CT detects more osteoporotic endplate depressions than radiograph: a descriptive comparison of 76 vertebrae

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.

Radiographic Diagnosis of Osteoporotic Vertebral Fracture in Older Women and Men Based on Statistical Probability

A radiographic gold standard to distinguish osteoporotic vertebral fractures (VFs) from nonosteoporotic VFs does not exist. Radiographic fracture-shaped vertebral deformity (FSVD) is common among young populations with normal bone strength. FSVD in an older population is called osteoporotic-like vertebral fracture (OLVF) when the FSVD is likely associated with compromised bone strength. For more severe grade deformities or when a vertebra is collapsed, experienced readers can make an osteoporotic VF diagnosis with a high degree of certainty. In milder cases, radiographic osteoporotic VF is often diagnosed based on a high probability rather than an absolute diagnosis. For older women, three nonadjacent minimal grade OLVFs (< 20% height loss), one minimal grade OLVF and one mild OLVF (≥ 20∼25% height loss), or one OLVF with ≥ 25% height loss meets the diagnosis of osteoporosis. For older men, a single OLVF with ≥ 33 to 40% height loss is insufficient to suggest the patient has osteoporosis.

The Small Pixel Effect in Ultra-High-Resolution Photon-Counting CT of the Lumbar Spine

OBJECTIVES

Image acquisition in ultra-high-resolution (UHR) scan mode does not impose a dose penalty in photon-counting CT (PCCT). This study aims to investigate the dose saving potential of using UHR instead of standard-resolution PCCT for lumbar spine imaging.

MATERIALS AND METHODS

Eight cadaveric specimens were examined with 7 dose levels (5-35 mGy) each in UHR (120 × 0.2 mm) and standard-resolution acquisition mode (144 × 0.4 mm) on a first-generation PCCT scanner. The UHR images were reconstructed with 3 dedicated bone kernels (Br68 [spatial frequency at 10% of the modulation transfer function 14.5 line pairs/cm], Br76 [21.0], and Br84 [27.9]), standard-resolution images with Br68 and Br76. Using automatic segmentation, contrast-to-noise ratios (CNRs) were established for lumbar vertebrae and psoas muscle tissue. In addition, image quality was assessed subjectively by 19 independent readers (15 radiologists, 4 surgeons) using a browser-based forced choice comparison tool totaling 16,974 performed pairwise tests. Pearson's correlation coefficient ( r ) was used to analyze the relationship between CNR and subjective image quality rankings, and Kendall W was calculated to assess interrater agreement.

RESULTS

Irrespective of radiation exposure level, CNR was higher in UHR datasets than in standard-resolution images postprocessed with the same reconstruction parameters. The use of sharper convolution kernels entailed lower CNR but higher subjective image quality depending on radiation dose. Subjective assessment revealed high interrater agreement ( W = 0.86; P < 0.001) with UHR images being preferred by readers in the majority of comparisons on each dose level. Substantial correlation was ascertained between CNR and the subjective image quality ranking (all r 's ≥ 0.95; P < 0.001).

CONCLUSIONS

In PCCT of the lumbar spine, UHR mode's smaller pixel size facilitates a considerable CNR increase over standard-resolution imaging, which can either be used for dose reduction or higher spatial resolution depending on the selected convolution kernel.

Artificial Intelligence-Assisted Detection of Osteoporotic Vertebral Fractures on Lateral Chest Radiographs in Post-Menopausal Women

Osteoporotic vertebral fractures (OVFs) are often not reported by radiologists on routine chest radiographs. This study aims to investigate the clinical value of a newly developed artificial intelligence (AI) tool, Ofeye 1.0, for automated detection of OVFs on lateral chest radiographs in post-menopausal women (>60 years) who were referred to undergo chest x-rays for other reasons. A total of 510 de-identified lateral chest radiographs from three clinical sites were retrieved and analysed using the Ofeye 1.0 tool. These images were then reviewed by a consultant radiologist with findings serving as the reference standard for determining the diagnostic performance of the AI tool for the detection of OVFs. Of all the original radiologist reports, missed OVFs were found in 28.8% of images but were detected using the AI tool. The AI tool demonstrated high specificity of 92.8% (95% CI: 89.6, 95.2%), moderate accuracy of 80.3% (95% CI: 76.3, 80.4%), positive predictive value (PPV) of 73.7% (95% CI: 65.2, 80.8%), and negative predictive value (NPV) of 81.5% (95% CI: 79, 83.8%), but low sensitivity of 49% (95% CI: 40.7, 57.3%). The AI tool showed improved sensitivity compared with the original radiologist reports, which was 20.8% (95% CI: 14.5, 28.4). The new AI tool can be used as a complementary tool in routine diagnostic reports for the reduction in missed OVFs in elderly women.

A comparison of radiographic degeneration features of older Chinese women and older Italian Caucasian women with a focus on thoracic spine

BACKGROUND

Compared with Caucasians, East Asians have a lower incident of back pain, lower prevalence and severity of osteoporotic vertebral fracture and lumbar spine degeneration.

AIM

This study compares radiographic spine degeneration features of older Chinese women (as an example of East Asians) and older Italian women (as an example of Caucasians) with a focus on the thoracic spine.

METHODS

From two population-based epidemiological studies conducted in Hong Kong, China and Rome, Italy, 297 pairs (mean age: 73.6 years) age-matched older community women's lateral spine radiographs were sampled. Existence (or absence) of seven degeneration features were assessed including: (1) hyper-kyphosis, (2) disc space narrowing (T3/T4 ~ T11/T12), (3) osteoarthritic (OA) wedging (T4 ~ T12), (4) generalised osteophyte formation (T4 ~ T12); (5) acquired short vertebrae (T4 ~ T12), (6) Schmorl node (T4 - L5), (7) disc calcification (T4-L5).

RESULTS

Italian women were more likely to have hyper-kyphosis (53.4% vs 25.6%), disc space narrowing (34.4% vs. 17.2%), OA wedging (6.4% vs. 0.67%), Schmorl node (19.5% vs. 4.4%, all P < 0.001). However, there was no statistically significant difference in osteophyte formation (7.7% vs. 9.4%, P > 0.1) and acquired short vertebrae (8.0% vs. 10.4%, P > 0.1). Disc calcification was uncommon among both Chinese and Italians.

DISCUSSION AND CONCLUSION

For the first time, this study documented a lower prevalence of a number of thoracic spine degeneration features among Chinese. This study further affirms the concept of a generally healthier spine in older Chinese relative to older Caucasians. The observed differences may reflect a foundational background influence of genetic predisposition that represents an important line of future research.

Conversion of osteoporotic vertebral fracture severity score to osteoporosis T-score equivalent status: a framework and a comparative study of Hong Kong Chinese and Rome Caucasian older women

We explored how the severity of radiological osteoporotic vertebral fracture (OVF) can be converted to the equivalent T-score values.

INTRODUCTION

To perform a study to define what portion of older community women with what severity of radiographic OVF correspond to what low T-score status.

METHODS

There were age-matched 301 Italian community women and 301 Chinese community women (sub-group A, age, 73.6 ± 6.1 years). In addition, Chinese sub-groups B and C included 110 community women (age, 68.9 ± 5.5 years) and 101 community women (age: 82.2 ± 4.3 years), respectively. For each vertebra in women, a score of 0, - 0.5, - 1, - 1.5, - 2, - 2.5, and - 3 was assigned for no OVF or OVF of < 20%, ≥ 20 ~ 25%, ≥ 25% ~ 1/3, ≥ 1/3 ~ 40%, ≥ 40%-2/3, and ≥ 2/3 vertebral height loss, respectively, OVFss was defined as the summed score of vertebrae T4 to L5. OVFss and T-scores were ranked from the smallest to the largest values.

RESULTS

For the Chinese total group (sub-groups A, B, and C together), OVFss = - 1 corresponded to lowest T-score (lowest T-score of lumbar spine, femoral neck, and total hip) of - 3.4 ~ - 3.2. OVFss ≤ - 1.5 corresponded to femoral neck T-score ≤ - 2.5. OVFss = -1.5 corresponded to a mean femoral neck T-score of - 3.0, - 2.6, and - 2.4, among Chinese sub-groups B, A, and C subjects, respectively. For Italians, all cases with OVFss ≤ - 1 had lowest T-score ≤ - 2.5. For cases with femoral neck T-score = - 2.5, 41.7% had OVFss = - 1.5, and 58.3% had OVFss = - 1.

CONCLUSION

For older women, statistically OVFss ≤ - 1 suggests this subject is osteoporotic according to lowest T-score. If using femoral neck T-score, OVFss ≤ - 1.5 qualifies osteoporosis diagnosis.

A software program for automated compressive vertebral fracture detection on elderly women's lateral chest radiograph: Ofeye 1.0

Background

Because osteoporotic vertebral fracture (OVF) on chest radiographs is commonly missed in radiological reports, we aimed to develop a software program which offers automated detection of compressive vertebral fracture (CVF) on lateral chest radiographs, and which emphasizes CVF detection specificity with a low false positivity rate.

Methods

For model training, we retrieved 3,991 spine radiograph cases and 1,979 chest radiograph cases from 16 sources, with among them in total 1,404 cases had OVF. For model testing, we retrieved 542 chest radiograph cases and 162 spine radiograph cases from four independent clinics, with among them 215 cases had OVF. All cases were female subjects, and except for 31 training data cases which were spine trauma cases, all the remaining cases were post-menopausal women. Image data included DICOM (Digital Imaging and Communications in Medicine) format, hard film scanned PNG (Portable Network Graphics) format, DICOM exported PNG format, and PACS (Picture Archiving and Communication System) downloaded resolution reduced DICOM format. OVF classification included: minimal and mild grades with <20% or ≥20-25% vertebral height loss respectively, moderate grade with ≥25-40% vertebral height loss, severe grade with ≥40%-2/3 vertebral height loss, and collapsed grade with ≥2/3 vertebral height loss. The CVF detection base model was mainly composed of convolution layers that include convolution kernels of different sizes, pooling layers, up-sampling layers, feature merging layers, and residual modules. When the model loss function could not be further decreased with additional training, the model was considered to be optimal and termed 'base-model 1.0'. A user-friendly interface was also developed, with the synthesized software termed 'Ofeye 1.0'.

Results

Counting cases and with minimal and mild OVFs included, base-model 1.0 demonstrated a specificity of 97.1%, a sensitivity of 86%, and an accuracy of 93.9% for the 704 testing cases. In total, 33 OVFs in 30 cases had a false negative reading, which constituted a false negative rate of 14.0% (30/215) by counting all OVF cases. Eighteen OVFs in 15 cases had OVFs of ≥ moderate grades missed, which constituted a false negative rate of 7.0% (15/215, i.e., sensitivity 93%) if only counting cases with ≥ moderate grade OVFs missed. False positive reading was recorded in 13 vertebrae in 13 cases (one vertebra in each case), which constituted a false positivity rate of 2.7% (13/489). These vertebrae with false positivity labeling could be readily differentiated from a true OVF by a human reader. The software Ofeye 1.0 allows 'batch processing', for example, 100 radiographs can be processed in a single operation. This software can be integrated into hospital PACS, or installed in a standalone personal computer.

Conclusions

A user-friendly software program was developed for CVF detection on elderly women's lateral chest radiographs. It has an overall low false positivity rate, and for moderate and severe CVFs an acceptably low false negativity rate. The integration of this software into radiological practice is expected to improve osteoporosis management for elderly women.