

OBJECTIVE

The aim of the study is to try to explain what an overtreatment is and which ones are the possible risks related to an excess of simplification in the medical practice, through the description of an emblematic clinical case.

METHODS

In the present article, we report the case of a female patient aged 57 who complained about lower back pain and crural neuralgia and had a lumbar and sacral magnetic resonance imaging performed in the Department of Neuroradiology in Bari showing suspicious repetitive bone lesions; therefore, the patient underwent several medical procedures and laboratory exams which ended with a surgical removal of a left L3-L4 foraminal disc herniation and a bone biopsy.

RESULTS

When it was finally possible to exclude any other diseases including thyroid neoplasms, a "reassuring" osteoporosis diagnosis has been made since the lesions were likely to be degenerative and the patient underwent menopause 7 years ago. However, the multiplicity of the lesions of the vertebrae and of the pelvic bones as well as their signal could not be ignored, so that a close magnetic resonance imaging follow-up has been recommended.

CONCLUSIONS

The present case is therefore a good example of overtreatment which may lead to delicate questions, investigating any possible mistakes in the diagnosis procedure as well as the role that defensive medicine is playing nowadays on medical procedures and the economic impact that all this can have on our healthcare system. In the end, we may ask ourselves: is "less" better or is "more" always "more?"

Differential diagnosis of benign and malignant vertebral compression fractures using conventional and advanced MRI techniques

Atraumatic vertebral compression fractures (VCFs) are commonly encountered in clinical practice and often represent a diagnostic challenge. MRI plays a major role in the differential diagnosis of benign and malignant VCFs, due to its high contrast resolution and the possibility to obtain quantitative and functional data with the employment of advanced sequences. Computer-aided diagnosis systems are also applied on MRI images for this purpose, showing promising results. In this setting, aim of this pictorial review is to elucidate the role of MRI in the differential diagnosis of VCFs with a specific focus on advanced and post-processing imaging techniques.

ACR Appropriateness Criteria® Management of Vertebral Compression Fractures

Vertebral compression fractures (VCFs) have various causes, including osteoporosis, neoplasms, and acute trauma. As painful VCFs may contribute to general physical deconditioning, management of painful VCFs has the potential for improving quality of life and preventing superimposed medical complications. Various imaging modalities can be used to evaluate a VCF to help determine the etiology and guide intervention. The first-line treatment of painful VCFs has been nonoperative or conservative management as most VCFs show gradual improvement in pain over 2 to 12 weeks, with variable return of function. There is evidence that vertebral augmentation (VA) is associated with better pain relief and improved functional outcomes compared to conservative therapy for osteoporotic VCFs. A multidisciplinary approach is necessary for the management of painful pathologic VCFs, with management strategies including medications to affect bone turnover, radiation therapy, and interventions such as VA and percutaneous thermal ablation to alleviate symptoms. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

A novel MRI- and CT-based scoring system to differentiate malignant from osteoporotic vertebral fractures in Chinese patients

Background

Various types of magnetic resonance imaging (MRI) and computed tomography (CT) findings are used to differentiate malignant vertebral fractures (MVFs) from osteoporotic vertebral fractures (OVFs). The distinguishing ability of any single finding is limited. This study developed a novel scoring system that integrates multiple MRI and CT signs for improved accuracy of differential diagnosis between MVFs and OVFs.

Methods

A total of 150 MVFs and 150 OVFs in thoracolumbar vertebrae were analyzed. MRI and CT images were obtained within 2 months of the probable time of fracture. The sensitivity and specificity of 15 MRI and CT image findings were evaluated. A stepwise discriminant analysis using these signs as variables was used to create a scoring system to differentiate MVFs from OVFs.

Results

All 15 image findings had strong specificity and moderate sensitivity. Seven MRI and three CT image findings were selected and assigned integral values in the final scoring system. A total score of 4 or greater points indicated MVF, whereas a total score of 3 or fewer points indicated OVF. The classification accuracy was 98.3% in the test set.

Conclusions

This novel scoring system using MRI and CT radiologic findings to differentiate MVFs from OVFs in Chinese patients was efficient with high accuracy and good applicability.

The Prognostic Significance of Pedicle Enhancement from Contrast-enhanced MRI for the Further Collapse in Osteoporotic Vertebral Compression Fractures

STUDY DESIGN

A retrospective observational study.

OBJECTIVE

The aim of this study was to investigate the prognostic significance of contrast-enhanced magnetic resonance imaging (MRI) for detecting pedicle enhancement and predicting future collapse in patients with acute benign osteoporotic vertebral compression fracture (OVCF).

SUMMARY OF BACKGROUND DATA

Traditional morphological classification regarding compression versus burst fractures cannot accurately anticipate the prognosis of further collapse. Identifying subgroups with a higher risk for further collapse may be beneficial in determining the treatment modality, which should be decided immediately after the injury.

METHODS

One hundred fourteen patients with benign OVCFs who, at the onset, underwent contrast-enhanced spine MRI between 2003 and 2016 were retrospectively analyzed. Patients were recruited on the basis of predefined inclusion and exclusion criteria. The primary outcome was the compression progression rate; other potential variables included demographic and clinical characteristics, initial compression rates, and kyphotic angles. In addition, other structural abnormalities on MRI were assessed. The compression progression rates were compared according to pedicle enhancement, and the prognostic significance of pedicle enhancement for further collapse were analyzed.

RESULTS

Further compression progression rates were significantly higher in the pedicle-enhanced (PE) group than in the nonenhanced (NE) group. Multivariate logistic analysis revealed that pedicle enhancement may be associated with further compression progression ≥10%. The vertebral augmentation (VAG) protective effect against collapse was only significant within the PE group, while bone densitometry and patients' mobility were significant only within the NE group. The log-rank test revealed a statistically significant difference in the rates of further collapse ≥10% during the 1 year between the groups.

CONCLUSION

Sign of pedicle enhancement is a potential risk factor for further compression progression. Contrast-enhanced MRI should be performed at the onset to better determine the future risk of collapse and to choose a better treatment modality for benign OVCF patients.

LEVEL OF EVIDENCE

3.

The META score for differentiating metastatic from osteoporotic vertebral fractures: an independent agreement assessment

BACKGROUND CONTEXT

Differentiating osteoporotic vertebral fractures (OVFs) from metastatic vertebral fractures (MVFs) is an important clinical challenge. A novel magnetic resonance imaging (MRI)-based score (the META score) was described, aiming to differentiate OVF from MVF. This score showed an almost perfect agreement by the group developing it, but an independent agreement evaluation is pending.

PURPOSE

We aimed to perform an independent inter- and intraobserver agreement evaluation of the META score and to test the score's capability of differentiating OVF from MVF.

STUDY DESIGN

This is an agreement study of the META score.

METHODS

Sixty-four patients with confirmed OVF or MVF were assessed by six independent evaluators (three spine surgeons and three fellowship-trained radiologists) using the META score. We used the intraclass correlation coefficient (ICC) to determine the overall inter-and intraobserver agreement, and the kappa statistic (κ) to express the agreement for each individual score criterion. The score accuracy was determined by calculating the area under the receiver operating characteristic curve. Finally, we used κ to evaluate the agreement among raters to determine whether the fracture was OVF or MVF.

RESULTS

The overall interobserver agreement was poor [ICC=0.10 (0.02-0.20)]; spine surgeons [ICC=0.75 (0.66-0.83)] had better agreement than radiologists did [ICC=0.05 (-0.08 to 0.21)]. The intraobserver agreement was poor [ICC=0.17 (0.01-0.32)]; both spine surgeons [ICC=0.21 (0.05-0.41)] and radiologists had a poor agreement [ICC=0.03 (-0.29 to 0.27)]. The agreement for each specific criterion varied from κ=0.24 to κ=0.60. The area under the receiver operating characteristic curve was 0.58 (0.64 for spine surgeons and 0.52 for radiologists, p<.01).

CONCLUSIONS

The interobserver agreement using the META score was adequate for spine surgeons but not for other potential users (radiologists); the intraobserver agreement was poor. Further studies are thus necessary before the use of this score is recommended.

Does the META score evaluating osteoporotic and metastatic vertebral fractures have enough agreement to be used by orthopaedic surgeons with different levels of training?

PURPOSE

Differentiating osteoporotic vertebral fractures (OVF) from metastatic vertebral fractures (MVF) is difficult. A magnetic resonance imaging (MRI)-based score (META score) aiming to differentiate OVF and MVF was recently published; however, an independent agreement assessment is required before the score is used. We performed such independent agreement evaluation, including raters with different levels of training.

METHODS

Sixty-four patients with confirmed OVF or MVF were evaluated by six raters (three spine surgeons and three orthopaedic residents) using the META score. We used the intra-class correlation coefficient (ICC) to evaluate inter- and intra-observer agreement and the kappa statistic (κ) to determine the agreement for individual score criteria. We calculated the area under the receiver-operating characteristic curve (AUC) to establish the score accuracy.

RESULTS

The inter-observer agreement was poor [ICC = 0.22 (0.12-0.33)]; spine surgeons [ICC = 0.75 (0.66-0.83)] had better agreement than that of residents [ICC = 0.06 (- 0.07 to 0.23)]. The intra-observer agreement was poor [ICC = 0.15 (- 0.04 to 0.30)]; both spine surgeons [ICC = 0.21 (0.05-0.41)] and residents exhibited poor agreement [ICC = - 0.06 (- 0.40 to 0.20)]. The agreement for each specific criterion varied from κ = 0.24 to κ = 0.38. The AUC was 0.57 (0.64 for spine surgeons and 0.51 for residents, p < 0.01).

CONCLUSION

The inter-observer agreement using the META score was adequate for spine surgeons but not for residents; the intra-observer agreement was poor. These results do not support the standard use of the META score to differentiate OVF and MVF. These slides can be retrieved under Electronic Supplementary Material.

High Prevalence of Radiological Vertebral Fractures in Women on Thyroid-Stimulating Hormone-Suppressive Therapy for Thyroid Carcinoma

CONTEXT

Bone loss and nonvertebral fractures have been reported in patients with differentiated thyroid carcinoma (DTC) undergoing thyroid-stimulating hormone (TSH) suppressive therapy. Radiological vertebral fractures (VFs) are an early and clinically crucial marker of bone fragility.

OBJECTIVE AND DESIGN

A cross-sectional study to evaluate the prevalence and determinants of radiological VFs in women receiving l-thyroxine (L-T4) therapy for DTC.

PATIENTS AND INTERVENTIONS

A total of 179 consecutive women (median age, 59 years; n = 178 postmenopausal) who had undergone thyroidectomy for DTC and were currently receiving L-T4 were evaluated for radiological VFs and bone mineral density (BMD). There were three TSH target levels [<0.5 mU/L, group 1 (n = 83); 0.5 to 1.0 mU/L, group 2 (n = 50); >1.0 mU/L, group 3 (n = 46)].

RESULTS

VFs were found in 51 patients (28.5%), with significantly (P < 0.001) higher prevalence in group 1 (44.6%) as compared with group 2 (24.0%) and group 3 (4.3%). VF prevalence was not significantly different among patients in group 1 with normal BMD, osteopenia, or osteoporosis, whereas in groups 2 and 3, VFs were more frequent in patients with osteoporosis than in those with either osteopenia or normal BMD. In the whole population, VFs were significantly and independently associated with TSH level <1.0 mU/L; densitometric diagnosis of osteoporosis at lumbar spine, femoral neck, or total hip; age of patients; and duration of L-T4 therapy.

CONCLUSION

The prevalence of VFs was high in women with DTC who were undergoing long-term, suppressive L-T4 therapy.