Search

Objectives: This retrospective single-center analysis aimed to evaluate whether artificial intelligence can detect type 2 diabetes mellitus by evaluating the pectoral muscle on digital breast tomosynthesis (DBT). Material method: An analysis of 11,594 DBT images of 287 consecutive female patients (mean age 60, range 40–77 years) was conducted using convolutional neural networks (EfficientNetB5). The inclusion criterion was left-sided screening images with unsuspicious interpretation who also had a current glycosylated hemoglobin A1c (HBA1c) % value. The exclusion criteria were inadequate imaging, history of breast cancer, and/or diabetes mellitus. HbA1c values between 5.6 and 6.4% were categorized as prediabetic, and those with values ≥ 6.5% were categorized as diabetic. A recorded HbA1c ≤ 5.5% served as the control group. Each group was divided into 3 subgroups according to age. Images were subjected to pattern analysis parameters then cropped and resized in a format to contain only pectoral muscle. The dataset was split into 85% for training and 15% for testing the model's performance. The accuracy rate and F1-score were selected as performance indicators. Results: The training process was concluded in the 15th epoch, each comprising 1000 steps, with an accuracy rate of 92% and a loss of only 0.22. The average specificity and sensitivity for all 3 groups were 95%. The F1-score was 0.95. AUC-ROC was 0.995. PPV was 94%, and NPV was 98%. Conclusion: Our study presented a pioneering approach, applying deep learning for the detection of diabetes mellitus status in women using pectoral muscle images and was found to function with an accuracy rate of 92%. Critical relevance statement: AI can differentiate pathological changes within pectoral muscle tissue by assessing radiological images and maybe a potential diagnostic tool for detecting diabetes mellitus and other diseases that affect muscle tissues. Key points: • AI may have an opportunistic use as a screening exam for diabetes during digital breast tomosynthesis. • This technique allows for early and non-invasive detection of diabetes mellitus by AI. • AI may have broad applications in detecting pathological changes within muscle tissue. [ABSTRACT FROM AUTHOR]

Breast tumors are the major malignancy in females and diagnostic systems using artificial intelligence algorithms for breast imaging have shown promising results. Among many algorithms, a deep convolutional neural network (DCNN) using K-means clustering and a multiclass support vector machine model enhance the precision of categorizing breast tumors from mammogram images. Nonetheless, effective breast tumor identification is still difficult without partitioning the pectoral muscle (PM) boundary from the remaining breast area. Therefore, this article proposes an Ensemble-Net model by ensembling the transfer learning model with different pre-trained CNN structures for partitioning the PM boundary from the remaining breast area in the mammographic scans. The segmentation process has 2 phases. In the initial phase, different region-of-interests are generated that include the object according to the input images. In the secondary phase, the object class is predicted after the areas of bounding boxes are refined and a pixel-range mask is created for the entity. These 2 different phases are associated with the backbone structure which creates the pyramid hierarchy of DCNN to acquire the features from the raw images. Moreover, it employs global average pooling followed by the softmax classification to recognize the normal, benign and malignant cases. Finally, the experimental outcomes demonstrate that the Ensemble-Net achieves 96.72% accuracy than the other classical classifiers. [ABSTRACT FROM AUTHOR]

Concentrations of 12 metals (As, Ba, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb and Zn) were examined in the pectoral and thigh muscle of great cormorants (Phalacrocorax carbo). The samples were collected from Central Tisza-Jászság Nature Conservation Area in Hungary. The tissue samples were analysed by inductively coupled plasma optical emission spectroscopy (ICP-OES). The aim of the study was to examine the impacts of heavy metal pollution on the water birds, determine the concentrations of the abovementioned metals in the different muscle tissues of these wetland birds, and provide the basic materials for monitoring the environmental pollution. Among the investigated elements/metals, the detected concentrations of As, Ba, Cd, Co, Cr, Mo and Ni were below the detection limit. Higher concentration of Cu, Hg, Mn and Pb was measured in the pectoral muscle compared to the thigh muscle, but only in the case of Cu and Mn were found significant differences between the tissues. In the case of the Zn concentration, the higher value was detected in the thigh muscle. There were no statistical differences between males and females in either metal concentrations. [ABSTRACT FROM AUTHOR]

The pectoral muscle is the high-intensity region in most mediolateral oblique (MLO) views of mammograms. Since it appears at the same intensity as most abnormalities it should be removed for successful classification. Removal of pectoral muscle is often a challenging task since its position, size and shape are different for different patients and it may not occur at all. In this paper, an efficient technique for the detection and removal of pectoral muscle is proposed. The algorithm is tested and proved efficient over a wide range of pectoral muscle types and datasets based on IOU and RMSE value. [ABSTRACT FROM AUTHOR]

Phenotypic flexibility in avian metabolic rates and body composition have been well-studied in high-latitude species, which typically increase basal metabolic rate (BMR) and summit metabolism (Msum) when acclimatized to winter conditions. Patterns of seasonal metabolic acclimatization are more variable in lower-latitude birds that experience milder winters, with fewer studies investigating adjustments in avian organ and muscle masses in the context of metabolic flexibility in these regions. We quantified seasonal variation (summer vs winter) in the masses of organs and muscles frequently associated with changes in BMR (gizzard, intestines and liver) and Msum (heart and pectoral muscles), in white-browed sparrow-weavers (Plocepasser mahali). We also measured pectoral muscle thickness using a portable ultrasound system to determine whether we could non-lethally estimate muscle size. A concurrent study measured seasonal changes in BMR and Msum in the same population of sparrow-weavers, but different individuals. There was no seasonal variation in the dry masses of the gizzard, intestines or liver of sparrow-weavers, and during the same period, BMR did not vary seasonally. We found significantly higher heart (~ 18% higher) and pectoral muscle (~ 9% higher) dry mass during winter, although ultrasound measurements did not detect seasonal changes in pectoral muscle size. Despite winter increases in pectoral muscle mass, Msum was ~ 26% lower in winter compared to summer. To the best of our knowledge, this is the first study to report an increase in avian pectoral muscle mass but a concomitant decrease in thermogenic capacity. [ABSTRACT FROM AUTHOR]

Arteriovenous malformation of pectoralis muscle is a rare but known entity that usually presents as a confusing finding in screening mammogram. A vascular malformation large enough to occupy the contour of breast is not reported in the literature. A screen detected lesion is most likely to be left alone with observation and rarely get excised surgically. We present a large symptomatic breast lump imaged in a 3D mammogram and underwent wide excision of the entire vascular tumour successfully and obtained a biopsy confirmation of the lesion. [ABSTRACT FROM AUTHOR]

Purpose: Accurately detecting and removing pectoral muscle areas depicting on mediolateral oblique (MLO) view mammograms are an important step to develop a computer-aided detection scheme to assess global mammographic density or tissue patterns. This study aims to develop and test a new fully automated, accurate and robust method for segmenting pectoral muscle in MLO mammograms. Methods: The new method includes the following steps. First, a small rectangular region in the top-left corner of the MLO mammogram which may contain pectoral muscle is captured and enhanced by the fractional differential method. Next, an improved iterative threshold method is applied to segment a rough binary boundary of the pectoral muscle in the small region. Then, a rough contour is fitted with the least squares method on the basis of points of the rough boundary. Last, the fitting contour is subjected to local active contour evolution to obtain the final pectoral muscle segmentation line. The method has been tested on 720 MLO mammograms.Results: The segmentation results generated using the new scheme were evaluated by two expert mammographic radiologists using a 5-scale rating system. More than 65% were rated above scale 3. When assessing the segmentation results generated using Hough transform, morphologic thresholding methods and Unet-based model, less than 20%, 35% and 47% of segmentation results were rated above scale 3 by two radiologists, respectively. Quantitative data analysis results show that the Dice coefficient of 0.986 ± 0.005 is obtained. In addition, the mean rate of errors and Hausdorff distance between the contours detected by automated and manual segmentation are FP = 1.71 ± 3.82%, FN = 5.20 ± 3.94% and 2.75 ± 1.39 mm separately.Conclusion: The proposed method can be used to segment the pectoral muscle in MLO mammograms with higher accuracy and robustness. [ABSTRACT FROM AUTHOR]

This paper presents a review of recent advances in the development of methods for segmentation of the breast boundary and the pectoral muscle in mammograms. Regardless of improvement of imaging technology, accurate segmentation of the breast boundary and detection of the pectoral muscle are still challenging tasks for image processing algorithms. In this paper, we discuss problems related to mammographic image preprocessing and accurate segmentation. We review specific methods that were commonly used in most of the techniques proposed for segmentation of mammograms and discuss their advantages and disadvantages. Comparative analysis of the methods reported on is made difficult by variations in the datasets and procedures of evaluation used by the authors. We attempt to overcome some of these limitations by trying to compare methods which used the same dataset and have some similarities in approaches to the breast boundary segmentation and detection of the pectoral muscle. In this paper, we will address the most often used methods for segmentation such as thresholding, morphology, region growing, active contours, and wavelet filtering. These methods, or their combinations, are the ones most used in the last decade by the majority of work published in this image processing domain. [ABSTRACT FROM AUTHOR]

Detection of mass in mammogram for early diagnosis of breast cancer is a significant assignment in the reduction of the mortality rate. However, in some cases, screening of mass is difficult task for radiologist, due to variation in contrast, fuzzy edges and noisy mammograms. Masses and micro-calcifications are the distinctive signs for diagnosis of breast cancer. This paper presents, a method for mass enhancement using piecewise linear operator in combination with wavelet processing from mammographic images. The method includes, artifact suppression and pectoral muscle removal based on morphological operations. Finally, mass segmentation for detection using adaptive threshold technique is carried out to separate the mass from background. The proposed method has been tested on 130 (45 + 85) images with 90.9 and 91 % True Positive Fraction (TPF) at 2.35 and 2.1 average False Positive Per Image(FP/I) from two different databases, namely Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM). The obtained results show that, the proposed technique gives improved diagnosis in the early breast cancer detection. [ABSTRACT FROM AUTHOR]

Mammography is a primary imaging method for breast cancer diagnosis. It is an important issue to accurately identify and separate pectoral muscles (PM) from breast tissues. Hough-transform-based methods are commonly adopted for PM detection. But their performances are susceptible when PM edges cannot be depicted by straight lines. In this study, we present a new pectoral muscle identification algorithm which utilizes statistical features of pixel responses. First, the Anderson-Darling goodness-of-fit test is used to extract a feature image by assuming non-Gaussianity for PM boundaries. Second, a global weighting scheme based on the location of PM was applied onto the feature image to suppress non-PM regions. From the weighted image, a preliminary set of pectoral muscles boundary components is detected via row-wise peak detection. An iterative procedure based on the edge continuity and orientation is used to determine the final PM boundary. Our results on a public mammogram database were assessed using four performance metrics: the false positive rate, the false negative rate, the Hausdorff distance, and the average distance. Compared to previous studies, our method demonstrates the state-of-art performance in terms of four measures. [ABSTRACT FROM AUTHOR]

In migratory birds, seasonal factors interacting at different stages of the annual cycle can influence individual life histories. These have been well documented for Nearctic-Neotropical birds. Yet, seasonal interactions between the wintering, migration, and breeding periods have not been demonstrated for Palearctic-African passerine migrants. We tested whether variation in long- and short-term dietary choice of the Garden Warbler Sylvia borin can influence events during the subsequent spring migration from the African winter quarters to the Palearctic breeding grounds. Using bone collagen and muscle carbon stable isotope (δC) analysis, we assessed the relationships between dietary history, body condition, and migration timing in the Garden Warbler during a return migration from Africa. We predicted that Garden Warblers arriving early will have significantly different muscle and collagen δC relative to those arriving later. Whereas muscle δC (referring to events in the immediate past) was not related to body condition, we found a strong association between body condition and collagen δC signatures (representing the integration of long-term events). Collagen and muscle δC indicate that birds passing through later originated from moister or cooler geographic areas. The observed variation in isotope signatures might relate to differences in habitat and geographic/population origin, or in dietary intake. [ABSTRACT FROM AUTHOR]

In medio-lateral oblique view of mammogram, pectoral muscle may sometimes affect the detection of breast cancer due to their similar characteristics with abnormal tissues. As a result pectoral muscle should be handled separately while detecting the breast cancer. In this paper, a novel approach for the detection of pectoral muscle using average gradient- and shape-based feature is proposed. The process first approximates the pectoral muscle boundary as a straight line using average gradient-, position-, and shape-based features of the pectoral muscle. Straight line is then tuned to a smooth curve which represents the pectoral margin more accurately. Finally, an enclosed region is generated which represents the pectoral muscle as a segmentation mask. The main advantage of the method is its' simplicity as well as accuracy. The method is applied on 200 mammographic images consisting 80 randomly selected scanned film images from Mammographic Image Analysis Society (mini-MIAS) database, 80 direct radiography (DR) images, and 40 computed radiography (CR) images from local database. The performance is evaluated based upon the false positive (FP), false negative (FN) pixel percentage, and mean distance closest point (MDCP). Taking all the images into consideration, the average FP and FN pixel percentages are 4.22%, 3.93%, 18.81%, and 6.71%, 6.28%, 5.12% for mini-MIAS, DR, and CR images, respectively. Obtained MDCP values for the same set of database are 3.34, 3.33, and 10.41 respectively. The method is also compared with two well-known pectoral muscle detection techniques and in most of the cases, it outperforms the other two approaches. [ABSTRACT FROM AUTHOR]

Background: Augmentation mastopexy has historically challenged the creativity of plastic surgeons. Recurrent breast ptosis is the main cause for revision after such a primary operation. Avoiding the need for reoperation and achieving long-term projection and upper pole fullness have been the main focus for the work of many authors. In this study, a new approach for a stable and lasting breast shape based on the use of the pectoral muscle was conceived. Method: Augmentation mastopexy was performed for patients with breast ptosis grades 2 and 3 according to Regnault's classification. With the proposed surgical technique, a loop of the pectoral muscle was used to keep the implant in a stable position. An inferior chest wall-based flap optimized coverage of the lower pole of the prosthesis. Results: From 2008 to 2009, 22 patients underwent augmentation mastopexy using the described technique. Of these 22 patients, 12 were indicated for grade 2 and 10 for grade 3 ptosis. The mean follow-up period was 11.9 months. A high level of satisfaction was observed. No major complications occurred. Conclusions: Augmentation mastopexy using a loop of the pectoral muscle to hold the implant is a new and effective way to obtain long-lasting projection and upper pole fullness. [ABSTRACT FROM AUTHOR]

The pectoral muscle is the biggest organ within a passerine bird. It provides flight locomotion and is known to act as a protein source during periods with increased protein demands or decreased protein availability. The mass of the flight muscle is dynamic and changes during juvenile growth, reproduction, seasonal acclimatization, fasting and migration. Thus, a tool that accurately and non-invasively quantifies this phenotypic flexibility in flight muscle mass is of interest to ornithologists. We provide a calibration and validation of a "muscle meter" device designed to accurately measure the shape of the flight muscle. For two species of different size, the European starling ( Sturnus vulgaris) and the garden warbler ( Sylvia borin), we compared the accuracy and precision of different linear regression models for predicting flight muscle mass. The multifactorial linear regression model with the most support for both species included 'muscle meter score' (mm), tarsus length and body mass ( m), although a simpler model with mm and m had as much support for predicting flight muscle mass of European starlings. A validation exercise revealed that flight muscle mass of these two species could be estimated with a relative error of about 3%. The muscle meter is a simple device, easy and quick to handle, that can reliably and non-invasively estimate flight muscle mass of captive and wild birds when used in conjunction with standard measurements of tarsus length and m. [ABSTRACT FROM AUTHOR]

Automatic pectoral muscle removal on medio-lateral oblique (MLO) view of mammogram is an essential step for many mammographic processing algorithms. However, it is still a very difficult task since the sizes, the shapes and the intensity contrasts of pectoral muscles change greatly from one MLO view to another. In this paper, we propose a novel method based on a discrete time Markov chain (DTMC) and an active contour model to automatically detect the pectoral muscle boundary. DTMC is used to model two important characteristics of the pectoral muscle edge, i.e., continuity and uncertainty. After obtaining a rough boundary, an active contour model is applied to refine the detection results. The experimental results on images from the Digital Database for Screening Mammography (DDSM) showed that our method can overcome many limitations of existing algorithms. The false positive (FP) and false negative (FN) pixel percentages are less than 5% in 77.5% mammograms. The detection precision of 91% meets the clinical requirement. [ABSTRACT FROM AUTHOR]

The formation of a skeletal muscle fiber begins with the withdrawal of committed mononucleated precursors from the cell cycle. These myoblasts elongate while aligning with each other, guided by recognition between their membranes. This step is followed by cell fusion and the formation of long striated multinucleated myotubes. We used methyl-ß-cyclodextrin (MCD) in primary cultured chick skeletal muscle cells to deplete membrane cholesterol and investigate its role during myogenesis. MCD promoted a significant increase in the expression of troponin T, enhanced myoblast fusion, and induced the formation of large multinucleated myotubes with nuclei being clustered centrally and not aligned at the cell periphery. MCD myotubes were striated, as indicated by sarcomeric a-actinin staining, and microtubule and desmin filament distribution was not altered. Pre-fusion MCD-treated myoblasts formed large aggregates, with cadherin and ß-catenin being accumulated in cell adhesion contacts. We also found that the membrane microdomain marker GM1 was not present as clusters in the membrane of MCD-treated myoblasts. Our data demonstrate that cholesterol is involved in the early steps of skeletal muscle differentiation. [ABSTRACT FROM AUTHOR]

This study investigated the evolution of a transition metal ion-binding cluster ([H–X–X–X–H]n; Tx) in the alternatively spliced NH2-terminal variable region of avian pectoral muscle troponin T (TnT). Encoded by avian fast skeletal muscle TnT-specific P exons, Tx-like structures were expressed in the breast muscle TnT's of almost all birds examined. Their presence results in the developmentally up-regulated high molecular weight pectoral muscle TnT. Sequence analysis and metal affinity chromatography revealed that in Galliformes and Craciformes, the Tx structure evolved into multiple H–X–X–X–H pairs with a high-affinity metal-binding capacity. Turkey, chicken, quail, and curassow breast muscle TnT's contain nine, seven, four, and three consecutive or closely located metal-binding sites, respectively, in the NH2-terminal region. The metal-binding affinity of the Tx element increased as the number of His pairs increased due to the duplication of P exons and the conversion of other exon sequences. The data show two related components of avian pectoral muscle TnT evolution: a larger, more acidic NH2-terminal segment and a cluster of transition metal-binding sites, both of which may have functional significance for their selection value. The evolution of the Tx segment in the NH2-terminal variable region of avian pectoral muscle TnT demonstrates a functional divergence on the basis of tolerance to structural drifting. [ABSTRACT FROM AUTHOR]

By mammographic screening we had detected six asymtomatic women who showed numerous tiny and well-delineated round to ovoid microcalcifications superimposed on pectoral shadows, in the oblique medio-lateral (OML) view. Our objective was to achieve a better evaluation of these calcifications and investigate their origin. Magnified mammograms of pectoral muscles were done in the six women. A questionnaire concerning the patients' diets was also administered. Trichinella antibody titres were quantified by sero-agglutination. Microcalcifications within pectoral muscle fibres were demonstrated in all the cases. Five women admitted to having eaten home-made pork products in the past. One of them showed a slightly elevated antibody titre. We confirmed the suspected diagnosis of calcified trichinosis by a surgical biopsy of the pectoral muscle performed on one of the patients. We conclude that chronic calcified trichinosis of the pectoral muscle can be visualised in the OML view of a conventional mammogram. The mammographic appearance of this entity is very characteristic and biopsy would not be required for its diagnosis in the future. [ABSTRACT FROM AUTHOR]