Texture analysis of foot sole soft tissue images in diabetic neuropathy using wavelet transform

Real-time denoising of ultrasound images based on deep learning

Ultrasound images are widespread in medical diagnosis for muscle-skeletal, cardiac, and obstetrical diseases, due to the efficiency and non-invasiveness of the acquisition methodology. However, ultrasound acquisition introduces noise in the signal, which corrupts the resulting image and affects further processing steps, e.g. segmentation and quantitative analysis. We define a novel deep learning framework for the real-time denoising of ultrasound images. Firstly, we compare state-of-the-art methods for denoising (e.g. spectral, low-rank methods) and select WNNM (Weighted Nuclear Norm Minimisation) as the best denoising in terms of accuracy, preservation of anatomical features, and edge enhancement. Then, we propose a tuned version of WNNM (tuned-WNNM) that improves the quality of the denoised images and extends its applicability to ultrasound images. Through a deep learning framework, the tuned-WNNM qualitatively and quantitatively replicates WNNM results in real-time. Finally, our approach is general in terms of its building blocks and parameters of the deep learning and high-performance computing framework; in fact, we can select different denoising algorithms and deep learning architectures.

Plantar soft tissues and Achilles tendon thickness and stiffness in people with diabetes: a systematic review

BACKGROUND

Diabetes mellitus is associated with changes in soft tissue structure and function. However, the directionality of this change and the extent to which either tissue thickness or stiffness contributes to the pathogenesis of diabetes-related foot ulcerations is unclear. Hence, this systematic review aims to summarise the existing evidence for soft tissue structural differences in the feet of people with and without diabetes.

METHODS

In compliance with MOOSE and PRISMA guidelines, AMED, CINAHL, MEDLINE, ProQuest Health & Medical Collection, ProQuest Nursing & Allied Health Database, and Web of Science electronic databases were systematically searched for studies published from database inception until 1st October 2020 [Prospero CRD42020166614]. Reference lists of included studies were further screened. Methodological quality was appraised using a modified critical appraisal tool for quantitative studies developed by McMaster University.

RESULTS

A total of 35 non-randomised observational studies were suitable for inclusion. Within these, 20 studies evaluated plantar tissue thickness, 19 studies evaluated plantar tissue stiffness, 9 studies evaluated Achilles tendon thickness and 5 studies evaluated Achilles tendon stiffness outcomes. No significant differences in plantar tissue thickness were found between people with and without diabetes in 55% of studies (11/20), while significantly increased plantar tissue stiffness was found in people with diabetes in 47% of studies (9/19). Significantly increased Achilles tendon thickness was found in people with diabetes in 44% of studies (4/9), while no significant differences in Achilles tendon stiffness were found between people with and without diabetes in 60% of studies (3/5).

CONCLUSIONS

This systematic review found some evidence of soft tissue structural differences between people with and without diabetes. However, uncertainty remains whether these differences independently contribute to diabetes-related foot ulcerations. The heterogeneity of methodological approaches made it difficult to compare across studies and methodological quality was generally inadequate. High-quality studies using standardised and validated assessment techniques in well-defined populations are required to determine more fully the role of structural tissue properties in the pathogenesis of diabetes-related foot ulcerations.

Modified Quality Threshold Clustering for Temporal Analysis and Classification of Lung Lesions

Lung cancer is the type of cancer that most often kills after the initial diagnosis. To aid the specialist in its diagnosis, temporal evaluation is a potential tool for analyzing indeterminate lesions, which may be benign or malignant, during treatment. With this goal in mind, a methodology is herein proposed for the analysis, quantification, and visualization of changes in lung lesions. This methodology uses a modified version of the quality threshold clustering algorithm to associate each voxel of the lesion to a cluster, and changes in the lesion over time are defined in terms of voxel moves to another cluster. In addition, statistical features are extracted for classification of the lesion as benign or malignant. To develop the proposed methodology, two databases of pulmonary lesions were used, one for malignant lesions in treatment (public) and the other for indeterminate cases (private). We determined that the density change percentage varied from 6.22% to 36.93% of lesion volume in the public database of malignant lesions under treatment and from 19.98% to 38.81% in the private database of lung nodules. Additionally, other inter-cluster density change measures were obtained. These measures indicate the degree of change in the clusters and how each of them is abundant in relation to volume. From the statistical analysis of regions in which the density changes occurred, we were able to discriminate lung lesions with an accuracy of 98.41%, demonstrating that these changes can indicate the true nature of the lesion. In addition to visualizing the density changes occurring in lesions over time, we quantified these changes and analyzed the entire set through volumetry, which is the technique most commonly used to analyze changes in pulmonary lesions.

A medical imaging analysis system for trigger finger using an adaptive texture-based active shape model (ATASM) in ultrasound images

Trigger finger has become a prevalent disease that greatly affects occupational activity and daily life. Ultrasound imaging is commonly used for the clinical diagnosis of trigger finger severity. Due to image property variations, traditional methods cannot effectively segment the finger joint’s tendon structure. In this study, an adaptive texture-based active shape model method is used for segmenting the tendon and synovial sheath. Adapted weights are applied in the segmentation process to adjust the contribution of energy terms depending on image characteristics at different positions. The pathology is then determined according to the wavelet and co-occurrence texture features of the segmented tendon area. In the experiments, the segmentation results have fewer errors, with respect to the ground truth, than contours drawn by regular users. The mean values of the absolute segmentation difference of the tendon and synovial sheath are 3.14 and 4.54 pixels, respectively. The average accuracy of pathological determination is 87.14%. The segmentation results are all acceptable in data of both clear and fuzzy boundary cases in 74 images. And the symptom classifications of 42 cases are also a good reference for diagnosis according to the expert clinicians’ opinions.

Statistical tools for the temporal analysis and classification of lung lesions

BACKGROUND AND OBJECTIVE

Lung cancer remains one of the most common cancers globally. Temporal evaluation is an important tool for analyzing the malignant behavior of lesions during treatment, or of indeterminate lesions that may be benign. This work proposes a methodology for the analysis, quantification, and visualization of small (local) and large (global) changes in lung lesions. In addition, we extract textural features for the classification of lesions as benign or malignant.

METHODS

We employ the statistical concept of uncertainty to associate each voxel of a lesion to a probability that changes occur in the lesion over time. We employ the Jensen divergence and hypothesis test locally to verify voxel-to-voxel changes, and globally to capture changes in lesion volumes.

RESULTS

For the local hypothesis test, we determine that the change in density varies by between 3.84 and 40.01% of the lesion volume in a public database of malignant lesions under treatment, and by between 5.76 and 35.43% in a private database of benign lung nodules. From the texture analysis of regions in which the density changes occur, we are able to discriminate lung lesions with an accuracy of 98.41%, which shows that these changes can indicate the true nature of the lesion.

CONCLUSION

In addition to the visual aspects of the density changes occurring in the lesions over time, we quantify these changes and analyze the entire set using volumetry. In the case of malignant lesions, large b-divergence values are associated with major changes in lesion volume. In addition, this occurs when the change in volume is small but is associated with significant changes in density, as indicated by the histogram divergence. For benign lesions, the methodology shows that even in cases where the change in volume is small, a change of density occurs. This proves that even in lesions that appear stable, a change in density occurs.

Differences in the mechanical characteristics of plantar soft tissue between ulcerated and non-ulcerated foot

AIMS

The purpose of this study was to investigate the differences in mechanical properties of the plantar soft tissue between the ulcerated and non-ulcerated feet in patients with diabetic neuropathy.

METHODS

Thirty nine patients who met the inclusion criteria participated in this study. Ten out of 39 participants had an active ulcer at a site other than the plantar heel and the first metatarsal head. Real time ultrasound elastography was performed to measure the soft tissue thickness and stiffness of the heel pad and sub-metatarsal fat pad. To account for the qualitative nature of conventional real time elastography, relative tissue stiffness was assessed against that of a standardised ultrasound standoff material.

RESULTS

The results indicated that the ulcerated group had a significantly lower heel pad relative stiffness (t (37)=2.559, P=0.015, η2=0.150) in the left foot.

CONCLUSIONS

The observed difference in the stiffness of the heel pad between the ulcerated and non-ulcerated feet indicates a possible link between tissue mechanics and ulceration. Further analysis of the data proposed in this study provided a quantitative assessment of plantar fat pad deformability which can contribute to understanding the role of tissue biomechanics in ulceration.

Application of DCT-derived parameters for early detection of polyneuropathy in diabetic patients

Diabetic foot is one of the most severe complications of diabetes. Early diagnosis of this syndrome can ensure proper medical care and adequate treatment. Various image analysis methods can be used to speed up the diagnosis process, and automated diagnosis can be applied as a screening technique to reduce its cost. Introducing auxiliary diagnostic parameters may help to detect polyneuropathy or neuropathy, both of which often precede the appearance of diabetic foot syndrome. The present paper describes a study performed on a group of diabetic patients by analyzing plantar pressure distribution images. As part of this study, 2D discrete cosine transform (DCT) is computed for the forefoot and rearfoot regions of each diabetic subject in a group of 37 patients. Three new DCT-based parameters are introduced to help to detect polyneuropathy or at least indicate that the patient may have polyneuropathy without a time-consuming examination. The results indicate a certain relationship between these parameters and the presence of polyneuropathy. This information could be used in further diagnosis to prevent foot ulcers from developing in patients with diabetes.

Mechanical behavior of intact and low-grade degenerated cartilage / Mechanische Eigenschaften von intaktem und niedriggradig geschädigtem Knorpel

Young's modulus, elastic and plastic deformation, mechanical hardness and load at failure were determined for low-grade degenerated hyaline cartilage in a porcine model. Osteochondral plugs from the medial condyle of 30 female pigs were used. Cartilage defects were classified using the International Cartilage Repair Society (ICRS) protocol. Mechanical hardness was measured using a Shore A testing device. Total stiffness and plastic deformation was evaluated in the range 50-200 N using a 5-mm indenter. The load at failure was then determined. ICRS grade I specimens showed significantly lower stiffness than grade 0 specimens. ICRS grade 0 specimen showed no significant plastic deformation within the load range 25-100 N. In degenerated cartilage, plastic deformation started at a significantly lower load (50 N). The Young's modulus at 25 N in ICRS grade 0 specimens (18.8 MPa) was significantly higher than in grade I (11.1 MPa) or grade II (10.5 MPa) specimens. Intact cartilage showed significantly higher tension at failure and mechanical Shore A hardness. Young's modulus and tension at failure showed strong correlation. Cartilage degeneration is associated with a significant loss of elasticity and mechanical stress resistance. Shore hardness measurement is an adequate method for rapid biomechanical evaluation of cartilage specimens.