Ultrasound-Guided Characterization of Interstitial Ablated Tissue Using RF Time Series: Feasibility Study

Imani, Farhad; Abolmaesumi, Purang; Lassó, András; Burdette, Everette C.; Ghoshal, Goutam; Heffter, Tamas; Williams, Emery; Neubauer, Paul; Fichtinger, Gabor; Mousavi, Parvin

doi:10.1109/tbme.2013.2240300

Cited by 14 publications

(16 citation statements)

References 41 publications

(72 reference statements)

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“…SVM has been demonstrated previously to differentiate various tissue types using temporal ultrasound data in in vivo and ex vivo studies, consistently and with high accuracies [7,8]. To build an SVM model, data is mapped to a higher dimension using a kernel function enabling separation of its two classes with maximum margin 2 .…”

Section: Methodsmentioning

confidence: 99%

“…To build an SVM model, data is mapped to a higher dimension using a kernel function enabling separation of its two classes with maximum margin 2 . We used an RBF kernel function which only needs one parameter for initialization [7,8]. Tuning the SVM kernel and parameters provided us the flexibility to: i) choose from various linear and nonlinear transformation of input data and different decision boundaries, and ii) prevent overfitting of the classifier during training.…”

Section: Methodsmentioning

confidence: 99%

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Augmenting MRI–transrectal ultrasound-guided prostate biopsy with temporal ultrasound data: a clinical feasibility study

et al. 2015

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Purpose In recent years, fusion of multi-parametric MRI (mp-MRI) with transrectal ultrasound (TRUS) guided biopsy has enabled targeted prostate biopsy with improved cancer yield. Target identification is solely based on information from mp-MRI, which is subsequently transferred to the subject coordinates through an image registration approach. mp-MRI has shown to be highly sensitive to detect higher grade prostate cancer, but suffers from a high rate of false positives for lower grade cancer, leading to unnecessary biopsies. This paper utilizes a machine-learning framework to further improve the sensitivity of targeted biopsy through analyzing temporal ultrasound data backscattered from the prostate tissue. Methods Temporal ultrasound data was acquired during targeted fusion prostate biopsy from suspicious cancer foci identified in mp-MRI. Several spectral features, representing the signature of backscattered signal from the tissue, were extracted from the temporal ultrasound data. A supervised support vector machine classification model was trained to relate the features to the result of histopathology analysis of biopsy cores obtained from cancer foci. The model was used to predict the label of biopsy cores for mp-MRI identified targets in an independent group of subjects. Results Training of the classier was performed on data obtained from 35 biopsy cores. A five-fold cross-validation strategy was utilized to examine the consistency of the selected features from temporal ultrasound data, where we achieved the classification accuracy and area under receiver operating characteristic curve of 94% and 0.98, respectively. Subsequently, an independent group of 25 biopsy cores was used for validation of the model, in which mp-MRI had identified suspicious cancer foci. Using the trained model, we predicted the tissue pathology using temporal ultrasound data: 16 out of 17 benign cores, as well as all three higher grade cancer cores, were correctly identified. Conclusion The results show that temporal analysis of ultrasound data is potentially an effective approach to complement mp-MRI-TRUS-guided prostate cancer biopsy, specially to reduce the number of unnecessary biopsies and to reliably identify higher grade cancers.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Augmenting MRI–transrectal ultrasound-guided prostate biopsy with temporal ultrasound data: a clinical feasibility study

et al. 2015

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“…In similar studies conducted by other research groups, extraction of RF time series features had been demonstrated in 12 ex vivo chicken breast and 2 in situ bovine liver tissue samples based on PRE- and POST-HIFU exposure treatments. [ 1 12 ] In this study, 6 ex vivo porcine tissue samples were analyzed in three PRE-HIFU, DUR-HIFU, and POST-HIFU exposure stages. The approach presented in this work is different from the previously published ones[ 1 ] because, here, the main focus is on the estimation of the changes occurring DUR-HIFU exposure.…”

Section: Discussionmentioning

confidence: 99%

“…5, were extracted for the RF time series signal based on the procedures defined by Imani et al . [ 12 ]…”

Section: Methodsmentioning

confidence: 99%

Radio frequency ultrasound time series signal analysis to evaluate high-intensity focused ultrasound lesion formation status in tissue

et al. 2016

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High-intensity focused ultrasound (HIFU) is a novel treatment modality used by scientists and clinicians in the recent decades. This modality has had a great and significant success as a noninvasive surgery technique applicable in tissue ablation therapy and cancer treatment. In this study, radio frequency (RF) ultrasound signals were acquired and registered in three stages of before, during, and after HIFU exposures. Different features of RF time series signals including the sum of amplitude spectrum in the four quarters of the frequency range, the slope, and intercept of the best-fit line to the entire power spectrum and the Shannon entropy were utilized to distinguish between the HIFU-induced thermal lesion and the normal tissue. We also examined the RF data, frame by frame to identify exposure effects on the formation and characteristics of a HIFU thermal lesion at different time steps throughout the treatment. The results obtained showed that the spectrum frequency quarters and the slope and intercept of the best fit line to the entire power spectrum both increased two times during the HIFU exposures. The Shannon entropy, however, decreased after the exposures. In conclusion, different characteristics of RF time series signal possess promising features that can be used to characterize ablated and nonablated tissues and to distinguish them from each other in a quasi-quantitative fashion.

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“…Tissue coagulation can be monitored by identifying changes in echogenicity [57, 59], Doppler signals [57], backscatter [18], stiffness [16, 19, 106, 107] and echo-decorrelation[14, 15]. US imaging has also been successfully implemented to guide and position interstitial CBUS devices.…”

Section: Image Guidancementioning

confidence: 99%

Catheter-based ultrasound technology for image-guided thermal therapy: Current technology and applications

Salgaonkar

Diederich

2015

International Journal of Hyperthermia

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Catheter-based ultrasound (CBUS) is being applied to deliver minimally invasive thermal therapy to solid cancer tumors, benign tissue growth, vascular disease, and tissue remodeling. Compared to other energy modalities used in catheter-based surgical interventions, unique features of ultrasound result in conformable and precise energy delivery with high selectivity, fast treatment times, and larger treatment volumes. Here, a concise review of CBUS technology being currently utilized in animal and clinical studies or being developed for future applications is presented. CBUS devices have been categorized into interstitial, endoluminal and endovascular/cardiac applications. Basic applicator designs, site specific evaluations and possible treatment applications have been discussed in brief. Particular emphasis has been given on ablation studies that incorporate image-guidance for applicator placement, therapy monitoring, feedback control, and post-procedure assessment. Examples of devices included here span the entire spectrum of development cycle from preliminary simulation based design studies to implementation in clinical investigations. The use of CBUS under image guidance has the potential for significantly improving precision and applicability of thermal therapy delivery.

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Ultrasound-Guided Characterization of Interstitial Ablated Tissue Using RF Time Series: Feasibility Study

Cited by 14 publications

References 41 publications

Augmenting MRI–transrectal ultrasound-guided prostate biopsy with temporal ultrasound data: a clinical feasibility study

Augmenting MRI–transrectal ultrasound-guided prostate biopsy with temporal ultrasound data: a clinical feasibility study

Radio frequency ultrasound time series signal analysis to evaluate high-intensity focused ultrasound lesion formation status in tissue

Catheter-based ultrasound technology for image-guided thermal therapy: Current technology and applications

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