Directional fractal signature methods for trabecular bone texture in hand radiographs: data from the Osteoarthritis Initiative

Bone Data Lake: A storage platform for bone texture analysis

Trabecular bone (TB) texture regions selected on hand and knee X-ray images can be used to detect and predict osteoarthritis (OA). However, the analysis has been impeded by increasing data volume and diversification of data formats. To address this problem, a novel storage platform, called Bone Data Lake (BDL) is proposed for the collection and retention of large numbers of images, TB texture regions and parameters, regardless of their structure, size and source. BDL consists of three components, i.e.: a raw data storage, a processed data storage, and a data reference system. The performance of the BDL was evaluated using 20,000 knee and hand X-ray images of various formats (DICOM, PNG, JPEG, BMP, and compressed TIFF) and sizes (from 0.3 to 66.7 MB). The images were uploaded into BDL and automatically converted into a standardized 8-bit grayscale uncompressed TIFF format. TB regions of interest were then selected on the standardized images, and a data catalog containing metadata information about the regions was constructed. Next, TB texture parameters were calculated for the regions using Variance Orientation Transform (VOT) and Augmented VOT (AVOT) methods and stored in XLSX files. The files were uploaded into BDL, and then transformed into CSV files and cataloged. Results showed that the BDL efficiently transforms images and catalogs bone regions and texture parameters. BDL can serve as the foundation of a reliable, secure and collaborative system for OA detection and prediction based on radiographs and TB texture.

Assessment of correlation between hand-wrist maturation and cervical vertebral maturation: a fractal analysis study

BACKGROUND

To investigate whether fractal dimension (FD) measurements from hand-wrist radiographs and lateral cephalometric radiographs are correlated with each other and with skeletal maturation stages.

METHODS

In this retrospective study conducted on hand-wrist and lateral cephalometric radiographs obtained from patients between 2017 and 2023, hand-wrist maturation stages (HWMS) and cervical vertebral maturation stages (CVMS) of 144 subjects (6 to 17 years of age) were assessed radiographically. The participants were divided into nine groups (n = 16 each) based on HWMS. Fractal analysis was performed on the radiographs of the radius, the middle finger phalanges (proximal, medial and distal), and the cervical vertebral bodies (C2, C3, C4). Mean and standard deviation values, Spearman's and Pearson correlation analyses, one-way ANOVA, Kruskal-Wallis H tests and Mann-Whitney-U test were used to evaluate the data.

RESULTS

Positive correlations were found between the FD values of the radius and HWMS or CVMS (r = .559, P = .001, r = .528 P = .001 respectively). The FD values of the radius were positively correlated with those of all cervical vertebrae (C2, C3, C4), proximal and medial phalanges as well as age. FD values measured from the proximal phalanx, medial phalanx and radius showed significant differences among both HWMS and CVMS (P < .05). HWMS was strongly correlated with CVMS (r = .929, P = .001). Age was strongly correlated with HWMS (r = .795, P = .001) and CVMS (r = .756, P = .001). There was a significant difference in terms of age distribution among HWMS and CVMS (P < .05).

CONCLUSIONS

FD measurements on hand-wrist radiographs can provide useful information for the assessment of skeletal maturation stage. Especially, FD measurements from the radius are important and more reliable to predict skeletal maturation stage.

Prediction of rapid palatal expansion success via fractal analysis in hand-wrist radiographs

INTRODUCTION

This study aimed to evaluate the efficacy of fractal analysis of hand-wrist radiography in the decision of conventional or surgery-assisted rapid palatal expansion (RPE).

METHODS

The study included 48 patients who underwent the RPE procedure. Study groups were as follows: group 1 (successful conventional RPE [n = 24, 5 male and 19 female patients; mean age ± standard deviation, 15.85 ± 0.97 years]) and group 2 (failed conventional RPE [n = 24, 5 male and 19 female patients; mean age ± standard deviation, 15.96 ± 1.08 years]). Fractal dimension (FD) analysis was conducted on hand-wrist radiographs of the patients for 4 different regions: the epiphysis-diaphysis line of the radius bone and the proximal, medial (MP3), and distal (DP3) phalanxes of the middle finger. A Student t test was performed to compare fractal values between the groups. A receiver operating characteristic analysis was applied to determine the optimal cutoff value of FDs. In addition, a Pearson correlation coefficient was calculated to evaluate the relationship between the fractal values and either age or hand-wrist stage in a second sample group (n = 90; age range, 8.7-18.7 years).

RESULTS

Fractal values of the radius, MP3, and DP3 were significantly increased in the failed conventional RPE group (P <0.05). The optimal cutoff value of the FD for predicting the success of conventional RPE was 1.16 in the radius, 1.18 in proximal phalanxes, 1.29 in MP3, and 1.08 in DP3. There was a positive correlation between fractal values of the radius and age or hand-wrist stages (P <0.05).

CONCLUSIONS

Within the limits of this study, results revealed that fractal analysis of hand-wrist radiographs might be considered a significant tool in the prediction of RPE success.

Hand osteoarthritis: clinical phenotypes, molecular mechanisms and disease management

Osteoarthritis (OA) is a highly prevalent condition, and the hand is the most commonly affected site. Patients with hand OA frequently report symptoms of pain, functional limitations and frustration in undertaking everyday activities. The condition presents clinically with changes to the bone, ligaments, cartilage and synovial tissue, which can be observed using radiography, ultrasonography or MRI. Hand OA is a heterogeneous disorder and is considered to be multifactorial in aetiology. This Review provides an overview of the epidemiology, presentation and burden of hand OA, including an update on hand OA imaging (including the development of novel techniques), disease mechanisms and management. In particular, areas for which new evidence has substantially changed the way we understand, consider and treat hand OA are highlighted. For example, genetic studies, clinical trials and careful prospective imaging studies from the past 5 years are beginning to provide insights into the pathogenesis of hand OA that might uncover new therapeutic targets in the disease.

Comparison of bone texture between normal individuals and patients with Kashin-Beck disease from plain radiographs in knee

To compare tibial bone texture between Kashin-Beck disease (KBD) patients and normal individuals from plain radiographs using an advanced image analysis. Plain knee radiographs were obtained from KBD patients (n = 49) and age-matched healthy controls (n = 98). KBD were graded with diagnostic criteria WS/T 207-2010. The textural values related to bone structure from medial and lateral tibial subchondral and trabecular bones were evaluated using entropy of Laplacian-based image (E_Lap), entropy of local binary patterns (E_LBP), homogeneity indices (HI) of local angles (HI_Mean, HI_Perp and HI_Paral), and fractal dimensions from horizontal (FD_Hor) and vertical (FD_Ver) structures. KBD patients were shorter in height and lighter in weight, and their tibial width was wider than controls. Anatomical angle of KBD patients showed more genu valgus. Total KBD patients and subgroups had higher E_Lap, HI_Mean, HI_Perp and HI_Paral in detected tibial subchondral and trabecular bones than controls, except E_Lap in lateral subchondral bone. E_LBP, FD_Hor and FD_Ver from the detected tibial bone in KBD patients and subgroups were lower than controls, except FD_Ver in lateral trabecular bone. Our results indicate that micro-scale in bone texture in KBD-affected knees can be quantitatively examined from plain radiographs using an advanced image analysis.

Trabecular bone texture detected by plain radiography is associated with MRI-defined osteophytes in finger joints of women without radiographic osteoarthritis

OBJECTIVE

To examine associations between trabecular bone (TB) texture and magnetic resonance imaging (MRI)-defined osteophytes in finger joints without radiographic osteoarthritis (OA) using an augmented variance orientation transform (AVOT) method.

DESIGN

In a cross-sectional study, associations of the TB texture and osteophytes were examined in 21 women with mean (standard deviation) age of 69.9 (5.3) from the Oslo Hand OA cohort. The AVOT was applied to distal and proximal TB regions selected on hand radiographs of the subjects. The regions were adjacent to 57 finger joints (24 distal and 33 proximal interphalangeal) without radiographic OA (Kellgren-Lawrence [KL] grade 0), without MRI-defined joint space narrowing (JSN), bone marrow lesions (BMLs), attrition, erosion, cysts, sclerosis, malalignment (all MRI grades 0) and without or only with mild synovitis (MRI grade 0 or 1). Bone texture parameters were calculated: mean fractal dimension (FD_MEAN), FDs in the horizontal (FD_H) and vertical (FD_V) directions, and along the roughest part (FD_Sta). Associations between the parameters categorized into groups using tertiles and osteophytes were evaluated using logistic regression adjusted for age.

RESULTS

Lower FD_Sta and FD_V in the distal TB regions were associated with increased odds of MRI-defined osteophytes (P < 0.037 for linear trend). No statistically significant associations were found for the proximal regions.

CONCLUSIONS

Lower mean roughness and lower roughness in vertical and roughest directions of the proximal TB texture are associated with MRI-defined osteophytes in finger joints without radiographic OA. These findings suggest that TB texture may be a useful marker for detecting early hand OA.

Subchondral tibial bone texture predicts the incidence of radiographic knee osteoarthritis: data from the Osteoarthritis Initiative

OBJECTIVES

To evaluate whether trabecular bone texture (TBT) parameters measured on computed radiographs (CR) could predict the onset of radiographic knee osteoarthritis (OA).

MATERIALS AND METHODS

Subjects from the Osteoarthritis Initiative (OAI) with no sign of radiographic OA at baseline were included. Cases that developed either a global radiographic OA defined by the Kellgren-Lawrence (KL) scale, a joint space narrowing (JSN) or tibial osteophytes (TOS) were compared with the controls with no changes after 48 months of follow-up. Baseline bilateral fixed flexion CR were analyzed using a fractal method to characterize the local variations. The prediction was explored using logistic regression models evaluated by the area under the receiver operating characteristic curves (AUC).

RESULTS

From the 344 knees, 79 (23%) developed radiographic OA after 48 months, 44 (13%) developed progressive JSN and 59 (17%) developed osteophytes. Neither age, gender and BMI, nor their combination predicted poorer KL (AUC 0.57), JSN or TOS (AUC 0.59) scores. The inclusion of the TBT parameters in the models improved the global prediction results for KL (AUC 0.69), JSN (AUC 0.73) and TOS (AUC 0.71) scores.

CONCLUSIONS

Several differences were found between the models predictive of three different outcomes (KL, JSN and TOS), indicating different underlying mechanisms. These results suggest that TBT parameters assessed when radiographic signs are not yet apparent on radiographs may be useful in predicting the onset of radiological tibiofemoral OA as well as identifying at-risk patients for future clinical trials.

Automated selection of bone texture regions on hand radiographs: Data from the Osteoarthritis Initiative

Manual selection of finger trabecular bone texture regions on hand X-ray images is time-consuming, tedious, and observer-dependent. Therefore, we developed an automated method for the region selection. The method selects square trabecular bone regions of interest above and below the second to fifth distal and proximal interphalangeal joints. Two regions are selected per joint (16 regions per hand). The method consists of four integral parts: (1) segmentation of a radiograph into hand and background, (2) identification of finger regions, (3) localization of center points of heads of distal phalanges and the distal interphalangeal, proximal interphalangeal, and metacarpophalangeal joints, and (4) placement of the regions of interest under and above the distal and proximal interphalangeal joints. A gold standard was constructed from regions selected by two observers on 40 hand X-ray images taken from Osteoarthritis Initiative cohort. Datasets of 520 images were generated from the 40 images to study the effects of hand and finger positioning. The accuracy in regions selection and the agreement in calculating five directional fractal parameters were evaluated against the gold standard. The accuracy, agreement, and effects of hand and finger positioning were measured using similarity index (0 for no overlap and 1 for entire overlap) and interclass correlation coefficient as appropriate. A high accuracy in selecting regions (similarity index ≥ 0.79) and a good agreement in fractal parameters (interclass correlation coefficient ≥ 0.58) were achieved. Hand and finger positioning did not affect considerably the region selection (similarity index ≥ 0.70). These results indicate that the method developed selects bone regions on hand X-ray images with accuracy sufficient for fractal analyses of bone texture.

Imaging of osteoarthritis (OA): What is new?

In daily clinical practice, conventional radiography is still the most applied imaging technique to supplement clinical examination of patients with suspected osteoarthritis (OA); it may not always be needed for diagnosis. Modern imaging modalities can visualize multiple aspects of the joint, and depending on the diagnostic need, radiography may no longer be the modality of choice. Magnetic resonance imaging (MRI) provides a complete assessment of the joint and has a pivotal role in OA research. Computed tomography (CT) and nuclear medicine offer alternatives in research scenarios, while ultrasound can visualize bony and soft-tissue pathologies and is highly feasible in the clinic. In this chapter, we overview the recent literature on established and newer imaging modalities, summarizing their ability to detect and quantify the range of OA pathologies and determining how they may contribute to early OA diagnosis. This accurate imaging-based detection of pathologies will underpin true understanding of much needed structure-modifying therapies.