Biophysical Properties Of Tissues Research Articles

Likelihood-free posterior estimation and uncertainty quantification for diffusion MRI models

Abstract Diffusion magnetic resonance imaging (dMRI) allows to estimate brain tissue microstructure as well as the connectivity of the white matter (known as tractography). Accurate estimation of the model parameters (by solving the inverse problem) is thus very important to infer the underlying biophysical tissue properties and fiber orientations. Although there has been extensive research on this topic with a myriad of dMRI models, most models use standard nonlinear optimization techniques and only provide an estimate of the model parameters without any information (quantification) about uncertainty in their estimation. Further, the effect of this uncertainty on the estimation of the derived dMRI microstructural measures downstream (e.g., fractional anisotropy) is often unknown and is rarely estimated. To address this issue, we first design a new deep-learning algorithm to identify the number of crossing fibers in each voxel. Then, at each voxel, we propose a robust likelihood-free deep learning method to estimate not only the mean estimate of the parameters of a multi-fiber dMRI model (e.g., the biexponential model), but also its full posterior distribution. The posterior distribution is then used to estimate the uncertainty in the model parameters as well as the derived measures. We perform several synthetic and in-vivo quantitative experiments to demonstrate the robustness of our approach for different noise levels and out-of-distribution test samples. Besides, our approach is computationally fast and requires an order of magnitude less time than standard nonlinear fitting techniques. The proposed method demonstrates much lower error (compared to existing methods) in estimating several metrics, including number of fibers in a voxel, fiber orientation, and tensor eigenvalues. The proposed methodology is quite general and can be used for the estimation of the parameters from any other dMRI model.

Tuning immunity through tissue mechanotransduction.

Immune responses are governed by signals from the tissue microenvironment, and in addition to biochemical signals, mechanical cues and forces arising from the tissue, its extracellular matrix and its constituent cells shape immune cell function. Indeed, changes in biophysical properties of tissue alter the mechanical signals experienced by cells in many disease conditions, in inflammatory states and in the context of ageing. These mechanical cues are converted into biochemical signals through the process of mechanotransduction, and multiple pathways of mechanotransduction have been identified in immune cells. Such pathways impact important cellular functions including cell activation, cytokine production, metabolism, proliferation and trafficking. Changes in tissue mechanics may also represent a new form of ‘danger signal’ that alerts the innate and adaptive immune systems to the possibility of injury or infection. Tissue mechanics can change temporally during an infection or inflammatory response, offering a novel layer of dynamic immune regulation. Here, we review the emerging field of mechanoimmunology, focusing on how mechanical cues at the scale of the tissue environment regulate immune cell behaviours to initiate, propagate and resolve the immune response.

The cell surface hyaluronidase TMEM2 is essential for systemic hyaluronan catabolism and turnover

As a major component of the extracellular matrix, hyaluronan (HA) plays an important role in defining the biochemical and biophysical properties of tissues. In light of the extremely rapid turnover of HA and the impact of this turnover on HA biology, elucidating the molecular mechanisms underlying HA catabolism is key to understanding the in vivo functions of this unique polysaccharide. Here, we show that TMEM2, a recently identified cell surface hyaluronidase, plays an essential role in systemic HA turnover. Employing induced global Tmem2 knockout mice (Tmem2iKO), we determined the effects of Tmem2 ablation not only on the accumulation of HA in bodily fluids and organs, but also on the process of HA degradation in vivo. Within 3 weeks of tamoxifen-induced Tmem2 ablation, Tmem2iKO mice exhibit pronounced accumulation of HA in circulating blood and various organs, reaching levels as high as 40-fold above levels observed in control mice. Experiments using lymphatic and vascular injection of fluorescent HA tracers demonstrate that ongoing HA degradation in the lymphatic system and the liver is significantly impaired in Tmem2iKO mice. We also show that Tmem2 is strongly expressed in endothelial cells in the subcapsular sinus of lymph nodes and in the liver sinusoid, two primary sites implicated in systemic HA turnover. Our results establish TMEM2 as a physiologically relevant hyaluronidase with an essential role in systemic HA catabolism in vivo, acting primarily on the surface of endothelial cells in the lymph nodes and liver.

Multi-modal nonlinear optical and thermal imaging platform for label-free characterization of biological tissue

The ability to characterize the combined structural, functional, and thermal properties of biophysically dynamic samples is needed to address critical questions related to tissue structure, physiological dynamics, and disease progression. Towards this, we have developed an imaging platform that enables multiple nonlinear imaging modalities to be combined with thermal imaging on a common sample. Here we demonstrate label-free multimodal imaging of live cells, excised tissues, and live rodent brain models. While potential applications of this technology are wide-ranging, we expect it to be especially useful in addressing biomedical research questions aimed at the biomolecular and biophysical properties of tissue and their physiology.

CLINICAL EVALUATION OF DIFFUSION WEIGHTED IMAGING OF BREAST MASSES IN FEMALE PATIENTS FROM BIHAR REGION

Breast masses range from benign to malignant with varied etiologies. Fibroadenoma the Commonest benign and invasive ductal carcinomas are the commonest malignant lesions. Breast carcinoma is the most common and the second leading cause of deaths in women. It is present fully accepted that breast magnetic resonance is amongst the most sensitive diagnostic imaging techniques for breast lesions. DWI-MR (diffusion weighted magnetic resonance) provides new and different information about the biophysical properties of tissue. The consequent reduction of macroscopic motion effect makes possible the use of DWI in detection and characterization in breast MRI imaging. These facts and figures defines the need for early detection and treatment of breast for favourable prognosis. DWI has sufficient capacity to diagnose invasive, non-invasive breast lesions and has the ability to provide steady, high-resolution tissue images and there is a need to apply DWI to clinical practice while taking advantage of this high contrast resolution. Diffusion weighted Imaging is a potential resource as an adjuvant to breast MRI to differentiate benign from malignant lesions. Such sequence can be easily added to the standard breast magnetic resonance protocol.
 The present study was planned in Department of Radio- Diagnosis, Katihar Medical College and Hospital, Katihar, Bihar, India. Total 20 cases of the breast lesions refereed to our hospital were evaluated in the present study. Those patients who had come for breast MRI examinations and were detected to have lesions greater than 1 cm in size were included in the study and DWI was performed after obtaining prior consent. Patients who were referred for mammography and sonomammography and who were detected to have solid lesions greater than 1 cm were also included in this study after obtaining prior consent; diffusion-weighted sequences were performed for these patients only to characterize the lesions detected on mammography and sonomammography.
 The data generated from the present study concludes that DWI for breast lesions can differentiate benign from malignant lesions with a high sensitivity and specificity. The usefulness of this technique needs to be further evaluated with larger double-blind studies.
 Keywords: Diffusion Weighted Imaging, DWI, Breast Masses, etc.

Forensic biological research features human tissue to the purpose of the estimation of the post-mortem interval and causing mechanical damage

In the article is given data about the possibility of determining the age of damages and death by the analysis of the elastic properties of biological tissues. The proposed method of determining the prescription of death and mechanical damage by studying the biophysical properties of tissue of the corpse provides an increase in the accuracy of the diagnosis by 20% and reduces the duration of the latter by 1.5 times compared with the prototype, mainly due to the determination of the drop in the voltage level on the sample of the tissue under investigation. The conducted researches require further scientific development.

Understanding the Effects and Adverse Reactions of Deep Brain Stimulation: Is It Time for a Paradigm Shift Toward a Focus on Heterogenous Biophysical Tissue Properties Instead of Electrode Design Only?

Deep brain stimulation (DBS) has been proven to be an effective treatment modality for various late-stage neurological and psychiatric disorders. However, knowledge on the electrical field distribution in the brain tissue is still scarce. Most recent attempts to understand electric field spread were primarily focused on the effect of different electrodes on rather simple tissue models. The influence of microanatomic, biophysical tissue properties in particular has not been investigated in depth. Ethical concerns restrict thorough research on field distribution in human in vivo brain tissue. By means of a simplified model, we investigated the electric field distribution in a broader area of the subthalamic nucleus (STN). Pivotal biophysical parameters including conductivity, permittivity and permeability of brain tissue were incorporated in the model. A brain tissue model was created with the finite element method (FEM). Stimulation was mimicked with parameters used for monopolar stimulation of patients suffering from Parkinson’s disease. Our results were visualized with omnidirectional and segmented electrodes. The stimulated electric field was visualized with superimpositions on a stereotactic atlas (Morel). Owing to the effects of regional tissue properties near the stimulating electrode, marked field distortions occur. Such effects include, for example, isolating effects of heavily myelinated neighboring structures, e.g., the internal capsule. In particular, this may be illustrated through the analysis of a larger coronal area. While omnidirectional stimulation has been associated with vast current leakage, higher targeting precision was obtained with segmented electrodes. Finally, targeting was improved when the influence of microanatomic structures on the electric spread was considered. Our results confirm that lead design is not the sole influence on current spread. An omnidirectional lead configuration does not automatically result in an omnidirectional spread of current. In turn, segmented electrodes do not automatically imply an improved steering of current. Our findings may provide an explanation for side-effects secondary to current leakage. Furthermore, a possible explanation for divergent results in the comparison of the intraoperative awake patient and the postoperative setting is given. Due to the major influence of biophysical tissue properties on electric field shape, the local microanatomy should be considered for precise surgical targeting and optimal hardware implantation.

Neurobiology, not artifacts: Challenges and guidelines for imaging the high risk infant

The search for the brain-basis of atypical development in human infants is challenging because the process of imaging and the generation of the MR signal itself relies on assumptions that reflect biophysical properties of the brain tissue. These assumptions are not inviolate, have been questioned by recent empirical evidence from high risk infant-sibling studies, and to date remain largely underexamined at the between-group level. In particular, I consider recent work showing that infants at High vs. Low familial risk (HR vs. LR, respectively) for developing Autism Spectrum Disorders (ASD) have atypical patterns of head movements during an MR scan that are functionally important—they are linked to future learning trajectories in toddlerhood. Addressing head movement issues in neuroimaging analyses in infant research as well as understanding the causes of these movements from a developmental perspective requires acknowledging the complexity of this endeavor. For example, head movement signatures in infants can interact with experimental task conditions (such as listening to language compared to sleeping), autism risk, and age. How can new knowledge about newborns' individual, subject-specific behavioral differences which may impact MR signal acquisition and statistical inference ignite critical thinking for the field of infant brain imaging across the spectrum of typical and atypical development? Early behavioral differences between HR and LR infant cohorts that are often examples of “artifactual” confounds in MR work provide insight into nascent neurobiological differences, including biophysical tissue properties and hemodynamic response variability, in these and related populations at risk for atypical development. Are these neurobiological drivers of atypical development? This work identifies important knowledge gaps and suggests guidelines at the leading edge of baby imaging science to transform our understanding of atypical brain development in humans. The precise study of the neurobiological underpinnings of atypical development in humans calls for approaches including quantitative MRI (qMRI) pulse sequences, multi-modal imaging (including DTI, MRS, as well as MEG), and infant-specific HRF shapes when modeling BOLD signal.

The Impact of Compressed Femtosecond Laser Pulse Durations on Neuronal Tissue Used for Two-Photon Excitation Through an Endoscope

Accurate intraoperative tumour margin assessment is a major challenge in neurooncology, where sparse tumours beyond the bulk tumour are left undetected under conventional resection. Non-linear optical imaging can diagnose tissue at the sub-micron level and provide functional label-free histopathology in vivo. For this reason, a non-linear endomicroscope is being developed to characterize brain tissue intraoperatively based on multiple endogenous optical contrasts such as spectrally- and temporally-resolved fluorescence. To produce highly sensitive optical signatures that are specific to a given tissue type, short femtosecond pulsed lasers are required for efficient two-photon excitation. Yet, the potential of causing bio-damage has not been studied on neuronal tissue. Therefore, as a prerequisite to clinically testing the non-linear endomicroscope in vivo, the effect of short laser pulse durations (40–340 fs) on ex vivo brain tissue was investigated by monitoring the intensity, the spectral, and the lifetime properties of endogenous fluorophores under 800 and 890 nm two-photon excitation using a bi-modal non-linear endoscope. These properties were also validated by imaging samples on a benchtop multiphoton microscope. Our results show that under a constant mean laser power, excitation pulses as short as 40 fs do not negatively alter the biochemical/ biophysical properties of tissue even for prolonged irradiation.

Sensitivity of thermophysiological models of cryoablation to the thermal and biophysical properties of tissues

Advancement in biomedical simulation and imaging modality have catalysed the development of in silico predictive models for cryoablation. However, one of the main challenges in ensuring the accuracy of the model prediction is the use of proper thermal and biophysical properties of the patient. These properties are difficult to measure clinically and thus, represent significant uncertainty that can affect the model prediction. Motivated by this, a sensitivity analysis is carried out to identify the model parameters that have the most significant impact on the lesion size during cryoablation. The study is initially carried out using the Morris method to screen for the most dominant parameters. Once determined, analysis of variance (ANOVA) is performed to quantitatively rank the order of importance of each parameter and their interactions. Results from the sensitivity analysis revealed that blood perfusion, water transport and ice nucleation parameters are critical in predicting the lesion size, suggesting that the acquisition of these parameters should be prioritised to ensure the accuracy of the model prediction.

Improved MR‐based characterization of engineered cartilage using multiexponential T2 relaxation and multivariate analysis

Noninvasive monitoring of tissue quality would be of substantial use in the development of cartilage tissue engineering strategies. Conventional MR parameters provide noninvasive measures of biophysical tissue properties and are sensitive to changes in matrix development, but do not clearly distinguish between groups with different levels of matrix development. Furthermore, MR outcomes are nonspecific, with particular changes in matrix components resulting in changes in multiple MR parameters. To address these limitations, we present two new approaches for the evaluation of tissue engineered constructs using MR, and apply them to immature and mature engineered cartilage after 1 and 5 weeks of development, respectively. First, we applied multiexponential T(2) analysis for the quantification of matrix macromolecule-associated water compartments. Second, we applied multivariate support vector machine analysis using multiple MR parameters to improve detection of degree of matrix development. Monoexponential T(2) values decreased with maturation, but without further specificity. Much more specific information was provided by multiexponential analysis. The T(2) distribution in both immature and mature constructs was qualitatively comparable to that of native cartilage. The analysis showed that proteoglycan-bound water increased significantly during maturation, from a fraction of 0.05 ± 0.01 to 0.07 ± 0.01. Classification of samples based on individual MR parameters, T(1), T(2), k(m) or apparent diffusion coefficient, showed that the best classifiers were T(1) and k(m), with classification accuracies of 85% and 84%, respectively. Support vector machine analysis improved the accuracy to 98% using the combination (k(m), apparent diffusion coefficient). These approaches were validated using biochemical and Fourier transform infrared imaging spectroscopic analyses, which showed increased proteoglycan and collagen with maturation. In summary, multiexponential T(2) and multivariate support vector machine analyses provide improved sensitivity to changes in matrix development and specificity to matrix composition in tissue engineered cartilage. These approaches show substantial potential for the evaluation of engineered cartilage tissue and for extension to other tissue engineering constructs.

Sonication-induced unfolding proteins

The methodology of predicting sonication-induced unfolding proteins (SUP) is presented in this study. The methodology bases on: (a) simulation of SUP by the excessive deviations of protein domains in regime of damped forced vibrations caused by critical level of involved acoustic energy, which is associated with temperature rise and acoustic pressure; (b) simulation of stochasticity of SUP by failures in jobs service in the queueing system with Markovian fluxes. The assessments of probability of SUP accounting the complex of parameters of pulsed ultrasound, biophysical properties of tissue and macromolecular crowding of insonated zone of tissue are considered.

SENSITIVITY ANALYSIS FOR THE OPTIMIZATION OF RADIOFREQUENCY ABLATION IN THE PRESENCE OF MATERIAL PARAMETER UNCERTAINTY

We present a sensitivity analysis of the optimization of the probe placement in radiofrequency (RF) ablation which takes the uncertainty associated with biophysical tissue properties (electrical and thermal conductivity) into account. Our forward simulation of RF ablation is based upon a system of partial differential equations (PDEs) that describe the electric potential of the probe and the steady state of the induced heat. The probe placement is optimized by minimizing a temperature-based objective function such that the volume of destroyed tumor tissue is maximized. The resulting optimality system is solved with a multilevel gradient descent approach. By evaluating the corresponding optimality system for certain realizations of tissue parameters (i.e., at certain, well-chosen points in the stochastic space) the sensitivity of the system can be analyzed with respect to variations in the tissue parameters. For the interpolation in the stochastic space we use an adaptive sparse grid collocation (ASGC) approach presented by Ma and Zabaras. We underscore the significance of the approach by applying the optimization to CT data obtained from a real RF ablation case.

The extracellular matrix of the dermis: flexible structures with dynamic functions

The current understanding of the role of extracellular matrix proteins is mainly based on their structural properties and their assembly into complex networks. The multiplicity of interactions between cells, cytokines and growth factors within the networks determines functional units dictating the biophysical properties of tissues. This review focuses on the understanding how alterations in the genes, modifying enzymes or biological functions of extracellular matrix molecules, lead to inborn or acquired skin disorders. Analysis of the disease mechanisms provides the basis for the emerging concept that not solely structural defects of single extracellular matrix proteins are at fault, but rather that the functional unit as a whole is not working properly, causing similar clinical symptoms although the causative genes are entirely different. The understanding of these disease-causing pathways has already led to surprising new therapeutic developments applied to rare inborn disorders. They now permit to design new concepts for the treatment of more common diseases associated with the accumulation of connective tissue and alterations of the biomechanical properties of the extracellular matrix.

Aspiration of Biological Viscoelastic Drops

Spherical cellular aggregates are in vitro systems to study the physical and biophysical properties of tissues. We present a novel approach to characterize the mechanical properties of cellular aggregates using a micropipette aspiration technique. We observe an aspiration in two distinct regimes: a fast elastic deformation followed by a viscous flow. We develop a model based on this viscoelastic behavior to deduce the surface tension, viscosity, and elastic modulus. A major result is the increase of the surface tension with the applied force, interpreted as an effect of cellular mechanosensing.

Relaxation Time Estimation from Complex Magnetic Resonance Images

Magnetic Resonance (MR) imaging techniques are used to measure biophysical properties of tissues. As clinical diagnoses are mainly based on the evaluation of contrast in MR images, relaxation times assume a fundamental role providing a major source of contrast. Moreover, they can give useful information in cancer diagnostic. In this paper we present a statistical technique to estimate relaxation times exploiting complex-valued MR images. Working in the complex domain instead of the amplitude one allows us to consider the data bivariate Gaussian distributed, and thus to implement a simple Least Square (LS) estimator on the available complex data. The proposed estimator results to be simple, accurate and unbiased.

Evaluation of breast cancer using magnetic resonance imaging with diffusion sequence.

Abstract Abstract #4026 The diffusion is a physical property that describes the microscopic random movement of molecules in response to termal energy. The diffusion may be affect by biophysical properties of tissues: cellular density, tumor structure (necrosis, edema), and microcirculation.
 We have made a quantitative analysis of the images of diffusion, calculating the coefficient of apparent diffusion (ADC) that reflects the capacity of specific diffusion of the tissue. The ADC is an objective parameter that can be used to characterize the tissues. It measures the displacement in unit of time (mm2/sec).
 In malignant tumors the barriers to the diffusion are increased (high hypercellularity) and therefore, the diffusion is restricted, which is translated as low values of ADC.
 We present 30 cases of infiltrating breast carcinoma, studied by sequence of diffusion SE EPI (TR 6500 msec; TE 85 msec; Matrix 128 x 80, NEX 6, Thickness 7 mm, GAP 3 mm, Value b 600 mm2/sec. AXIAL 38 courts 2 min 37 sec).
 In malignant tumors the ADC is minor of 1,1 x 10-3 and is lower than that of benign injuries and normal tissue fibroglandular.
 The apparent diffusion coefficient (ADC) are:
 • Cancer: 1,03 ± 0,23 x 103 mm2/sec.
 • Fibroadenoma: 1,74 ± 0,16 x 103 mm2/sec.
 • Cyst: 2,17 ± 0,25 x 103 mm2/sec.
 • Fibroglandular tissue: 1,83 ± 0,25 x 103 mm2/sec.
 Also we present 10 patients in whom we have used the ADC in the follow-up of the chemotherapy treatment. We have confirmed that the early increase of the ADC shows correlation with good response.
 We attach the example of a patient.
 Breast MR difussion: evaluation of chemotherapy response.
 
 Good evolution: rapid increse of ADC.
 In the scientific meeting we will present the results. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4026.

In vivo measurement of the apparent diffusion coefficient in normal and malignant prostatic tissue using thin-slice echo-planar imaging

Diffusion is a physical process based on the random movement of water molecules, known as Brownian movement. Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique that provides information on such biophysical properties of tissues as density, cell organisation and microstructure, which influence the diffusion of water molecules. The aim of this study was to evaluate the ability of MRI to obtain information on the diffusion of water molecules in normal and malignant prostate tissues. Ten volunteers and 19 patients with prostate lesions diagnosed by transrectal ultrasound (TRUS) were enrolled in our study. Morphological imaging was obtained with T2-weighted turbo spin-echo (TSE) sequences with and without fat suppression [spectral presaturation with inversion recovery (SPIR)] and an axial dynamic T1-weighted SPIR fast-field echo (FFE) sequence during intravenous administration of contrast material. DWI was obtained with a high-spatial-resolution single-shot spin-echo echo planar imaging (EPI) inversion recovery (IR) sequence. The apparent diffusion coefficient (ADC) maps were analysed by positioning an 8-pixel region of interest (ROI) over different zones of the prostate, and the focal lesion when present. The tumour was confirmed by a TRUS-guided needle biopsy taken within 1 month of the MRI examination. The mean ADC value of the central zones (1,512.07+/-124.85x10(-3) mm2/s) was significantly lower than the mean ADC of the peripheral zones (1,984.11+/-226.23x10(-3) mm2/s) (p<0.01). The mean ADC value of tumours (958.97+/-168.98x10(-3) mm2/s) was significantly lower than the mean values of normal peripheral zones (p<0.01). Our preliminary results indicate that DWI is useful for characterising tissue in the different regions of the prostate gland and in distinguishing normal from cancerous tissues, given its ability to detect early changes in the structural organisation of prostate tissue.

Diffusion MRI: precision, accuracy and flow effects.

After a decade of evolution and application of diffusion imaging, a large body of literature has been accumulated. It is in this context that the accuracy and precision of diffusion-weighted and quantitative diffusion MRI are reviewed. The emphasis of the review is on practical methods for clinical human imaging, particularly in the brain. The requirements for accuracy and precision are reviewed for various clinical and basic science applications. The methods of measuring and calculating diffusion effects with MRI are reviewed. The pulse gradient spin echo (PGSE) methods are emphasized as these methods are used most commonly in the clinical setting. Processing of PGSE data is reviewed. Various PGSE encoding schemes are also reviewed in terms of the accuracy and precision of isotropic and anisotropic diffusion measurements. The broad range of factors impacting the accuracy of the PGSE methods and other encoding schemes is then considered. Firstly, system inaccuracies such as background imaging gradients, gradient linearity, refocusing RF pulses, eddy currents, image misregistration, noise and dynamic range are considered. A second class of inaccuracies is contributed by the bulk effects of the imaged object, and include sample background gradients, subject motion of cerebrospinal fluid and organs, and aperiodic organ motion. A final category of potential inaccuracies is classified as being contributed by microscopic, biophysical tissue properties and include partial volume effects, anisotropy, restriction, diffusion distance, compartmentation, exchange, multiexponential diffusion decay, T2 weighting and microvascular perfusion. Finally, the application of diffusion methods to studies of blood flow in the microvasculature (i.e. the arterioles, capillaries and venules) are reviewed in detail, particularly in terms of feasibility and the stringent accuracy and precision requirements. Recent provocative studies examining the use of PGSE approaches to suppress microvascular signals in brain functional MRI (fMRI) are also reviewed.

Acid mucopolysaccharides and porcine muscle quality.

NUMEROUS postmortem biochemical and physiological changes which porcine muscle undegoes in its transformation to meat are associated, independently or jointly, with development of pale, soft, exudative (PSE) muscle (Briskey, 1963 ; Cassens, Briskey and Hoekstra, 1963). Sayre, Briskey and Hoekstra (1963) demonstrated that in severe cases, PSE muscles lose their connective tissue attachments to bone. Loss of intramuscular binding in hams from PSE pigs has also been reported by Briskey (1963). McClain et al. (1968) reported an altered or decreased ground substance content in the epimysium from PSE muscles. Acid mucopolysaccharides (AMPS) are the major components within the ground substance. The AMPS of ground substance play a significant part in a number of biophysical properties of tissue including ion exchange, water binding, membrane permeability and collagen structure stability (Brimacombe and Webber, 1964). Direct participation of AMPS in the preceding, suggested their possible involvement in some of the variations observed in porcine muscle quality. Major objectives of this study were: (1) to quantitate AMPS in normal and PSE muscle, and (2) to determine relation between specific AMPS and tenderness of porcine muscle.