Malignant Vertebral Fractures Research Articles

Deep Learning to Differentiate Benign and Malignant Vertebral Fractures at Multidetector CT.

Background Differentiating between benign and malignant vertebral fractures poses diagnostic challenges. Purpose To investigate the reliability of CT-based deep learning models to differentiate between benign and malignant vertebral fractures. Materials and Methods CT scans acquired in patients with benign or malignant vertebral fractures from June 2005 to December 2022 at two university hospitals were retrospectively identified based on a composite reference standard that included histopathologic and radiologic information. An internal test set was randomly selected, and an external test set was obtained from an additional hospital. Models used a three-dimensional U-Net encoder-classifier architecture and applied data augmentation during training. Performance was evaluated using the area under the receiver operating characteristic curve (AUC) and compared with that of two residents and one fellowship-trained radiologist using the DeLong test. Results The training set included 381 patients (mean age, 69.9 years ± 11.4 [SD]; 193 male) with 1307 vertebrae (378 benign fractures, 447 malignant fractures, 482 malignant lesions). Internal and external test sets included 86 (mean age, 66.9 years ± 12; 45 male) and 65 (mean age, 68.8 years ± 12.5; 39 female) patients, respectively. The better-performing model of two training approaches achieved AUCs of 0.85 (95% CI: 0.77, 0.92) in the internal and 0.75 (95% CI: 0.64, 0.85) in the external test sets. Including an uncertainty category further improved performance to AUCs of 0.91 (95% CI: 0.83, 0.97) in the internal test set and 0.76 (95% CI: 0.64, 0.88) in the external test set. The AUC values of residents were lower than that of the best-performing model in the internal test set (AUC, 0.69 [95% CI: 0.59, 0.78] and 0.71 [95% CI: 0.61, 0.80]) and external test set (AUC, 0.70 [95% CI: 0.58, 0.80] and 0.71 [95% CI: 0.60, 0.82]), with significant differences only for the internal test set (P < .001). The AUCs of the fellowship-trained radiologist were similar to those of the best-performing model (internal test set, 0.86 [95% CI: 0.78, 0.93; P = .39]; external test set, 0.71 [95% CI: 0.60, 0.82; P = .46]). Conclusion Developed models showed a high discriminatory power to differentiate between benign and malignant vertebral fractures, surpassing or matching the performance of radiology residents and matching that of a fellowship-trained radiologist. © RSNA, 2024 See also the editorial by Booz and D'Angelo in this issue.

The role of diffusion-weighted MRI in the accurate diagnosis of vertebral compression fractures: A comparative study

IntroductionAccurately distinguishing between benign and malignant vertebral compression fractures is crucial for clinical management. This study evaluated the predictive accuracy of diffusion-weighted imaging (DWI) in differentiating the cause of vertebral fractures using MRI. MethodsA longitudinal cross-over study was conducted at Jinnah Postgraduate Medical Centre (JPMC) Karachi from July 2018 to January 2021. Patients with vertebral compression fractures underwent T1-weighted, T2-weighted, and DWI imaging with ADC mapping on a 1.5 T MRI scanner. Imaging findings were compared with histopathologic results and clinical follow-up. Sensitivity, specificity, and ROC curve analyses were performed. ResultsThe study enrolled 303 patients with a mean age of 43.6 ± 10.9 years, of whom 118 were male. DWI demonstrated high accuracy in predicting the cause of vertebral compression fractures, with a sensitivity of 96.2 %, a specificity of 76.2 %, and an area under the ROC curve of 0.857. The optimal ADC cut-off value was 0.82 × 10˄-3 mm˄2/s, which yielded a positive predictive value of 79.7 % and a negative predictive value of 95.4 %. ConclusionsDWI is a safe and non-invasive imaging modality with excellent predictive accuracy in differentiating between benign and malignant vertebral compression fractures. Iso- or hypointensity of collapsed vertebral bodies on DWI suggests a benign lesion, while T2-weighted hyperintensity is highly indicative of malignancy. Low signal on ADC is also highly indicative of malignant vertebral fractures. Incorporating DWI improves accuracy in assessing vertebral lesions, especially when standard sequences are inconclusive. Implications for practiceDWI revolutionizes vertebral compression fracture diagnosis, distinguishing between benign and malignant cases. This precision guides treatment decisions, minimizing the necessity for invasive procedures like biopsy. As a safe and reliable imaging method, DWI elevates patient care, ensuring accurate diagnostics and improved outcomes.

Differentiation of benign and malignant vertebral fractures using a convolutional neural network to extract CT-based texture features

PurposeTo assess the diagnostic performance of three-dimensional (3D) CT-based texture features (TFs) using a convolutional neural network (CNN)-based framework to differentiate benign (osteoporotic) and malignant vertebral fractures (VFs).MethodsA total of 409 patients who underwent routine thoracolumbar spine CT at two institutions were included. VFs were categorized as benign or malignant using either biopsy or imaging follow-up of at least three months as standard of reference. Automated detection, labelling, and segmentation of the vertebrae were performed using a CNN-based framework (https://anduin.bonescreen.de). Eight TFs were extracted: Varianceglobal, Skewnessglobal, energy, entropy, short-run emphasis (SRE), long-run emphasis (LRE), run-length non-uniformity (RLN), and run percentage (RP). Multivariate regression models adjusted for age and sex were used to compare TFs between benign and malignant VFs.ResultsSkewnessglobal showed a significant difference between the two groups when analyzing fractured vertebrae from T1 to L6 (benign fracture group: 0.70 [0.64–0.76]; malignant fracture group: 0.59 [0.56–0.63]; and p = 0.017), suggesting a higher skewness in benign VFs compared to malignant VFs.ConclusionThree-dimensional CT-based global TF skewness assessed using a CNN-based framework showed significant difference between benign and malignant thoracolumbar VFs and may therefore contribute to the clinical diagnostic work-up of patients with VFs.

Evaluation and outcome of percutaneous vertebroplasty for multilevel osteoporotic and malignant vertebral fractures (more than two)

BackgroundPercutaneous vertebroplasty (PV) is now a popular technique used to augment and stabilize the vertebral body fracture and to reduce pain as well. AimThe aim of the study is to evaluate the outcome of percutaneous vertebroplasty of multilevel osteoporotic and malignant fractures (more than two). Study designThis is a retrospective clinical case series study. Patients and methodsThis study was conducted on 30 patients with multilevel osteoporotic and malignant compression fractures (more than two). Visual analogue scale (VAS) was used to evaluate the functional outcome. All patients were treated using percutaneous vertebroplasty. They were followed for 6 months postoperatively. ResultsThe functional state of all patients improved after percutaneous vertebroplasty. According to the visual analogue scale (VAS), the preoperative VAS score was (8.43 ± 1.19). Immediate postoperative VAS was (3.07 ± 1.20) and after six months it dropped to (1.13 ± 0.67). There was a significant improvement of pain (p < 0.001). Asymptomatic leakage in the disc space was reported in two patients. A single case of pulmonary embolism was reported who complained of dyspnea. This patient was admitted to ICU and managed with proper medications with satisfactory results. ConclusionsMultilevel PV is proved to be a safe, cost effective and successful procedure that could reduce pain significantly and improve patient’s mobility.

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

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

Single shot zonal oblique multislice SE-EPI diffusion-weighted imaging with low to ultra-high b-values for the differentiation of benign and malignant vertebral spinal fractures

PurposeTo investigate the diagnostic yield of low to ultra-high b-values for the differentiation of benign from malignant vertebral fractures using a state-of-the-art single-shot zonal-oblique-multislice spin-echo echo-planar diffusion-weighted imaging sequence (SShot ZOOM SE-EPI DWI). Materials and Methods66 patients (34 malignant, 32 benign) were examined on 1.5 T MR scanners. ADC maps were generated from b-values of 0,400; 0,1000 and 0,2000s/mm2. ROIs were placed into the fracture of interest on ADC maps and trace images and into adjacent normal vertebral bodies on trace images. The ADC of fractures and the Signal-Intensity-Ratio (SIR) of fractures relative to normal vertebral bodies on trace images were considered quantitative metrics. The appearance of the fracture of interest was graded qualitatively as iso-, hypo-, or hyperintense relative to normal vertebrae. ResultsADC achieved an area under the curve (AUC) of 0.785/0.698/0.592 for b = 0,400/0,1000/0,2000s/mm2 ADC maps respectively. SIR achieved an AUC of 0.841/0.919/0.917 for b = 400/1000/2000s/mm2 trace images respectively. In qualitative analyses, only b = 2000s/mm2 trace images were diagnostically valuable (sensitivity:1, specificity:0.794). Machine learning models incorporating all qualitative and quantitative metrics achieved an AUC of 0.95/0.98/0.98 for b-values of 400/1000/2000s/mm2 respectively. The model incorporating only qualitative metrics from b = 2000s/mm2 achieved an AUC of 0.97. ConclusionBy using quantitative and qualitative metrics from SShot ZOOM SE-EPI DWI, benign and malignant vertebral fractures can be differentiated with high diagnostic accuracy. Importantly qualitative analysis of ultra-high b-value images may suffice for differentiation as well.

[Diffusion-Weighted Magnetic Resonance Imaging of Spine].

척추영상에 사용되는 확산강조영상의 기술적 측면, 양성과 악성 척추체 압박골절의 구분, 다발성골수종이나 전이암의 발견과 감별진단, 그리고 항암화학요법이나 방사선치료 후 반응 평가에 대해 기술하고자 한다.

Reliability and Validity of Different MRI Sequences in Improving the Accuracy of Differential Diagnosis of Benign and Malignant Vertebral Fractures: A Meta-Analysis.

OBJECTIVE. We aimed to systematically examine the reliability and validity of different MRI sequences in differentiating benign and malignant vertebral fractures, appropriately select the best MRI sequence to improve the diagnostic accuracy, and compare the diagnostic accuracy of MRI sequences in the context of different study designs or publication date. MATERIALS AND METHODS. Computer and manual retrieval were conducted on studies published between January 1, 2000, and September 31, 2016. Studies relevant to the differential diagnosis of benign and malignant vertebral fractures by MRI and reference standard (histopathologic diagnosis or clinical follow-up examination) were analyzed. RESULTS. Eighteen articles were included. Neither threshold (p = 0.86) nor nonthreshold (p = 0.06) effects were present. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 89% (95% CI, 86-92%), 88% (95% CI, 85-91%), 6.54 (95% CI, 4.44-9.65), 0.14 (95% CI, 0.09-0.21), and 55.76 (95% CI, 37.06-83.89), respectively. The AUC was 0.95. The risk of publication bias was negligible (p = 0.33). CONCLUSION. MRI sequences could provide appreciable diagnostic performance in differentiating benign and malignant vertebral fractures. However, our pooled estimates do not support the superiority of one set of sequences over another, and there is not sufficient evidence to show that prospective or recent studies are obviously better than retrospective or older studies.

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

BackgroundVarious 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.MethodsA 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.ResultsAll 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.ConclusionsThis 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.

Quantitative evaluation of diffusion-weighted imaging with multiple b-values in vertebral fractures

Aim: Differentiating benign from malignant vertebral fracture is sometimes difficult in geriatric oncology patients. Accurate diagnosis is necessary for treatment planning. Therefore, we aimed to investigate the role of quantitative evaluation of diffusion-weighted imaging (DWI) at multiple b-values of 200, 400 and 600 s/mm2 in differentiating benign from malignant thoracolumbar vertebral fractures and to determine an optimal b-value. Methods: Forty-four patients with 72 vertebral fractures were enrolled. Magnetic resonance imaging (MRI) findings combined with DWI at b-values of 200, 400 and 600 s/mm2 were evaluated. Apparent diffusion coefficient (ADC) and normalized ADC values were obtained. Radiological and histopathological/follow-up results were compared. Results: Of 72 vertebral fractures, 22 were benign and 50 were malignant. Mean ADC and normalized ADC values of malignant group were lower than benign group’s in all b-values (p<0.05). Despite of no significant difference between ADC values at b-values of 200, 400 and 600 s/mm2 within each group, normalized ADC values were lower at b-value of 200 s/mm2 than those of at 600 s/mm2 in malignant group (p<0.05). Conclusion: MRI combined with DWI is a problem solving modality especially in geriatric oncology patients. Performing DWI at b-value of 200 s/mm2 and estimation of normalized ADC value for optimization of data are recommended.

Quantitative evaluation of T2* relaxation times for the differentiation of acute benign and malignant vertebral body fractures

ObjectivesThe aim of this prospective study was to evaluate the diagnostic performance of T2*-weighted magnetic resonance imaging (MRI) to differentiate between acute benign and neoplastic vertebral compression fractures (VCFs). Materials and methodsThirty-seven consecutive patients with a total of 52 VCFs were prospectively enrolled in this IRB approved study. All VCFs were categorized as either benign or malignant according to direct bone biopsy and histopathologic confirmation. In addition to routine clinical spine MRI including at least sagittal T1-weighted, T2-weighted and T2 spectral attenuated inversion recovery (SPAIR)-weighted sequences, all patients underwent an additional sagittal six-echo modified Dixon gradient-echo sequence of the spine at 3.0-T. Intravertebral T2* and T2*ratio (fracture T2*/normal vertebrae T2*) for acute benign and malignant VCFs were calculated using region-of-interest analysis and compared between both groups. Additional receiver operating characteristic analyses were performed. Five healthy subjects were scanned three times to determine the short-term reproducibility of vertebral T2* measurements. ResultsThere were 27 acute benign and 25 malignant VCFs. Both T2* and T2*ratio of malignant VCFs were significantly higher compared to acute benign VCFs (T2*, 30 ± 11 vs. 19 ± 11 ms [p = 0.001]; T2*ratio, 2.9 ± 1.6 vs. 1.2 ± 0.7 [p < 0.001]). The areas under the curve were 0.77 for T2* and 0.88 for T2*ratio, yielding an accuracy of 73% and 89% for distinguishing acute benign from malignant VCFs. The root mean square absolute precision error was 0.44 ms as a measure for the T2* short-term reproducibility. ConclusionQuantitative assessment of vertebral bone marrow T2* relaxation times provides good diagnostic accuracy for the differentiation of acute benign and malignant VCFs.

Vertebral Compression Fractures in Elderly: How to Recognize and Report

In elderly patients, when there is no obvious evidence of malignancy on plain radiography, it can be difficult to evaluate benign and malignant vertebral fractures, because these patients are predisposed to senile osteoporosis and malignant disease. The only complaint could be back pain, as both types of fractures have the same symptoms and signs. A reliable imaging modality is always required, as appropriate management and early diagnosis of malignant vertebral fractures are important. The aim of this study was to highlight the importance of recognizing, through diagnostic techniques, the presence of vertebral fractures, since the majority of vertebral fractures do not come to clinical attention and to determine the parameters that are useful for the early differentiation between benign versus malignant vertebral fractures.

Cement pulmonary embolism as a complication of percutaneous vertebroplasty in cancer patients

BackgroundVertebroplasty is a minimally invasive procedure commonly performed for vertebral compression fractures secondary to osteoporosis or malignancy. Leakage of bone cement into the paravertebral venous system and cement pulmonary embolism (cPE) are well described, mostly in patients with osteoporosis. Little is known about the clinical sequelae and outcomes in cancer patients. In this study, we report our experience with cPE following vertebroplasty performed in cancer patients.MethodsRecords of all consecutive cancer patients who underwent vertebroplasty at our institution were retrospectively reviewed. The procedure was performed via percutaneous injection of barium-opacified polymethyl-methacrylate cement.ResultsA total of 102 cancer patients with a median age of 53 (19–83) years were included. Seventy-eight (76.5%) patients had malignant vertebral fractures, and 24 (23.5%) patients had osteoporotic fractures. Cement PE was detected in 13 (12.7%) patients; 10 (76.9%) patients had malignant fractures, and the remaining three had osteoporotic fractures. Cement PE was mostly asymptomatic; however, 5 (38.5%) patients had respiratory symptoms that led to the diagnosis. Only the five symptomatic patients were anticoagulated.Cement PE was more common with multiple myeloma (MM); it occurred in 7 (18.9%) of the 37 patients with MM compared with only three (7.3%) of the 41 patients with other malignancies. No difference in incidence was observed between patients with osteoporotic or malignant vertebral fractures.ConclusionsCement PE is a relatively common complication following vertebroplasty and is mostly asymptomatic. Multiple myeloma is associated with the highest risk. Large-scale prospective studies can help identify risk factors and clinical outcomes and could lead to better prevention and therapeutic strategies.

Differentiation of Acute Osteoporotic and Malignant Vertebral Fractures by Quantification of Fat Fraction With a Dixon MRI Sequence.

The purpose of this study was to differentiate malignant compression fractures from acute osteoporotic compression fractures of the spine by use of a Dixon MRI sequence to quantify fat fraction (FF). Forty-four vertebral compression fractures were assessed with turbo spin-echo T1-weighted and six-echo Dixon sequences for FF quantification at 3-T MRI. The fractures were divided into malignant compression fractures (n = 24) and acute osteoporotic compression fractures (n = 20). Two radiologists independently measured quantitative parameters from ROIs in the fractures, including the T1 signal intensity of the fracture, the FF of the fracture, and the FF ratio (fracture FF divided by normal marrow FF). The mean values of the parameters were compared between the two groups, interobserver reliability between two radiologists was assessed, ROC curves were analyzed, and logistic regression analysis was performed. The fracture FF and FF ratio of malignant compression fractures were significantly lower than those of acute osteoporotic compression fractures (fracture FF, 2.73% vs 14.36% [p < 0.001]; FF ratio, 0.05 vs 0.22 [p < 0.001]). There was no difference in T1 signal intensity of the fracture. The ROC AUC of fracture FF was 0.98 and of FF ratio was 0.95. In logistic regression analysis, fracture FF remained a significant variable that could be used to independently differentiate malignant from acute osteoporotic compression fractures (odds ratio, 0.33; p < 0.005). FF and FF ratio obtained from FF maps obtained with a six-echo Dixon MRI sequence may be useful for differentiating acute osteoporotic compression fractures from malignant compression fractures.

Discrimination between Malignant and Benign Vertebral Fractures Using Magnetic Resonance Imaging.

Study DesignRetrospective analysis using magnetic resonance imaging (MRI).PurposeTo identify MRI features that could discriminate benign from malignant vertebral fractures.Overview of LiteratureDiscrimination between benign and malignant vertebral fractures remains challenging, particularly in patients with osteoporosis and cancer. Presently, the most sensitive means of detecting and assessing fracture etiology is MRI. However, published reports have focused on only one or a few discriminators.MethodsTotally, 106 patients were assessed by MRI within six weeks of sustaining 114 thoracic and/or lumbar vertebral fractures (benign, n=65; malignant, n=49). The fractures were pathologically confirmed if malignant or clinically diagnosed if benign and were followed up for a minimum of six months. Seventeen features were analyzed in all fractures' magnetic resonance images. Single parameters were analyzed using the chi-square test; a logit model was established using multivariate logistic regression analysis.ResultsThe chi-square test revealed 11 malignant and 4 benign parameters. Multivariate logistic regression analysis selected (i) posterior wall diffuse protrusion (odds ratio [OR], 48; 95% confidence interval [CI], 4.2–548; p=0.002), (ii) pedicle involvement (OR, 21; 95% CI, 2.0–229; p=0.01), (iii) posterior involvement (OR, 21; 95% CI, 1.5–21; p=0.02), and (iv) band pattern (OR, 0.047; 95% CI, 0.0005–4.7; p=0.19). The logit model was expressed as P=1/[1+exp (x)], x=−3.88×(i)−3.05×(ii)−3.02×(iii)+3.05×(iv)+5.00, where P is the probability of malignancy. The total predictive value was 97.3%. The only exception was multiple myeloma with features of a benign fracture.ConclusionsAlthough each MRI feature had a different meaning with a variable differentiation power, combining them led to an accurate diagnosis. This study identified the most relevant MRI features that would be helpful in discriminating benign from malignant vertebral fractures.

Thick cement usage in percutaneous vertebroplasty for malignant vertebral fractures at high risk for cement leakage.

To assess the feasibility and safety of transpedicular percutaneous vertebroplasty (PVP) using thick bone cement in patients with intractable metastatic vertebral pain and at high risk for cement leakage. Unilateral transpedicular PVP using firm bone cement was performed in 77 patients with intractable pain due to vertebral metastases in the thoracolumbar spine, who had one or more relative contraindication to PVP. Primary outcome measures were the severity of pain as assessed on a 100-mm visual analogue scale and daily morphine consumption. Secondary outcome measures were the degree of disability and the incidence of procedure-related adverse outcomes. The outcome measures were assessed at the preoperative visit and at 1 day, 1 week, 4 weeks and 12 weeks after the procedure. Sixty-three (81.8%) patients completed the 12-week follow-up period. There were 30 men and 33 women, with a mean age of 58±11 (SD) [range: 34-81 years]. Compared with pre-procedure value, all post-procedure pain scores were significantly lower (P<0.0001). Likewise, there was a statistically significant reduction in daily morphine consumption at all follow-up times (P<0.0001). The ambulation score, ADL, and ODI were all significantly lower at all assessment times compared with pre-procedure values (P<0.0001). No serious adverse effects were observed. PVP using thick bone cement could be administered with reasonable safety to patients suffering from intractable pain caused by vertebral metastases who were at high risk for cement leakage. The procedure was associated with significant improvement of pain and disability.

Differentiation of acute osteoporotic from malignant vertebral compression fractures with conventional MRI and diffusion MR imaging

AimTo evaluate the role of using a single shot spin echoplanar DW sequence (SSSEP-DWI) compared to conventional MRI and contrast enhanced T1WI in differentiation between vertebral osteoporotic fractures and malignant compression fractures. The sensitivity and specificity of (SSSEP-DWI) will also be calculated. Patients and methodsSixty-eight acute vertebral compression fractures in 41 patients were imaged using conventional MRI, fat suppressed contrast enhanced T1WI and DW sequence on a 1.5T MR machine. Quantitative assessment of the abnormal signal intensity was done by measuring apparent diffusion coefficients (ADCs). Also, the areas of abnormal signal intensity were compared to adjacent normal marrow. ResultsWe had 38 benign fractures, and 30 malignant fractures. Post contrast enhancement showed sensitivity of 92% and specificity of 70% for malignant compression fractures. The hyperintense signal on DWI has 89% PPV for malignancy, while the sensitivity and specificity were 86% and 91% respectively. The mean ADC for malignant fractures was significantly lower than those of osteoporotic fractures (p=0.0002). ConclusionsSSSEP-DWI is a reliable adjunct parameter that supports conventional MRI in differentiating benign and malignant vertebral fractures.

Distinguishing Benign and Malignant Vertebral Fractures Using CT and MRI.

The differential diagnosis between benign and malignant vertebral fractures is a common challenge in clinical practice, especially because osteoporotic fractures become more frequent within the aging population and many malignant diseases spread to the bone first, impacting bone integrity. This article reviews the morphological features and computed tomography (CT) and magnetic resonance imaging (MRI) imaging findings that help differentiate between benign and malignant fractures. Newer techniques such as MR-based diffusion-weighted imaging, dynamic contrast-enhanced MR, and chemical-shift imaging as well as hybrid techniques such as positron emission tomography-CT are also discussed briefly.

Comments on "Standard-b-value vs low-b-value DWI for differentiation of benign and malignant vertebral fractures: a meta-analysis".

Comments on "Standard-b-value vs low-b-value DWI for differentiation of benign and malignant vertebral fractures: a meta-analysis".

Standard-b-value vs low-b-value DWI for differentiation of benign and malignant vertebral fractures: a meta-analysis.

To determine the comparative diagnostic performance of standard-b-value (≥500 mm(2)) vs low-b-value (<500s mm(-2)) diffusion-weighted imaging (DWI) for discriminating malignant from benign vertebral compression fractures. 12 studies with a total of 350 malignant and 312 benign vertebral fractures were included. The apparent diffusion coefficient (ADC) value of benign vertebral compression fractures was lower than that of malignant vertebral compression fractures (SMD = 1.81, 95% CI 0.98 to 2.64 Z = 4.27, p < 0.05). ADC value difference was more pronounced in the group of low-b-value DWI (SMD = 2.31, 95% CI 1.02 to 3.60 Z = 3.51, p < 0.05) than in the group of standard-b-value DWI (SMD = 1.38, 95% CI 0.18 to 2.59 Z = 2.25, p < 0.05). Ethnicity stratified analysis demonstrated higher ADC values in benign vertebral compression fractures in comparison to malignant tissues in both the Asian and Caucasian subgroups (Asians: SMD = 2.400, 95%CI 1.45 to approximately 3.35, p<0.05; Caucasians: SMD = 0.592, 95 % CI -0.848 to approximately 2.032, p < 0.05). And the ADC value difference was more pronounced in the Asian subgroup. ADC value appears to be a reliable method to differentiate benign from malignant fractures. Low-b-value DWI was more a valuable parameter than standard-b-value DWI for discriminating malignant from benign vertebral compression fractures. And the diffusion characteristics of the benign vertebral fractures such as osteoporosis, trauma and infection have rarely been investigated separately. The use of low-b-value DWI for differentiation of benign and malignant vertebral fractures is recommended.