Sevelamer Use and Mortality in People with Chronic Kidney Disease Stages 4 and 5 Not on Dialysis.

Rationale and objective: Data suggest that non-calcium-based binders, and specifically sevelamer, may lead to lower rates of death when compared with calcium-based binders in end-stage renal disease (ESRD) patients. However, the association between sevelamer use and mortality for those with non-dialysis-dependent chronic kidney disease (NDD-CKD) patients has been uncertain. Study design: Our research is presented in a prospective cohort study. Setting and participants: A total of 966 participants with NDD-CKD stages 4-5 were enrolled in the PECERA study from 12 centers in Spain. Exposure: The participants were treated with sevelamer. Outcome: This study yielded all-cause and cardiovascular mortality outcomes. Analytical approach: We conducted an association analysis between mortality and sevelamer use with time-dependent Cox proportional hazards models. Results: After a median follow-up of 29 months (IQR: 13-36 months), death occurred in 181 participants (19%), with cardiovascular (n = 95, 53%) being the leading cause of death. In a multivariable model, the adjusted hazard ratios (HRs) for patients under sevelamer treatment were 0.44 (95% CI, 0.22 to 0.88) and 0.37 (95% CI, 0.18 to 0.75) for all-cause and cardiovascular mortality, respectively, compared with those of untreated patients. Limitations: Some limitations include potential confusion via indication bias; causal statements about these associations cannot be made due to the observational nature of this study. Conclusions: In this prospective NDD-CKD cohort study, the administration of sevelamer was independently associated with lower all-cause and cardiovascular mortality, suggesting that non-calcium-based phosphate binders might be the first-line therapy for phosphate lowering in this population. Further interventional studies clarifying the risks and benefits of phosphate binders in NDD-CKD are warranted.

Mechanical mapping of the prostate in vivo using Dynamic Instrumented Palpation; towards an in vivo strategy for cancer assessment.

A calibrated palpation sensor has been developed for making instrumented Digital Rectal Examinations (iDREs) with a view to assessing patients for prostate cancer. The instrument measures the dynamic stiffness of the palpable surface of the prostate, and has been trialled on 12 patients in vivo. The patients had been diagnosed with prostate cancer and were scheduled for radical prostatectomy. As far as possible, patients with asymmetric disease were chosen so as to give a variation in gland condition over the palpable surface. The device works by applying an oscillating pressure (force) to a flexible probe whose displacement into the tissue is also measured in order to yield a dynamic stiffness, the static stiffness being incidentally measured at the mean oscillatory force. The device was deployed mounted on the index finger of a urologist and measurements taken at 12-16 positions on each patient using light and firm pressure and palpation frequencies of 1 or 5 Hz. In parallel, conventional DRE assessments were made by a consultant urologist for cancer. After in vivo measurement, the glands were removed and examined histologically with each palpation point being classified as cancerous (C) or not (NC). The work has established the first measurements of static modulus of living prostate tissue to be: 26.8 (13.3) kPa for tissue affected by prostate cancer (C classification), and 24.8 kPa (11.9) for tissue unaffected by cancer (NC classification), values quoted as median (interquartile range). The dynamic properties were characterised by: dynamic modulus, 5.15 kPa (4.86) for the C classification and 4.61 kPa (3.08) for the NC classification and the time lag between force and displacement at 5 Hz palpation frequency, 0.0175 s (0.0078) for the C classification and 0.0186 s (0.0397) for the NC classification, values again quoted as median (interquartile range). With the limited set of features that could be generated, an Artificial Neural Network (ANN) classification yielded a sensitivity of 97%, negative predictive value of 86%, positive predictive value of 67% and accuracy of 70% but with relatively poor specificity (30%). Besides extending the feature set, there are a number of changes in probe design, probing strategy and in mechanics analysis, which are expected to improve the diagnostic capabilities of the method.

Locating and sizing tumor nodules in human prostate using instrumented probing - computational framework and experimental validation.

Detection of tumor nodules is key to early cancer diagnosis. This study investigates the potential of using the mechanical data, acquired from probing the prostate for detecting the existence, and, more importantly, characterizing the size and depth, from the posterior surface, of the prostate cancer (PCa) nodules. A computational approach is developed to quantify the uncertainty of nodule detectability and is based on identifying stiffness anomalies in the profiles of point force measurements across transverse sections of the prostate. The capability of the proposed method was assessed firstly using a 'training' dataset of in silico models including PCa nodules with random size, depth and location, followed by a clinical feasibility study, involving experimental data from 13 ex vivo prostates from patients who had undergone radical prostatatectomy. Promising levels of sensitivity and specificity were obtained for detecting the PCa nodules in a total of 44 prostate sections. This study has shown that the proposed methods could be a useful complementary tool to exisiting diagnostic methods of PCa. The future study will involve implementing the proposed measurement and detection strategies in vivo, with the help of a miniturized medical device.

Disorders in bone-mineral parameters and the risk of death in persons with chronic kidney disease stages 4 and 5: the PECERA study.

BACKGROUND: Abnormalities of bone mineral parameters are associated with increased mortality in patients on dialysis, but their effects and the optimal range of these biomarkers are less well characterized in non-dialysis chronic kidney disease (CKD). METHODS: PECERA (Collaborative Study Project in Patients with Advanced CKD) is a 3-year, prospective multicenter, open-cohort study of 966 adult patients with non-dialyzed CKD stages 4-5 enrolled from 12 centers in Spain. Associations between levels of serum calcium (Ca) (corrected for albumin), phosphate (P), and intact parathyroid hormone (iPTH) with all-cause mortality (primary outcome) and cardiovascular mortality (secondary outcome) were examined using time-dependent Cox proportional hazards models and penalized splines analysis adjusted by demographics and comorbidities, treatments and biochemical values collected every 6 months for 3 years. RESULTS: After a median follow-up of 29 months (IQR: 13-36 months) there were 181 deaths (19%). The association of calcium with all-cause mortality was J-shaped, with an increased risk for all-cause mortality at levels > 10.5 mg/dL. For phosphate and iPTH levels, the association was U-shaped. The serum values associated with the minimum risk of mortality were 3.8 mg/dL for phosphate and 70 pg/mL for iPTH, being the lowest risk ranges between 2.8 and 5.0 mg/dL, and between 38 and 112 pg/mL for phosphate and iPTH, respectively. CONCLUSIONS: Our study provides evidence on the non-linear association of serum calcium, phosphate and iPTH levels with mortality in stage 4 and 5 CKD patients, and suggests potential survival benefits for controlling bone mineral parameters in this population, as previously reported for dialysis patients.

Identification of tumor nodule in soft tissue: An inverse finite-element framework based on mechanical characterization.

Identification and characterization of nodules in soft tissue, including their size, shape, and location, provide a basis for tumor identification. This study proposes an inverse finite-element (FE) based computational framework, for characterizing the size of examined tissue sample and detecting the presence of embedded tumor nodules using instrumented palpation, without a priori anatomical knowledge. The inverse analysis was applied to a model system, the human prostate, and was based on the reaction forces which can be obtained by trans-rectal mechanical probing and those from an equivalent FE model, which was optimized iteratively, by minimizing an error function between the two cases, toward the target solution. The tumor nodule can be identified through its influence on the stress state of the prostate. The effectiveness of the proposed method was further verified using a realistic prostate model reconstructed from magnetic resonance (MR) images. The results show the proposed framework to be capable of characterizing the key geometrical indices of the prostate and identifying the presence of cancerous nodules. Therefore, it has potential, when combined with instrumented palpation, for primary diagnosis of prostate cancer, and, potentially, solid tumors in other types of soft tissue.

A novel palpation-based method for tumor nodule quantification in soft tissue-computational framework and experimental validation.

Variation in mechanical properties is a useful marker for cancer in soft tissue and has been used in clinical diagnosis for centuries. However, to develop such methods as instrumented palpation, there remain challenges in using the mechanical response during palpation to quantify tumor load. This study proposes a computational framework of identification and quantification of cancerous nodules in soft tissue without a priori knowledge of its geometry, size, and depth. The methodology, using prostate tissue as an exemplar, is based on instrumented palpation performed at positions with various indentation depths over the surface of the relevant structure (in this case, the prostate gland). The profile of force feedback results is then compared with the benchmark in silico models to estimate the size and depth of the cancerous nodule. The methodology is first demonstrated using computational models and then validated using tissue-mimicking gelatin phantoms, where the depth and volume of the tumor nodule is estimated with good accuracy. The proposed framework is capable of quantifying a tumor nodule in soft tissue without a priori information about its geometry, thus presenting great promise in clinical palpation diagnosis for a wide variety of solid tumors including breast and prostate cancer. Graphical abstract This study proposes a computational framework of quantification of cancerous nodules in soft tissue. The methodology is based on instrumental palpation performed at positions with various indentation depths. The profile of force feedback results is then compared with the benchmark in silico models to estimate the size and depth of the cancerous nodule.

A novel method for rapid and quantitative mechanical assessment of soft tissue for diagnostic purposes: A computational study.

Biological tissues often experience drastic changes in their microstructure due to their pathophysiological conditions. Such microstructural changes could result in variations in mechanical properties, which can be used in diagnosing or monitoring a wide range of diseases, most notably cancer. This paves the avenue for non-invasive diagnosis by instrumented palpation although challenges remain in quantitatively assessing the amount of diseased tissue by means of mechanical characterization. This paper presents a framework for tissue diagnosis using a quantitative and efficient estimation of the fractions of cancerous and non-cancerous tissue without a priori knowledge of tissue microstructure. First, the sample is tested in a creep or stress relaxation experiment, and the behavior is characterized using a single term Prony series. A rule of mixtures, which relates tumor fraction to the apparent mechanical properties, is then obtained by minimizing the difference between strain energy of a heterogeneous system and an equivalent homogeneous one. Finally, the percentage of each tissue constituent is predicted by comparing the observed relaxation time with that calculated from the rule of mixtures. The proposed methodology is assessed using models reconstructed from histological samples and magnetic resonance imaging of prostate. Results show that estimation of cancerous tissue fraction can be obtained with a maximum error of 12% when samples of different sizes, geometries, and tumor fractions are presented. The proposed framework has the potential to be applied to a wide range of diseases such as rectal polyps, cirrhosis, or breast and prostate cancer whose current primary diagnosis remains qualitative.

Quantitative mechanical assessment of the whole prostate gland ex vivo using dynamic instrumented palpation.

An instrumented palpation sensor, designed for measuring the dynamic modulus of tissue in vivo, has been developed and trialled on ex vivo whole prostate glands. The sensor consists of a flexible membrane sensor/actuator with an embedded strain gauge and is actuated using a dynamically varying airflow at frequencies of 1 and 5 Hz. The device was calibrated using an indentation stiffness measurement rig and gelatine samples with a range of static modulus similar to that reported in the literature for prostate tissue. The glands were removed from patients with diagnosed prostate cancer scheduled for radical prostatectomy, and the stiffness was measured within 30 min of surgical removal. Each prostate was later examined histologically in a column immediately below each indentation point and graded into one of the four groups; normal, benign prostatic hyperplasia, cancerous and mixed cancer and benign prostatic hyperplasia. In total, 11 prostates were assessed using multiple point probing, and the complex modulus at 1 and 5 Hz was calculated on a point-by-point basis. The device yielded values of quasi-static modulus of 15 ± 0.5 kPa and dynamic modulus of 20 ± 0.5 kPa for whole prostates, and a sensitivity of up to 80% with slightly lower specificity was achieved on diagnosis of prostate cancer using a combination of mechanical measures. This assessment did not take into account some obvious factors such as edge effects, overlap and clinical significance of the cancer, all of which would improve performance. The device, as currently configured, is immediately deployable in vivo. A number of improvements are also identified which could improve the sensitivity and specificity in future embodiments of the probe.

Histology-based homogenization analysis of soft tissue: application to prostate cancer.

It is well known that the changes in tissue microstructure associated with certain pathophysiological conditions can influence its mechanical properties. Quantitatively relating the tissue microstructure to the macroscopic mechanical properties could lead to significant improvements in clinical diagnosis, especially when the mechanical properties of the tissue are used as diagnostic indices such as in digital rectal examination and elastography. In this study, a novel method of imposing periodic boundary conditions in non-periodic finite-element meshes is presented. This method is used to develop quantitative relationships between tissue microstructure and its apparent mechanical properties for benign and malignant tissue at various length scales. Finally, the inter-patient variation in the tissue properties is also investigated. Results show significant changes in the statistical distribution of the mechanical properties at different length scales. More importantly the loss of the normal differentiation of glandular structure of cancerous tissue has been demonstrated to lead to changes in mechanical properties and anisotropy. The proposed methodology is not limited to a particular tissue or material and the example used could help better understand how changes in the tissue microstructure caused by pathological conditions influence the mechanical properties, ultimately leading to more sensitive and accurate diagnostic technologies.

Patient specific modeling of palpation-based prostate cancer diagnosis: effects of pelvic cavity anatomy and intrabladder pressure.

Computational modeling has become a successful tool for scientific advances including understanding the behavior of biological and biomedical systems as well as improving clinical practice. In most cases, only general models are used without taking into account patient-specific features. However, patient specificity has proven to be crucial in guiding clinical practice because of disastrous consequences that can arise should the model be inaccurate. This paper proposes a framework for the computational modeling applied to the example of the male pelvic cavity for the purpose of prostate cancer diagnostics using palpation. The effects of patient specific structural features on palpation response are studied in three selected patients with very different pathophysiological conditions whose pelvic cavities are reconstructed from MRI scans. In particular, the role of intrabladder pressure in the outcome of digital rectal examination is investigated with the objective of providing guidelines to practitioners to enhance the effectiveness of diagnosis. Furthermore, the presence of the pelvic bone in the model is assessed to determine the pathophysiological conditions in which it has to be modeled. The conclusions and suggestions of this work have potential use not only in clinical practice and also for biomechanical modeling where structural patient-specificity needs to be considered. © 2015 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.

Quantitative diagnostics of soft tissue through viscoelastic characterization using time-based instrumented palpation.

Although palpation has been successfully employed for centuries to assess soft tissue quality, it is a subjective test, and is therefore qualitative and depends on the experience of the practitioner. To reproduce what the medical practitioner feels needs more than a simple quasi-static stiffness measurement. This paper assesses the capacity of dynamic mechanical palpation to measure the changes in viscoelastic properties that soft tissue can exhibit under certain pathological conditions. A diagnostic framework is proposed to measure elastic and viscous behaviors simultaneously using a reduced set of viscoelastic parameters, giving a reliable index for quantitative assessment of tissue quality. The approach is illustrated on prostate models reconstructed from prostate MRI scans. The examples show that the change in viscoelastic time constant between healthy and cancerous tissue is a key index for quantitative diagnostics using point probing. The method is not limited to any particular tissue or material and is therefore useful for tissue where defining a unique time constant is not trivial. The proposed framework of quantitative assessment could become a useful tool in clinical diagnostics for soft tissue.