M. Garcia-Schürmann

A new system for the acquisition of ultrasonic multicompression strain images of the human prostate in vivo

We describe a novel recording system for the acquisition of multicompression strain images of the human prostate in vivo. The force at the tip of an ultrasonic transrectal probe is measured continuously, and ultrasonic RF-images are acquired consecutively at specified levels of compression. The acquired image sequence is processed by conventional cross-correlation techniques to obtain time shift estimates and corresponding strain images. We present phantom measurements as well as in vivo results and discuss the advantages and restrictions of the proposed system.

Ultrasonic multifeature tissue characterization for the early detection of prostate cancer

The incidence of the prostate carcinoma is one of the highest cancer risks in men in the western world. Its position in cancer mortality statistics is also among the highest. The prostate carcinoma is only curable at an early stage. Therefore, early detection is extremely important. At an early stage the prostate carcinoma is limited to the prostate capsule and can hence be cured performing radical prostatectomy. The different types of diagnostics that are used today (digital rectal examination, transrectal ultrasound and PSA value analysis) lack reliability and are therefore not sufficient. Even a combination of these three methods is not sufficiently reliable. Diagnosis of the prostate carcinoma using multi-feature tissue characterization in combination with ultrasound allows the detection of tumors at an early stage. Also biopsy guidance and planning can be improved. This results in reduced costs for cancer treatment.

Ultrasonic Tissue Characterization for Prostate Diagnostics: Spectral Parameters vs. Texture Parameters. Sonohistologie für die Prostatadiagnostik: Vergleich von Spektral- und Texturparametern

An ultrasonic multi-feature tissue characterizing system for the detection of prostate cancer is presented. The system is based on the processing of radio frequency (RF) ultrasonic echo data. Data from 100 patients was acquired in a clinical study. Parameters are extracted from the RF echo data and classified using two adaptive network-based fuzzy inference systems (FIS) working in parallel as a nonlinear classifier. Next to spectral parameters, conventional texture parameters are calculated using demodulated and log-compressed echo data. In the first approach, the classifier is trained on both, spectral and texture parameters. In the second approach, the classifier is only trained on texture parameters. Classification results of both approaches are compared and it is demonstrated, that only the use of spectral parameters yields satisfying classification results. Results of a minimum distance classifier (MDC) are presented for comparison with the fuzzy inference system. For the final fuzzy inference systems used in this approach, the area under the ROC curve is between 84% and 86% for the combined approach and between 70% and 74% for the approach based on texture parameters only.

Diagnosis of prostate carcinoma using multicompression strain imaging: data acquisition and first in vivo results

We present a new system for the acquisition of ultrasonic multicompression strain images of the human prostate in vivo. A mechanical force applied to the tip of an ultrasonic transrectal probe is measured continuously and ultrasonic RF-images are acquired consecutively at specified levels of tissue compression. An iterative phase-zero estimation method is used to obtain time delay estimates and the corresponding strain images from the acquired image sequence. We present phantom measurements as well as first in vivo results which are in good agreement to histological findings. Lateral tissue motion artifacts are corrected by a novel local companding method.

Neuro-fuzzy inference system for ultrasonic multifeature tissue characterization for prostate diagnostics

The incidence of the prostate carcinoma is one of the highest cancer risks in men in the western world. Its position in cancer mortality statistics is also among the highest. The different types of diagnostics that are used today lack reliability and are therefore not sufficient. Diagnosis of the prostate carcinoma using multifeature tissue characterization in combination with ultrasound allows the detection of tumors at an early stage and thus can aid the conducting physician in finding a diagnosis. Spatially resolved parameters and contextual information are used for the classification. Next to hypo- and hyperechoic tumors, also isoechoic tumors can be visualized.

Real Time Strain Imaging — a new Ultrasonic Method for Cancer Detection: First Study Results

Prostate tumors can have a higher mechanical hardness than the surrounding tissue. During the digital rectal exam this can be used not only to detect the hypertrophy but also localized hardenings. The examination by digital palpation is inaccurate and even in combination with PSAvalue and a transrectal ultrasonic examination the result is often not reliable. Ultrasound strain imaging is able to measure and visualize the elastic properties of a tissue region and hence is an adequate supplement for commonly used diagnostic procedures. We have developed a real time system for elastographic mechanical tissue assessment of the prostate which can be used for the transrectal ultrasonic examination for navigation and diagnosis. During the examination a sequence of ultrasonic images is acquired while the organ is slightly compressed by the ultrasound probe. Using a numerical analysis of image pairs of the acquired sequence the tissue strain is calculated which represents the spatial elasticity distribution of a specific cross-section of the organ and which are able to distinguish hard areas in the tissue. We present results from several patients. which show, that real time strain imaging is able to detect tumor-like areas which are inconspicuous in the bmode image. The results correspond to the histological specimens. After the evaluation of 130 patients using a prospective study we found the specificity for cancer detection to be approximately 84% and a sensitivity of approximately 76 %. Furthermore the tumor location and extend was correctly predicted in most of the investigated patients using our real time strain imaging. SIGNAL PROCESSING Strain imaging was first described by Ophir in 1991 [1], but could not easily be clinically applied so far, because the described method had no real time capability. To use it in a clinical setting we invented a time efficient algorithm, called “phase root seeking” [2], which in a current system is able to calculate up to 30 strain images per second using a conventional desktop PC. Similar to [1], time shifts are estimated using a discrete number of windows at discrete depths. The time shift τm,k of the k-th window of two A-lines centered around tk = k∆T is estimated by the following iterative formula L k m k m , 1 , 0 , , − τ = τ (1)

Ultrasonic tissue characterization-assessment of prostate tissue malignancy in vivo using a conventional classifier based tissue classification approach and elastographic imaging

We present the development of a combined system which is able to exploit the benefits of two methods used for tissue characterization, strain imaging and tissue classification using a trainable classification system. Our system is able to acquire in vivo multi-compression rf-data for the calculation of the tissue strain, i.e. the elastic properties of tissue, induced by tissue compression. At the same time a neuro-fuzzy classification system is used to map the tissue malignancy. In vivo classification results and in vivo strain images are presented. The images of the two new modalities are compared to demonstrate the advantages and restrictions of both methods.

ULTRASCHALL-GEWEBECHARAKTERISIERUNG FÜR DIE PROSTATADIAGNOSTIK

EINLEITUNG Das Prostatakarzinom ist der zweithäufigste bösartige Tumor beim Mann. In der Mortalitätsstatistik nimmt das Prostatakarzinom nach Erkrankungen an Lungenund Magen-Darm-Krebs die dritte Position ein. Nur in einem frühen Stadium ist das Prostatakarzinom heilbar, daher ist eine gezielte Früherkennung äußerst wichtig. Die bisherigen Diagnoseverfahren, digitaler Tastbcfund, transrektaler Ultraschall und PSA-WertAnalyse, sind unsicher und daher nicht ausreichend. Die Diagnose des Prostatakarzinoms unter Anwendung der Gewebecharakterisierung mittels Ultraschall bietet die Möglichkeit, Tumoren frühzeitig zu diagnostizieren und damit in einem heilbaren Stadium zu behandeln.

Frame-to-frame statistics of real-time strain images

Assesses the second order statistical properties of strain images with respect to the temporal direction. Successively acquired strain images in a real-time or similar off-line strain imaging system are correlated. This can be described by a covariance function, which is investigated in this paper by simulations. We determine how the statistical properties affect the choice of the frame-rate in a real-time strain imaging system and furthermore the effect of temporal filtering of strain images is discussed. The first in vivo real-time strain images of the prostate have been presented.