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.

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.

Reliability of MRSI brain temperature mapping at 1.5 and 3 T.

MRSI permits the non-invasive mapping of brain temperature in vivo, but information regarding its reliability is lacking. We obtained MRSI data from 31 healthy male volunteers [age range, 22-40 years; mean ± standard deviation (SD), 30.5 ± 5.0 years]. Eleven subjects (age range, 23-40 years; mean ± SD, 30.5 ± 5.2 years) were invited to receive four point-resolved spectroscopy MRSI scans on each of 3 days in both 1.5-T (TR/TE = 1000/144 ms) and 3-T (TR/TE = 1700/144 ms) clinical scanners; a further 20 subjects (age range, 22-40 years; mean ± SD, 30.5 ± 4.9 years) were scanned on a single occasion at 3 T. Data were fitted in the time domain to determine the water-N-acetylaspartate chemical shift difference, from which the temperature was estimated. Temperature data were analysed using a linear mixed effects model to determine variance components and systematic temperature changes during the scanning sessions. To characterise the effects of instrumental drift on apparent MRSI brain temperature, a temperature-controlled phantom was constructed and scanned on multiple occasions. Components of apparent in vivo temperature variability at 1.5 T/3 T caused by inter-subject (0.18/0.17 °C), inter-session (0.18/0.15 °C) and within-session (0.36/0.14 °C) effects, as well as voxel-to-voxel variation (0.59/0.54 °C), were determined. There was a brain cooling effect during in vivo MRSI of 0.10 °C [95% confidence interval (CI): -0.110, -0.094 °C; p < 0.001] and 0.051 °C (95% CI: -0.054, -0.048 °C; p < 0.001) per scan at 1.5 T and 3 T, respectively, whereas phantom measurements revealed minimal drift in apparent MRSI temperature relative to fibre-optic temperature measurements. The mean brain temperature at 3 T was weakly associated with aural (R = 0.55, p = 0.002) and oral (R = 0.62, p < 0.001) measurements of head temperature. In conclusion, the variability associated with MRSI brain temperature mapping was quantified. Repeatability was somewhat higher at 3 T than at 1.5 T, although subtle spatial and temporal variations in apparent temperature were demonstrated at both field strengths. Such data should assist in the efficient design of future clinical studies.

An arterial wall motion test phantom for the evaluation of wall motion software.

Increasing cardiovascular disease has led to new ultrasound methods of assessing artery disease such as arterial wall motion measurement. To validate arterial wall motion software, we developed a mechanically-controlled wall motion test phantom with straight upper and lower agar tissue mimicking material layers that resemble an artery cross section. The wall separation, displacements and wall velocities and accelerations can be controlled within physiologically realistic levels. A user-definable displacement or one of several pre-defined displacement waveforms can be created by the user with custom-written software. The test phantom is then controlled using the defined waveform with a stepper motor controller. Accuracy assessment of the test phantom with a laser vibrometer yielded a positional accuracy of 36+/-2 microm. A typical application of the test phantom is demonstrated by assessing a tissue Doppler imaging (TDI) method for estimating the distension waveform. The TDI-based method was found to have a minimum resolvable displacement of 22.5 microm, and a measurement accuracy of +/-8% using a physiological wall motion movement with a peak displacement of 689 microm. The accuracy of the TDI method was found to decrease with decreasing wall displacement and increasing wall velocity.