Transrectal Subharmonic Ultrasound Imaging for Prostate Cancer Detection

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Transrectal Subharmonic Ultrasound Imaging for Prostate Cancer Detection I. Gupta , B. Freid , V. Masarapu , P. Machado , E. Trabulsi , K. Wallace , E. Halpern , F. Forsberg PII: DOI: Reference:

S0090-4295(19)31132-X https://doi.org/10.1016/j.urology.2019.12.025 URL 21918

To appear in:

Urology

Received date: Revised date: Accepted date:

12 August 2019 21 December 2019 23 December 2019

Please cite this article as: I. Gupta , B. Freid , V. Masarapu , P. Machado , E. Trabulsi , K. Wallace , E. Halpern , F. Forsberg , Transrectal Subharmonic Ultrasound Imaging for Prostate Cancer Detection, Urology (2019), doi: https://doi.org/10.1016/j.urology.2019.12.025

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Transrectal Subharmonic Ultrasound Imaging for Prostate Cancer Detection I. Gupta 1, B. Freid 1, V. Masarapu 1, P. Machado 1, E. Trabulsi 1, K. Wallace 2, E. Halpern 1, F. Forsberg 1 1

. Thomas Jefferson University, Philadelphia, PA 19107, USA

2

. GE Global Research, Niskayuna NY 12309, USA

Corresponding Author: Flemming Forsberg, PhD, FAIUM, FAIMBE Professor, Department of Radiology, 763H Main Building, Thomas Jefferson University, 132 South 10th Street, Philadelphia, PA 19107 USA. Tel: +1-215-955-4870 E-mail: [email protected]

Keywords: Contrast agent, prostate cancer diagnosis, targeted biopsy, contrast enhanced ultrasonography This study was funded by NIH R21 CA202214. ClinicalTrials.gov Identifier: NCT02967458. Declarations of interest: F. Forsberg: Ultrasound scanner and/or contrast agent support from GE, Siemens, Cannon, Lantheus Medical Imaging and Bracco. No funding received. E. Trabulsi: Consultant to Astellas, Pfizer and Janssen (none of which are pertinent to the current study). 1

K. Wallace is an employee of GE. No other author has anything to report.

Abstract Objective: To assess the PCa detection rates of contrast-enhanced, transrectal subharmonic ultrasound imaging (SHI). Materials and Methods: This IRB-approved study enrolled 55 subjects. The initial 5 subjects were studied for SHI optimization, while the remaining 50 were evaluated with contrastenhanced sonography using continuous SHI, color and power Doppler as well as conventional grayscale, continuous color and power Doppler and SHI combined with maximum flash replenishment. A maximum of 6 directed biopsy cores were obtained from sites of greatest asymmetrical enhancement, followed by spatially distributed cores in a double sextant distribution. Subharmonic time-intensity parameters, including time to peak intensity, peak intensity and estimated perfusion were also evaluated for each directed biopsy core. Receiver operating characteristic (ROC) curve analysis and conditional logistic regression were employed to assess the benefit of each modality and the quantitative SHI parameters. Results: Cancer was detected in 22 of 50 subjects. Among subjects with clinically significant PCa (n=11), targeted cores were more likely to be positive (odds ratio 1.39, p=0.02). The majority of patients detected by SHI demonstrated significant PCa (5/8); SHI remained an independent marker of malignancy in a multivariate logistic regression model (p=0.027). ROC analysis of imaging findings compared to biopsy results yielded diagnostic accuracies ranging

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from 0.59 to 0.80 for all imaging modalities with the highest being for quantitative subharmonic perfusion estimates. Conclusions: This first-in-humans study provides a preliminary estimate of the diagnostic accuracy of SHI for detection of clinically significant PCa (up to 80%).

Introduction Prostate cancer (PCa) is the most prevalent cancer among American men and the sixth leading cause of cancer death (7.4% of deaths) among men worldwide.1 The American Cancer Society estimates about 174,650 new cases of PCa will be diagnosed each year in USA alone, leading to about 31,620 deaths per annum.2 The primary diagnostic tools for detecting PCa include biochemical screening with serum prostate specific antigen (PSA) and transrectal ultrasound (TRUS) guided biopsies. However, PSA screening results in the detection of many clinically insignificant cancers, which do not progress even without aggressive therapy.3 Also, a significant minority of clinically significant cases go undetected in patients with low PSA values. Clinically insignificant PCa can be managed by active surveillance (AS) and does not require treatment. In contrast, patients with a Gleason score ≥7, or those with ≥50% biopsy core involvement, are more likely to progress if left untreated; these “clinically significant” cancers should be considered for aggressive therapy.4-6 A major barrier to the widespread adoption of AS is the lack of an accurate noninvasive diagnostic test to prospectively identify patients with clinically significant PCa, whose disease will progress without definitive therapy. Contrast-Enhanced Imaging of Prostate Cancer

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Our group has focused on prostate imaging with microbubble-based ultrasound contrast agents (UCAs), as ultrasound is the least expensive and most commonly used modality for guidance of prostate biopsy. These UCAs have diameters less than 8 µm, having a lipid, protein or a polymer shell and can traverse the entire vasculature including the capillaries.7,8 The gas within these microbubbles has high compressibility and thus, the microbubbles enhance the backscattered ultrasound signal (about 10–30 dB enhancement). 9 At higher incident pressures (>200 kPa), these UCAs exhibit nonlinear behaviour.10 This behavior is used in diagnostic imaging as the UCA’s nonlinear oscillations occur over a wide range of frequencies from subharmonics (fo/2) to second harmonics (2fo) and ultraharmonics (3fo/2) of the insonation frequency (fo) as well as its multiples. These signals can be used to create specific contrast imaging modes, such as subharmonic imaging (SHI), harmonic imaging (HI) and superharmonic imaging, respectively. Clinical studies using HI have demonstrated that enhancement of the prostate with contrast enhanced transrectal ultrasound (CE-TRUS) correlates with increased microvessel density,11,12 and improved detection of PCa;13,14 with fewer biopsy cores.15,16 Additionally, color and power Doppler imaging techniques have been employed for contrast enhanced imaging of the prostate. However, Doppler techniques utilize relatively high energy levels that destroy a large proportion of the microbubbles. Another technique called maximum intensity projection (MIP) combines flash replenishment and the maximum contrast enhanced intensity of each pixel in the ultrasound image over several image frames to trace individual microbubbles in the microvasculature with time. MIP improves the sensitivity of contrast enhanced HI and reveals the vascular pattern of individual microvessels.17 Although CE-TRUS with HI selectively detects clinically significant PCa, overall by-patient detection of high grade PCa with targeted biopsy based upon HI alone remains inferior to a 12 4

core systematic biopsy. This limitation is related, in part, to difficulty discerning enhancing foci of PCa adjacent to the hypervascular transition zone. A major limitation of HI is the reduced contrast-to-tissue ratio resulting from second harmonic generation and accumulation in tissue.14 Hence, SHI is an attractive alternative imaging mode, because of the weaker subharmonic generation in tissue relative to the significant subharmonic scattering produced by UCAs.10 SHI transmits at double the resonance frequency and receives at half the transmit frequency i.e., fo/2.18 SHI has better lateral resolution as compared with HI, and causes less cavitational bioeffects, due to its higher transmitting frequency. This study focused on optimizing the detection of clinically significant PCa using SHI with CETRUS for targeted biopsies of the prostate.

Methods and Materials Institutional review board and FDA approval was obtained for this Health Insurance Portability and Accountability Act of 1996 compliant trial (IND 112,241). Fifty-five men were prospectively enrolled and provided written informed consent between February 2017 and February 2018. Inclusion criteria were age older than 18 years, a scheduled prostate biopsy based on an elevated PSA or abnormal digital rectal examination, as well as those with known PCa who were scheduled for a repeat biopsy on AS. Exclusion criteria were prostate biopsy within 30 days, participation in a clinical trial involving an investigational agent within 30 days, known or suspected hypersensitivity to perflutren, prior treatment for prostate cancer or severe concurrent illness.

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The initial 5 subjects were used for SHI optimization, and the remaining 50 for prospective evaluation of PCa detection with SHI. The initial optimization involved 9 different input pulses with varying shapes as previous studies have shown that the initial slope of pulses can alter the subharmonic response from microbubbles.19,20 All pulses were evaluated for background suppression, visualization of blood flow, and presence of artifacts by two experienced observers and the one with best image quality was selected. An endocavitary IC5-9D transducer on a modified Logiq E9 system (GE Healthcare; Waukesha, WI) was used. The UCA was Definity® (Perflutren Lipid Microsphere, Lantheus Medical Imaging; N. Billerica, MA). Two vials of Definity (activated per the manufacturer’s instructions) were diluted in 50 ml of saline and infused (4-10 ml/min titrated to effect). Study participants were imaged in the lithotomy position with grayscale ultrasound performed to measure gland size. Next, the prostate was evaluated with grayscale, color and power Doppler as well as with contrast-enhanced color Doppler, power Doppler and SHI with/without MIP. A standard imaging sweep through the prostate was performed in the axial plane from the base of the gland to the apex for each of the imaging modalities. The peripheral zone of each prostate was rated for suspicion of PCa at 12 sites, including the medial and lateral components of each sextant. The CE-TRUS images were interpreted by two experienced investigators (EH & FF) in consensus using a previously validated 5-point scale from 1 indicating benign, to 5 representing malignant.21 SHI was used to direct targeted biopsy of the prostate with up to 6 targeted biopsy specimens from suspicious sites. This was followed by a conventional systematic double sextant biopsy of the prostate by a second investigator blinded to the location of the targeted biopsy. A video clip including a complete sweep through the prostate from base to apex was obtained for each imaging mode to allow for off-line analysis. 6

Data Analysis Biopsy cores were interpreted by an experienced genitourinary pathologist. Each biopsy result was categorized in two ways: for the presence of PCa, and for the presence of clinically significant cancer (i.e., Gleason score ≥7 or ≥50% core involvement by tumor). First, systematic and targeted cores were analyzed for per patient and per core detection rates for PCa and clinically significant PCa. Secondly, conditional logistic regression analysis was used to assess the benefit of each imaging modality for predicting PCa as well as for predicting clinically significant PCa using Stata® 15.0 (Stata Corporation, College Station, TX). Statistical significance was considered at p<0.05. A stepwise reverse multivariate clustered conditional logistical regression was performed to select the imaging mode, which was most significant in predicting malignancy. The regression model included ten input variables: age, PSA, PSA density, and the scores from the seven imaging modes, as well as a single binary output variable: the biopsy result. Lastly, SHI scans from each of the patients were used to create time intensity curves (TIC) for the base, mid, and apex regions of the prostate. First, peak intensity (PI) parametric maps were created pixel by pixel by stepping though each frame of each clip. The time it took for each pixel to reach PI was recorded as the time to peak intensity (TTP) parameter. Finally, a parametric map of perfusion (PER) was created. This parameter estimates perfusion as the slope of the wash-in of the TIC (i.e., calculated by dividing PI by TTP). 22,23 Receiver operating characteristic (ROC) curve analysis was performed for each of the imaging modalities as well as for the three quantitative SHI parameters to determine diagnostic accuracy 7

(as area under the curve Az) for detecting PCa overall and clinically significant PCa, in particular.

Results The observers concluded that a rectangular pulse shape with a 3.5 MHz receiver frequency and a 2.5 MHz bandwidth was the optimal transmit pulse. Table 1 lists the characteristics of the 55 men enrolled in this pilot study. Patients with a positive biopsy had a higher PSA (albeit not significant; p=0.38) and a significantly lower gland volume (46.23±29.40 cm3 vs 64.84±26.20 cm3, p=0.009). Enhancement of capsular and intraprostatic vessels was observed in all patients upon intravenous infusion of the UCA. Of the 50, a total of 49 patients (98%) demonstrated suspicious enhancement on contrast enhanced ultrasound with SHI and received targeted biopsies. Figures 1 shows a representative image of SHI demonstrating suspicious asymmetrical enhancement in the left base. Comparison between systematic and targeted biopsies for detecting PCa PCa was detected in 22 of the 50 subjects (44%), and clinically significant cancer was detected in 11 of the 22 subjects (50%) using systematic biopsies. Whereas targeted biopsies diagnosed cancer in 8 subjects (16%) of which 5 were clinically significant (62.5%). Analysis of Gleason scores in the 22 patients with cancer detected by the 2 techniques failed to demonstrate any difference in Gleason scores by systematic versus directed biopsy cores (p=0.50). In total 29 patients out of the 50 had a negative prior MRI within the year prior to study participation, of which 8 were found to have PCa after biopsy (see Figure 1). 8

In term of per core, of the systematic biopsy cores, 49 of the 600 were positive for PCa (8.2%) and 24 of 228 directed cores were positive (10.5%). The logistic odds ratio (OR) of a positive result with targeted cores compared to systematic cores in patients with cancer was 1.32. The OR for positive results for clinically significant PCa was 1.39 (23 of 600 systematic cores vs 12 of 228 targeted cores). A statistically significant higher number of patients were diagnosed with prostate cancer based upon the 600 systematic cores as compared to the 228 directed cores (p=0.0002). Comparison of all imaging modalities for prediction of PCa Using conditional logistic regression for each imaging modality to assess its value for predicting malignancy, SHI was the most significant parameter for predicting PCa (p=0.001) as well as for clinically significant PCa (p=0.027), as shown in Table 2. After employing multivariate conditional logistic regression with backwards elimination, to compare SHI and other contrast enhanced imaging modalities, SHI remained as the most significant independent predictor of the presence of PCa (p=0.016) and also for clinically significant PCa (p=0.027). SHI parameters for PCa detection There was a significant difference in the estimated perfusion for clinically significant PCa compared to benign cases (34.58±11.55 ml/min*ml vs 25.32±8.26 ml/min*ml; p=0.003). There was no significant difference in the peak intensity and time to peak between the positive and benign cases; p>0.15. ROC analyses of the ability for all modalities and SHI parameters to detect all PCa as well as to detect clinically significant PCa yielded Az’s from 0.59–0.80 as shown in Table 3. SHI demonstrated an Az of 0.73 for detection of clinically significant PCa, comparable to other 9

CEUS imaging modes and the conventional grayscale imaging modes. The Az of the quantitative perfusion parameter for detecting clinically significant cancer was the highest (at 0.80) with a corresponding sensitivity of 0.80 [95% CI: 0.70%-0.89%] and specificity of 99% [95% CI: 99%100%].

Discussion In this study the role of SHI aided TRUS was assessed for the detection of PCa. Targeted biopsies aided by SHI demonstrated an OR of 1.32 and 1.39 relative to systematic biopsy for detection of PCa and clinically significant PCa, respectively. Previous studies employing CETRUS have shown an advantage over conventional TRUS, however with mixed success.24,25 In a previous clinical trial, 301 men were evaluated with contrast enhanced intermittent and continuous grayscale HI as well as color and power Doppler imaging.26 Directed cores were twice as likely to be positive as systematic cores in patients with PCa. However, directed biopsies missed 20% of patients with cancer (21 of 104), suggesting that systematic biopsy cannot be eliminated. Similar results were obtained in another study using a specific MIP implementation (MicroFlow Imaging or MFI). A potential advantage of MIP-SHI is the ability to visualize individual microvessels and to discern benign vs malignant vascular patterns. Another study by our group comparing conventional and contrast enhanced grayscale, color, power Doppler as well as continuous harmonic imaging, intermittent harmonic imaging and MIP imaging with whole mount prostectomy results achieved a maximum Az of 0.69 for identifying subjects with a >2% core involvement with contrast enhanced power Doppler.

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Based on this

study and the current study, SHI and it’s quantitative parameters is superior and demonstrates a

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greater diagnostic accuracy (0.73 and 0.80 respectively) than any of the aforementioned imaging modalities in the identification of PCa. As demonstrated in our multivariate regression model, SHI was an independent predictor of PCa even when combined with conventional grayscale and Doppler imaging as well as with previously employed contrast modalities. Although the PCa detection rate was lower relative to prior CEUS studies (OR of 1.39 in this study vs 2.10 in our prior study), a diagnostic accuracy of 80% was achieved for detection of clinically significant PCa with the quantitative SHI perfusion parameter. This suggests that further investigation into perfusion imaging with SHI may provide a useful method to predict the presence of significant PCa. Perfusion parameters of MRI have not shown much promise in diagnosing PCa. The study by Padhani et. al. found no correlation between enhancement and Gleason score or PSA levels.28 Another study used an enhanced inversion-prepared dual-contrast gradient-echo sequence at 1.5 Tesla to perform dynamic contrast enhanced MRI combined with dynamic susceptibility contrast (DSC) MR imaging and it was found that the measured blood volume and interstitial volume did not correlate with the histologic parameters. 29Lastly, a study at 3 Tesla found that the mean and 75th percentile values of wash-in and mean wash-out differed significantly between low-grade (Gleason grades 2 and 3 present) and high-grade prostate cancer (primary Gleason grade of 4 and/or any 5 component) in the peripheral zone, however the maximum Az achieved was 0.71 with the mean wash in parameter. 30 The lower OR in the current study as compared to our prior studies, may be related to a patient selection bias. Our urologists have begun using multiparametric MRI (mp-MRI) on many of their prostate biopsy patients. Many of the patients referred into the current study were sent because of a negative MP-MRI in the setting of high clinical suspicion for PCa, resulting in a study 11

population with 29 negative MRI exams out of 50 patients. It is possible that these “MRI negative” cases of PCa are more difficult to detect with CEUS, as SHI preferentially detects more aggressive cancers that are often positive on MRI. SHI based CE-TRUS may be used for all of the same applications as mp-MRI, including targeted biopsy for the diagnosis of prostate cancer, active surveillance without biopsy, and image guidance for focal therapy. Although mp-MRI is more widely used than CE-TRUS at this time, CE-TRUS has several practical advantages for clinical applications over mp-MRI. Ultrasound systems are portable and less expensive hence CE-TRUS can be performed at any location including rural sites in a cost effective manner. CE-TRUS studies can be performed at the same sitting as the ultrasound-guided biopsy, while mp-MRI requires two visits, one for the diagnostic MR study and a second for the fusion biopsy. Also, there is no need for a fusion imaging system (additional hardware/software) when using CE-TRUS. Finally, an important potential imaging advantage of CE-TRUS relative to mp-MRI is related to the superior temporal/spatial resolution of real-time ultrasound as compared with MRI. CE-TRUS provides sub-second temporal definition of contrast enhancement, and the ability to visualize neovascular patterns comprised of vessels that are sub-mm (10-50 microns) in size. Thus, although there are no studies comparing CE-TRUS directly to mp-MRI for prostate perfusion, CE-TRUS can provide superior temporal resolution for time-intensity curves and superior spatial resolution for demonstration of the neovascular pattern within the prostate. Our initial results indicate that SHI, and specifically parametric SHI, may be an effective followup screening tool for identifying clinically significant PCa in a patient population with elevated PSA or on AS. SHI can potentially reduce the number of biopsy cores for patients on AS who are subjected to annual repeat biopsies in order to detect high grade (Gleason score>7) or high 12

volume (core involvement of >50%) PCa. However, even though there was improved detection of PCa with SHI guided TRUS, there were 13 PCa cases diagnosed only by systematic biopsy, suggesting that further research is needed to optimize SHI detection of PCa. The current study was a pilot study to demonstrate the feasibility of SHI as an indicator for PCa. A larger clinical trial with quantitative SHI is needed to establish whether SHI may serve as a predictor for PCa and might replace systematic biopsy strategies.

Conclusion Contrast enhanced imaging of the prostate using SHI demonstrates excellent enhancement of the prostatic microvasculature. Directed biopsies with SHI were performed with only 1/3rd the number of cores as used for systematic sextant biopsy. ROC analysis for diagnosing clinically significant PCa using quantitative SHI perfusion estimates provided an area under the curve of 0.80. Nonetheless, many of the patients diagnosed by systematic biopsy were missed by SHI. This first in human study of SHI provides preliminary data on the diagnostic accuracy of contrast-enhanced SHI and quantitative derived parameters for detection of clinically significant PCa and may serve as the basis for future research efforts and clinical trials using SHI.

References 1. 2. 3. 4.

Center MM, Jemal A, Lortet-Tieulent J, et al. International variation in prostate cancer incidence and mortality rates. Eur Urol. 2012;61(6):1079-1092. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69(1):734. Bell KJ, Del Mar C, Wright G, Dickinson J, Glasziou P. Prevalence of incidental prostate cancer: A systematic review of autopsy studies. Int J Cancer. 2015;137(7):1749-1757. Zumsteg ZS, Spratt DE, Pei I, et al. A new risk classification system for therapeutic decision making with intermediate-risk prostate cancer patients undergoing doseescalated external-beam radiation therapy. Eur Urol. 2013;64(6):895-902.

13

5.

6.

7.

8. 9.

10. 11.

12.

13.

14.

15. 16.

17.

18. 19.

20.

Tosoian JJ, Mamawala M, Epstein JI, et al. Intermediate and Longer-Term Outcomes From a Prospective Active-Surveillance Program for Favorable-Risk Prostate Cancer. J Clin Oncol. 2015;33(30):3379-3385. Zumsteg ZS, Chen Z, Howard LE, et al. Number of Unfavorable Intermediate-Risk Factors Predicts Pathologic Upstaging and Prostate Cancer-Specific Mortality Following Radical Prostatectomy: Results From the SEARCH Database. Prostate. 2017;77(2):154163. Daeichin V, Bosch JG, Needles A, Foster FS, van der Steen A, de Jong N. Subharmonic, non-linear fundamental and ultraharmonic imaging of microbubble contrast at high frequencies. Ultrasound in Med and Biol. 2015;41(2):486-497. Paefgen V, Doleschel D, Kiessling F. Evolution of contrast agents for ultrasound imaging and ultrasound-mediated drug delivery. Front Pharmacol. 2015;6:197. Stride EP, Coussios CC. Cavitation and contrast: the use of bubbles in ultrasound imaging and therapy. Proceedings of the Institution of Mechanical Engineers Part HJournal of Engineering in Medicine. 2010;224(H2):171-191. Forsberg F, Shi WT, Goldberg BB. Subharmonic imaging of contrast agents. Ultrasonics. 2000;38(1-8):93-98. Sedelaar JP, van Leenders GJ, Hulsbergen-van de Kaa CA, et al. Microvessel density: correlation between contrast ultrasonography and histology of prostate cancer. Eur Urol. 2001;40(3):285-293. Strohmeyer D, Frauscher F, Klauser A, et al. Contrast-enhanced transrectal color doppler ultrasonography (TRCDUS) for assessment of angiogenesis in prostate cancer. Anticancer Res. 2001;21(4b):2907-2913. Bogers HA, Sedelaar JP, Beerlage HP, et al. Contrast-enhanced three-dimensional power Doppler angiography of the human prostate: correlation with biopsy outcome. Urology. 1999;54(1):97-104. Roy C, Buy X, Lang H, Saussine C, Jacqmin D. Contrast enhanced color Doppler endorectal sonography of prostate: efficiency for detecting peripheral zone tumors and role for biopsy procedure. J Urol. 2003;170(1):69-72. Frauscher F, Klauser A, Halpern EJ, Horninger W, Bartsch G. Detection of prostate cancer with a microbubble ultrasound contrast agent. Lancet. 2001;357(9271):1849-1850. Frauscher F, Klauser A, Volgger H, et al. Comparison of contrast enhanced color Doppler targeted biopsy with conventional systematic biopsy: impact on prostate cancer detection. J Urol. 2002;167(4):1648-1652. Forsberg F RR, Fox TB, Liu JB, Chiou SY, Potoczek M, Goldberg BB. Contrast enhanced maximum intensity projection ultrasound imaging for assessing angiogenesis in murine glioma and breast tumor models: A comparative study. Ultrasonics. 2011;51(3):382-389. Eisenbrey JR, Sridharan A, Machado P, et al. Three-Dimensional Subharmonic Ultrasound Imaging In Vitro and In Vivo. Acad Radiol. 2012;19(6):732-739. Biagi E, Breschi L, Varmacci E, Masotti L. Subharmonic emissions from microbubbles: Effect of the driving pulse shape. Ieee Transactions on Ultrasonics Ferroelectrics and Frequency Control. 2006;53(11):2174-2182. Gupta I, Eisenbrey J, Stanczak M, et al. Effect of Pulse Shaping on Subharmonic Aided Pressure Estimation In Vitro and In Vivo. J Ultrasound Med. 2017;36(1):3-11.

14

21.

22.

23.

24. 25.

26.

27.

28.

29.

30.

Mitterberger M, Aigner F, Pinggera GM, et al. Contrast-enhanced colour Dopplertargeted prostate biopsy: correlation of a subjective blood-flow rating scale with the histopathological outcome of the biopsy. BJU Int. 2010;106(9):1315-1318. Forsberg F, Liu JB, Shi WT, Furuse J, Shimizu M, Goldberg BB. In vivo perfusion estimation using subharmonic contrast microbubble signals. J Ultrasound Med. 2006;25(1):15-21. Sridharan A EJ, Liu JB, Machado P, Halldorsdottir VG, Dave JK, Zhao H, He Y, Park S, Dianis S, Wallace K, Thomenius KE, Forsberg F. Perfusion estimation using contrastenhanced 3-dimensional subharmonic ultrasound imaging: an in vivo study. Invest Radiol. 2013;48(9):654-660. Halpern EJ, Rosenberg M, Gomella LG. Prostate cancer: contrast-enhanced us for detection. Radiology. 2001;219(1):219-225. Halpern EJ, Verkh L, Forsberg F, Gomella LG, Mattrey RF, Goldberg BB. Initial experience with contrast-enhanced sonography of the prostate. AJR Am J Roentgenol. 2000;174(6):1575-1580. Halpern EJ RJ, Strup SE, Frauscher F, McCue P, Gomella LG. Detection of prostate carcinoma with contrast-enhanced sonography using intermittent harmonic imaging. Cancer. 2005;104(11)(0008-543X (Print)):2372-2383. Edouard J. Trabulsi, Brian P Calio, Sarah Kamel, et al. Prostate Contrast Enhanced Transrectal Ultrasound (CE-TRUS) Evaluation of the Prostate with Whole Mount Prostatectomy Correlation. Urology. 2019;(In Press). Padhani AR GC, Macvicar DA, Parker GJ, Suckling J, Revell PB, Leach MO, Dearnaley DP, Husband JE. Dynamic contrast enhanced MRI of prostate cancer: correlation with morphology and tumour stage, histological grade and PSA. Clin Radiol. 2000;55(2)(0009-9260 (Print)):99-109. Tobias Franiel LL, Birgit Rudolph, Hagen Rehbein, Carsten Stephan, Matthias Taupitz, Dirk Beyersdorff. Prostate MR Imaging: Tissue Characterization with Pharmacokinetic Volume and Blood Flow Parameters and Correlation with Histologic Parameters. Radiology. 2009;252(1):101-108. Vos EK LG, Kobus T, Hambrock T, Hulsbergen-van de Kaa CA, Barentsz JO, Huisman HJ, Scheenen TW. Assessment of prostate cancer aggressiveness using dynamic contrastenhanced magnetic resonance imaging at 3 T. Eur Urol. 2013 Sep;64(3):448-455.

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Figure Legends Figure 1. Grayscale and SHI at the base of the prostate obtained in a patient with prior negative MRI. Arrows point to an area of increased contrast enhancement at the left base. The targeted biopsy from this area demonstrated a Gleason 6 PCa.

Figure 2. Parametric maps averaged over the 12 regions; (a) PI in dB, (b) TTP in seconds, (c): PER in ml/min.

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Table 1: Patient Characteristics ( * indicates significant difference; biopsy result for overall PCa) Mean Overall

Age (yrs)

64.34 ± 7.28

PSA (ng/ml) 8.62 ± 5.46 Gland vol

Mean Positive

Mean Negative

Biopsy

Biopsy

64.26 ± 7.97

64.40 ± 6.88

0.472

8.92 ± 6.58

8.41 ± 4.58

0.375

64.84 ± 26.20*

0.009

57.06 ± 28.85 46.23 ± 29.40*

p value

(cm3)

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Table 2: Conditional logistic regression giving significance value for each imaging mode For PCa

For clinically significant PCa

p-value

p-value

0.361

0.103

0.055

0.065

0.003

0.033

0.003

0.048

0.002

0.053

SHI

0.001

0.027

MIP-SHI

0.002

0.063

Baseline: Grayscale Color Doppler Power Doppler Contrast: Color Doppler Power Doppler

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Table 3: SHI Parameters for targeted biopsies (* indicates significant difference; biopsy result for clinically significant PCa)

PI (dB)

Mean

Mean Positive

Mean Negative

Overall

Biopsy

Biopsy

124.31 ±

p value

0.431

16.07

128.23 ± 21.79

124.18 ± 15.86

TTP (sec)

3.02 ± 1.51

2.58 ± 1.29

3.03 ± 1.52

PER

25.62 ±

(ml/min*ml)

8.55

0.151 0.003

34.57 ± 11.55*

25.32 ± 8.28*

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