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Aliyev R, Hekimsoy İ, Tamsel İ, Ekizalioğlu DD, Kalemci MS, Altay B. Comparison of Testicular Sonography and Elastography Findings With Semen Parameters in Cases Investigated for Infertility. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2024; 43:1745-1754. [PMID: 38864308 DOI: 10.1002/jum.16510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 05/27/2024] [Accepted: 05/28/2024] [Indexed: 06/13/2024]
Abstract
OBJECTIVES This study aimed to investigate the correlation between testicular shear wave elastography (SWE) values and semen analysis results in men with infertility. METHODS This was a retrospective case-control study. Patients were categorized as normal, abnormal, or azoospermic based on sperm analysis results. Testicular volume was measured using B-mode ultrasonography using the Lambert formula. Subsequently, 40-80 regions of interest measuring 1.5 × 1.5 mm were manually positioned in both testicles based on their size, and two-dimensional SWE was applied through virtual touch imaging quantification software. RESULTS The patients had a mean age of 33.79 ± 6.3 years, with semen analysis revealing normal results in 15 patients (22.4%), pathological findings in 35 patients (52.2%), and azoospermia in 17 patients (25.4%). Right, left, total, and mean testicular volumes were significantly lower in patients with azoospermia compared to those in both normal and impaired semen parameters (P < .05). Conversely, testicular elastography scores were higher in patients with azoospermia than in the other groups (P < .05). The significant negative correlation between volume and elastographic findings remained independent of age (r = 0.4, P < .001). The accuracy rates for detecting impaired semen parameters and azoospermia were 94.3% and 94.1%, respectively, after considering factors such as age, testicular volume (right/left/total), and elastography (right/left/total). Notably, the total mean elastography score ranked first, with 100% in the independent normalized importance distribution of these variables. CONCLUSION SWE can be used effectively alone or in combination with other diagnostic tools to evaluate histopathological changes in the testicles of male patients with infertility.
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Affiliation(s)
- Ramil Aliyev
- Division of Radiology, Medicana International İzmir Hospital, İzmir, Turkey
| | - İlhan Hekimsoy
- Division of Radiology, İzmir Torbalı State Hospital, İzmir, Turkey
| | - İpek Tamsel
- Department of Radiology, Ege University School of Medicine, İzmir, Turkey
| | | | | | - Barış Altay
- Department of Urology, Ege University School of Medicine, İzmir, Turkey
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Chan DY, Morris DC, Moavenzadeh SR, Lye TH, Polascik TJ, Palmeri ML, Mamou J, Nightingale KR. Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks. ULTRASOUND IN MEDICINE & BIOLOGY 2024:S0301-5629(24)00285-0. [PMID: 39174376 DOI: 10.1016/j.ultrasmedbio.2024.07.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 06/17/2024] [Accepted: 07/25/2024] [Indexed: 08/24/2024]
Abstract
OBJECTIVE A deep neural network (DNN) was trained to generate a multiparametric ultrasound (mpUS) volume from four input ultrasound-based modalities (acoustic radiation force impulse [ARFI] imaging, shear wave elasticity imaging [SWEI], quantitative ultrasound-midband fit [QUS-MF], and B-mode) for the detection of prostate cancer. METHODS A DNN was trained using co-registered ARFI, SWEI, MF, and B-mode data obtained in men with biopsy-confirmed prostate cancer prior to radical prostatectomy (15 subjects, comprising 980,620 voxels). Data were obtained using a commercial scanner that was modified to allow user control of the acoustic beam sequences and provide access to the raw image data. For each subject, the index lesion and a non-cancerous region were manually segmented using visual confirmation based on whole-mount histopathology data. RESULTS In a prostate phantom, the DNN increased lesion contrast-to-noise ratio (CNR) compared to a previous approach that used a linear support vector machine (SVM). In the in vivo test datasets (n = 15), the DNN-based mpUS volumes clearly portrayed histopathology-confirmed prostate cancer and significantly improved CNR compared to the linear SVM (2.79 ± 0.88 vs. 1.98 ± 0.73, paired-sample t-test p < 0.001). In a sub-analysis in which the input modalities to the DNN were selectively omitted, the CNR decreased with fewer inputs; both stiffness- and echogenicity-based modalities were important contributors to the multiparametric model. CONCLUSION The findings from this study indicate that a DNN can be optimized to generate mpUS prostate volumes with high CNR from ARFI, SWEI, MF, and B-mode and that this approach outperforms a linear SVM approach.
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Affiliation(s)
- Derek Y Chan
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
| | - D Cody Morris
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Theresa H Lye
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA; Topcon Advanced Biomedical Imaging Laboratory, Topcon Healthcare, Oakland, NJ, USA
| | - Thomas J Polascik
- Departments of Urology and Radiology, Duke University Medical Center, Durham, NC, USA
| | - Mark L Palmeri
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Jonathan Mamou
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
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Duan J, Liu Z, Li Z, Wang H, Zhao W. Research on the mean maximum Young's modulus value as a new diagnostic parameter for prostate cancer. Sci Rep 2024; 14:16828. [PMID: 39039192 PMCID: PMC11263570 DOI: 10.1038/s41598-024-68036-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Accepted: 07/18/2024] [Indexed: 07/24/2024] Open
Abstract
Ultrasound-based shear wave elastography (SWE) can non-invasively assess prostate tissue stiffness for the diagnosis of prostate cancer (PCa). So far, there is no widely recognized standard for the detection process and calculation method of Young's modulus value in transrectal SWE ultrasound imaging (TSWEUI). In our study, the mean maximum Young's modulus value (m-Emax) of the maximum cross-section of prostate is obtained by calculating the mean of 12 measured Emax in the four quadrants. This retrospective study included 209 suspected malignant prostate disease patients with pathological results in our hospital. Among the 209 patients, 75 patients completed TSWEUI, and 63 of the 75 patients completed magnetic resonance imaging (MRI). The area under the receiver operating characteristic (ROC) curve (AUC) of 75 patients for m-Emax was 0.754. The prostate volume, prostate-specific antigen, and m-Emax were used to develop a nomogram (AUC = 0.868). The nomogram could effectively predict the probability of PCa, thereby reducing the needle biopsy rate for diagnosing PCa. The AUC of 63 patients was not statistically different between m-Emax (AUC = 0.717) and MRI (AUC = 0.787) (P = 0.361). These indicate that m-Emax can be used as an innovative parameter in TSWEUI to diagnosis PCa. TSWEUI is more cost-effective than MRI in diagnosing PCa.
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Affiliation(s)
- Jieyu Duan
- Department of Ultrasound, First Affiliated Hospital of Zhengzhou University, Zhengzhoug City, 450052, Henan Province, China
| | - ZhanHui Liu
- Department of Radiology, The First Hospital of Hebei Medical University, Shijiazhuang City, 050031, Hebei Province, China
| | - Zhong Li
- Department of Urology, The First Hospital of Hebei Medical University, Shijiazhuang City, 050031, Hebei Province, China
| | - Haoyu Wang
- Department of Ultrasound, The First Hospital of Hebei Medical University, 89 Donggang Road, Yuhua District, Shijiazhuang City, 050031, Hebei Province, China
| | - Wei Zhao
- Department of Ultrasound, The First Hospital of Hebei Medical University, 89 Donggang Road, Yuhua District, Shijiazhuang City, 050031, Hebei Province, China.
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Liu M, Cui N, Sun C, Gong X, Wang B, Yang D, Wang Y. A prospective study on using shear wave elastography to predict the ypT0 stage of rectal cancer after neoadjuvant therapy: a new support for the watch-and-wait approach? Front Mol Biosci 2024; 11:1402498. [PMID: 38737335 PMCID: PMC11082269 DOI: 10.3389/fmolb.2024.1402498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Accepted: 04/15/2024] [Indexed: 05/14/2024] Open
Abstract
Introduction The diagnostic accuracy of traditional imaging examination in predicting ypT stage of rectal cancer after neoadjuvant therapy is significantly reduced, which would affect patients' subsequent treatment choices. This study aimed to investigate the use of endorectal shear wave elastography (SWE) for diagnosing ypT0 stage of rectal cancer after neoadjuvant chemoradiotherapy (nCRT). Methods Sixty patients with rectal cancer were prospectively recruited in this study. Data on endorectal ultrasound (ERUS) and SWE parameters were collected before nCRT and 6-8 weeks after nCRT. Postoperative pathological results were the gold standard for evaluating the diagnostic accuracy of SWE and ERUS in predicting the ypT0 stage of rectal cancer after nCRT. Receiver operating characteristic (ROC) curve analysis was used to determine the cut-off values of the SWE parameters that best corresponded to the ypT0 stage and analyze the sensitivity, specificity, and accuracy. Results The diagnostic accuracies of using ERUS to predict the ypT and ypT0 stages of rectal cancer after nCRT were 58.1% (18/31) and 64.3% (9/14), respectively. The ROC curve was constructed with the lesion's Emean, Emean corrected (EC), Emean difference (ED), Emean corrected differencede (ECD), Emean descendding rate (EDR) and Emean corrected descendding rate (ECDR) values after nCRT, the cut-off values of diagnosing the ypT0 stage were 64.40 kPa, 55.45 kPa, 72.55 kPa, 73.75 kPa, 50.15%, and 55.93%, respectively; the area under the curve (AUC) for diagnosing the ypT0 stage was 0.924, 0.933, 0.748, 0.729, 0.857 and 0.861, respectively. The EC value showed the best diagnostic performance. Conclusion SWE could improve the accuracy of conventional ERUS in diagnosing the ypT0 stage of rectal cancer after nCRT. It is expected to become a new method to help predict pathological complete responses in clinical practice and provide new evidence for the watch-and-wait approach.
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Affiliation(s)
| | | | | | | | | | | | - Yong Wang
- Department of Ultrasound, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Payen T, Crouzet S, Guillen N, Chen Y, Chapelon JY, Lafon C, Catheline S. Passive Elastography for Clinical HIFU Lesion Detection. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:1594-1604. [PMID: 38109239 DOI: 10.1109/tmi.2023.3344182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
High-intensity Focused Ultrasound (HIFU) is a promising treatment modality for a wide range of pathologies including prostate cancer. However, the lack of a reliable ultrasound-based monitoring technique limits its clinical use. Ultrasound currently provides real-time HIFU planning, but its use for monitoring is usually limited to detecting the backscatter increase resulting from chaotic bubble appearance. HIFU has been shown to generate stiffening in various tissues, so elastography is an interesting lead for ablation monitoring. However, the standard techniques usually require the generation of a controlled push which can be problematic in deeper organs. Passive elastography offers a potential alternative as it uses the physiological wave field to estimate the elasticity in tissues and not an external perturbation. This technique was adapted to process B-mode images acquired with a clinical system. It was first shown to faithfully assess elasticity in calibrated phantoms. The technique was then implemented on the Focal One® clinical system to evaluate its capacity to detect HIFU lesions in vitro (CNR = 9.2 dB) showing its independence regarding the bubbles resulting from HIFU and in vivo where the physiological wave field was successfully used to detect and delineate lesions of different sizes in porcine liver. Finally, the technique was performed for the very first time in four prostate cancer patients showing strong variation in elasticity before and after HIFU treatment (average variation of 33.0 ± 16.0 % ). Passive elastography has shown evidence of its potential to monitor HIFU treatment and thus help spread its use.
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Ditonno F, Franco A, Manfredi C, Veccia A, Valerio M, Bukavina L, Zukowski LB, Vourganti S, Stenzl A, Andriole GL, Antonelli A, De Nunzio C, Autorino R. Novel non-MRI imaging techniques for primary diagnosis of prostate cancer: micro-ultrasound, contrast-enhanced ultrasound, elastography, multiparametric ultrasound, and PSMA PET/CT. Prostate Cancer Prostatic Dis 2024; 27:29-36. [PMID: 37543656 DOI: 10.1038/s41391-023-00708-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/17/2023] [Accepted: 07/20/2023] [Indexed: 08/07/2023]
Abstract
BACKGROUND Multiparametric magnetic resonance imaging (mpMRI) provides enhanced diagnostic accuracy in the detection of prostate cancer, but is not devoid of limitations. Given the recent evolution of non-MRI imaging techniques, this critical review of the literature aimed at summarizing the available evidence on ultrasound-based and nuclear medicine imaging technologies in the initial diagnosis of PCa. METHODS Three databases (PubMed®, Web of Science™, and Scopus®) were queried for studies examining their diagnostic performance in the primary diagnosis of PCa, weighted against a histological confirmation of PCa diagnosis, using a free-text protocol. Retrospective and prospective studies, both comparative and non-comparative, systematic reviews (SR) and meta-analysis (MA) were included. Based on authors' expert opinion, studies were selected, data extracted, and results qualitatively described. RESULTS Micro-ultrasound (micro-US) appears as an appealing diagnostic strategy given its high accuracy in detection of PCa, apparently non-inferior to mpMRI. The use of multiparametric US (mpUS) likely gives an advantage in terms of effectiveness coming from the combination of different modalities, especially when certain modalities are combined. Prostate-specific membrane antigen (PSMA) PET/CT may represent a whole-body, one-step approach for appropriate diagnosis and staging of PCa. The direct relationship between lesions avidity of radiotracers and histopathologic and prognostic features, and its valid diagnostic performance represents appealing characteristics. However, intrinsic limits of each of these techniques exist and further research is needed before definitively considering them reliable tools for accurate PCa diagnosis. Other novel technologies, such as elastography and multiparametric US, currently relies on a limited number of studies, and therefore evidence about them remains preliminary. CONCLUSION Evidence on the role of non-MRI imaging options in the primary diagnosis of PCa is steadily building up. This testifies a growing interest towards novel technologies that might allow overcoming some of the limitations of current gold standard MRI imaging.
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Affiliation(s)
- Francesco Ditonno
- Department of Urology, Rush University Medical Center, Chicago, IL, USA
- Department of Urology, University of Verona, Verona, Italy
| | - Antonio Franco
- Department of Urology, Rush University Medical Center, Chicago, IL, USA
- Department of Urology, Sant'Andrea Hospital, La Sapienza University, Rome, Italy
| | - Celeste Manfredi
- Department of Urology, Rush University Medical Center, Chicago, IL, USA
- Urology Unit, Department of Woman, Child and General and Specialized Surgery, "Luigi Vanvitelli" University, Naples, Italy
| | | | - Massimo Valerio
- Urology Department, Lausanne University Hospital, Lausanne, Switzerland
| | - Laura Bukavina
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Lucas B Zukowski
- Department of Urology, Rush University Medical Center, Chicago, IL, USA
| | | | - Arnuf Stenzl
- Department of Urology, University Hospital Tuebingen, Tuebingen, Germany
| | - Gerald L Andriole
- Johns Hopkins Medicine, Sibley Memorial Hospital, Washington, DC, USA
| | | | - Cosimo De Nunzio
- Department of Urology, Sant'Andrea Hospital, La Sapienza University, Rome, Italy
| | - Riccardo Autorino
- Department of Urology, Rush University Medical Center, Chicago, IL, USA.
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Helisaz H, Belanger E, Black P, Bacca M, Chiao M. Quantifying the Impact of Cancer on the Viscoelastic Properties of the Prostate Gland using a Quasi-Linear Viscoelastic Model. Acta Biomater 2024; 173:184-198. [PMID: 37939817 DOI: 10.1016/j.actbio.2023.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 10/27/2023] [Accepted: 11/01/2023] [Indexed: 11/10/2023]
Abstract
Pathological disorders can alter the mechanical properties of biological tissues, and studying such changes can help to better understand the disease progression. The prostate gland is no exception, as previous studies have shown that cancer can affect its mechanical properties. However, most of these studies have focused on the elastic properties of the tissue and have overlooked the impact of cancer on its viscous response. To address this gap, we used a quasi-linear viscoelastic model to investigate the impact of cancer on both the elastic and viscous characteristics of the prostate gland. By comparing the viscoelastic properties of segments influenced by cancer and those unaffected by cancer in 49 fresh prostates, removed within two hours after prostatectomy surgery, we were able to determine the influence of cancer grade and tumor volume on the tissue. Our findings suggest that tumor volume significantly affects both the elastic modulus and viscosity of the prostate (p-value less than 2%). Specifically, we showed that cancer increases Young's modulus and shear relaxation modulus by 20%. These results have implications for using mechanical properties of the prostate as a potential biomarker for cancer. However, developing an in vivo apparatus to measure these properties remains a challenge that needs to be addressed in future research. STATEMENT OF SIGNIFICANCE: This study is the first to explore how cancer impacts the mechanical properties of prostate tissues using a quasi-linear viscoelastic model. We examined 49 fresh prostate samples collected immediately after surgery and correlated their properties with cancer presence identified in pathology reports. Our results demonstrate a 20% change in the viscoelastic properties of the prostate due to cancer. We initially validated our approach using tissue-mimicking phantoms and then applied it to differentiate between cancerous and normal prostate tissues. These findings offer potential for early cancer detection by assessing these properties. However, conducting these tests in vivo remains a challenge for future research.
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Affiliation(s)
- Hamed Helisaz
- Department of Mechanical Engineering, University of British Columbia, V6T 1Z4, BC, Canada
| | - Eric Belanger
- Department of Pathology and Laboratory Medicine, University of British Columbia, V6T 1Z4, BC, Canada
| | - Peter Black
- Department of Urologic Sciences, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada
| | - Mattia Bacca
- Department of Mechanical Engineering, University of British Columbia, V6T 1Z4, BC, Canada
| | - Mu Chiao
- Department of Mechanical Engineering, University of British Columbia, V6T 1Z4, BC, Canada.
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Tang Y, Li X, Jiang Q, Zhai L. Diagnostic accuracy of multiparametric ultrasound in the diagnosis of prostate cancer: systematic review and meta-analysis. Insights Imaging 2023; 14:203. [PMID: 38001351 PMCID: PMC10673798 DOI: 10.1186/s13244-023-01543-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/15/2023] [Indexed: 11/26/2023] Open
Abstract
OBJECTIVES Ultrasound (US) technology has recently made advances that have led to the development of modalities including elastography and contrast-enhanced ultrasound. The use of different US modalities in combination may increase the accuracy of PCa diagnosis. This study aims to assess the diagnostic accuracy of multiparametric ultrasound (mpUS) in the PCa diagnosis. METHODS Through September 2023, we searched through Cochrane CENTRAL, PubMed, Embase, Scopus, Web of Science, ClinicalTrial.gov, and Google Scholar for relevant studies. We used standard methods recommended for meta-analyses of diagnostic evaluation. We plot the SROC curve, which stands for summary receiver operating characteristic. To determine how confounding factors affected the results, meta-regression analysis was used. RESULTS Finally, 1004 patients from 8 studies that were included in this research were examined. The diagnostic odds ratio for PCa was 20 (95% confidence interval (CI), 8-49) and the pooled estimates of mpUS for diagnosis were as follows: sensitivity, 0.88 (95% CI, 0.81-0.93); specificity, 0.72 (95% CI, 0.59-0.83); positive predictive value, 0.75 (95% CI, 0.63-0.87); and negative predictive value, 0.82 (95% CI, 0.71-0.93). The area under the SROC curve was 0.89 (95% CI, 0.86-0.92). There was a significant heterogeneity among the studies (p < 0.01). According to meta-regression, both the sensitivity and specificity of mpUS in the diagnosis of clinically significant PCa (csPCa) were inferior to any PCa. CONCLUSION The diagnostic accuracy of mpUS in the diagnosis of PCa is moderate, but the accuracy in the diagnosis of csPCa is significantly lower than any PCa. More relevant research is needed in the future. CRITICAL RELEVANCE STATEMENT This study provides urologists and sonographers with useful data by summarizing the accuracy of multiparametric ultrasound in the detection of prostate cancer. KEY POINTS • Recent studies focused on the role of multiparametric ultrasound in the diagnosis of prostate cancer. • This meta-analysis revealed that multiparametric ultrasound has moderate diagnostic accuracy for prostate cancer. • The diagnostic accuracy of multiparametric ultrasound in the diagnosis of clinically significant prostate cancer is significantly lower than any prostate cancer.
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Affiliation(s)
- Yun Tang
- Department of Geriatric Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
- Longmen Hao Street Community Health Service Center, Nan'an District, Chongqing, 401336, China
| | - Xingsheng Li
- Department of Geriatric Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Qing Jiang
- Department of Urology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
| | - Lingyun Zhai
- Department of Urology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
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Bucci R, Del Signore F, Vignoli M, Felici A, Russo M, Maresca C, Carluccio A. Canine prostatic serum esterase and strain and 2D-shear wave sonoelastography for evaluation of normal prostate in dogs: Preliminary results. Reprod Domest Anim 2023; 58:1311-1319. [PMID: 37501343 DOI: 10.1111/rda.14435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 07/03/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023]
Abstract
Canine prostatic serum esterase (CPSE) is considered a useful tool to identify prostate disorders in dogs, with increasing interest in ultrasound (US)-based sonoelastography to non-invasively detect prostate disorders. Since no report is available about a possible correlation between these diagnostic tools, we aimed to investigate a possible correlation between strain elastography (SE) and 2D-shear wave elastography (SWE) and CPSE. Twenty-one dogs were included and, on each animal, CPSE was evaluated followed by a complete US examination and SE and 2D-SWE application. Healthy dogs were identified based on the CPSE results. All the dogs included were characterized by normal CPSE values (<52.3 ng/mL) and normal US prostate appearance. The prostate was characterized by intermediate stiffness with SE (pattern III - 84.7% for the left lobe and 79.27% for the right lobe) and softer than the abdominal wall (SR 0.6 for the left lobe and 0.56 for the right lobe), with low values for both m/s and kilopascals (kPa) for 2D-SWE, pointing that the healthy tissue is not hard. 2D-SWE results were, respectively, 13.51 ± 5.55 kPa and 2.31 ± 0.42 m/s for the left lobe and 18.05 ± 6.47 kPa and 2.39 ± 0.43 m/s for the right lobe. The significant difference between the right and left measurements expressed with kPa, not evidenced with m/s, can be considered indicative of m/s as the most reliable measurement to be considered regarding the prostate parenchyma. Even though no linear correlation was detected between CPSE and elastography values, these preliminary results evidence that the healthy prostates were characterized by a similar elastographic pattern, thus pointing that these techniques can be potentially useful to be applied in case of prostatic disorders to improve the accuracy of the final diagnosis in a non-invasive way.
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Affiliation(s)
- Roberta Bucci
- Department of Veterinary Medicine, University of Teramo, Teramo, Italy
| | | | - Massimo Vignoli
- Department of Veterinary Medicine, University of Teramo, Teramo, Italy
| | - Andrea Felici
- Istituto Zooprofilattico Sperimentale dell'Umbria e delle Marche "Togo Rosati", Perugia, Italy
| | - Marco Russo
- Department of Veterinary Medicine and Animal Production, University of Naples, Naples, Italy
| | - Carmen Maresca
- Istituto Zooprofilattico Sperimentale dell'Umbria e delle Marche "Togo Rosati", Perugia, Italy
| | - Augusto Carluccio
- Department of Veterinary Medicine, University of Teramo, Teramo, Italy
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Clinical Trial Protocol: Developing an Image Classification Algorithm for Prostate Cancer Diagnosis on Three-dimensional Multiparametric Transrectal Ultrasound. EUR UROL SUPPL 2023; 49:32-43. [PMID: 36874606 PMCID: PMC9975006 DOI: 10.1016/j.euros.2022.12.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/22/2022] [Indexed: 01/27/2023] Open
Abstract
Introduction and hypothesis The tendency toward population-based screening programs for prostate cancer (PCa) is expected to increase demand for prebiopsy imaging. This study hypothesizes that a machine learning image classification algorithm for three-dimensional multiparametric transrectal prostate ultrasound (3D mpUS) can detect PCa accurately. Design This is a phase 2 prospective multicenter diagnostic accuracy study. A total of 715 patients will be included in a period of approximately 2 yr. Patients are eligible in case of suspected PCa for which prostate biopsy is indicated or in case of biopsy-proven PCa for which radical prostatectomy (RP) will be performed. Exclusion criteria are prior treatment for PCa or contraindications for ultrasound contrast agents (UCAs). Protocol overview Study participants will undergo 3D mpUS, consisting of 3D grayscale, 4D contrast-enhanced ultrasound, and 3D shear wave elastography (SWE). Whole-mount RP histopathology will provide the ground truth to train the image classification algorithm. Patients included prior to prostate biopsy will be used for subsequent preliminary validation. There is a small, anticipated risk for participants associated with the administration of a UCA. Informed consent has to be given prior to study participation, and (serious) adverse events will be reported. Statistical analysis The primary outcome will be the diagnostic performance of the algorithm for detecting clinically significant PCa (csPCa) on a per-voxel and a per-microregion level. Diagnostic performance will be reported as the area under the receiver operating characteristic curve. Clinically significant PCa is defined as the International Society of Urological grade group ≥2. Full-mount RP histopathology will be used as the reference standard. Secondary outcomes will be sensitivity, specificity, negative predictive value, and positive predictive value for csPCa on a per-patient level, evaluated in patients included prior to prostate biopsy, using biopsy results as the reference standard. A further analysis will be performed on the ability of the algorithm to differentiate between low-, intermediate-, and high-risk tumors. Discussion and summary This study aims to develop an ultrasound-based imaging modality for PCa detection. Subsequent head-to-head validation trials with magnetic resonance imaging have to be performed in order to determine its role in clinical practice for risk stratification in patients suspected for PCa.
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Roots J, Trajano GS, Drovandi C, Fontanarosa D. Variability of Biceps Muscle Stiffness Measured Using Shear Wave Elastography at Different Anatomical Locations With Different Ultrasound Machines. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:398-409. [PMID: 36266142 DOI: 10.1016/j.ultrasmedbio.2022.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 09/08/2022] [Accepted: 09/12/2022] [Indexed: 06/16/2023]
Abstract
Shear wave elastography is an emerging diagnostic tool used to assess for changes in the stiffness of muscle. Each region of the muscle may have a different stiffness; therefore, the anatomical region should be carefully selected. Machine vendors each have unique methods for calculating the returned stiffness values and, consequently, a high level of agreement in measurement between machines (quantified using the intraclass correlation coefficient [ICC] and Bland-Altman analysis) will allow research findings to be translated to the clinic. This study assessed three locations within the biceps muscle (50% and 75% of the distance between the acromioclavicular joint and antecubital fossa, and superior to distal myotendinous junction [MTJ]) of 32 healthy volunteers with two different machines, the Canon Aplio i600 and SuperSonic Imagine Aixplorer (SSI), to compare the reported shear wave velocities and the variability by coefficient of variation (CV) and ICC. There was no difference in the CV between machines, but a significant difference in the CV at muscle regions, with the 75% location having a 40.2% reduction in CV. The 75% location had the highest ICC values with good posterior mean ICCs of 0.84 on the Canon and 0.83 on the SSI. The 50% and MTJ locations had poor ICC values. The 75% location provided the lowest CV and highest ICC and should be used for future stiffness assessments.
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Affiliation(s)
- Jacqueline Roots
- School of Clinical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, Queensland, Australia.
| | - Gabriel S Trajano
- School of Exercise and Nutrition Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Christopher Drovandi
- Centre of Data Science, Queensland University of Technology, Brisbane, Queensland, Australia; School of Mathematical Sciences, Faculty of Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Davide Fontanarosa
- School of Clinical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, Queensland, Australia
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12
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Quantitative Assessment of Breast-Tumor Stiffness Using Shear-Wave Elastography Histograms. Diagnostics (Basel) 2022; 12:diagnostics12123140. [PMID: 36553148 PMCID: PMC9777730 DOI: 10.3390/diagnostics12123140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/08/2022] [Accepted: 12/11/2022] [Indexed: 12/15/2022] Open
Abstract
Purpose: Shear-wave elastography (SWE) measures tissue elasticity using ultrasound waves. This study proposes a histogram-based SWE analysis to improve breast malignancy detection. Methods: N = 22/32 (patients/tumors) benign and n = 51/64 malignant breast tumors with histological ground truth. Colored SWE heatmaps were adjusted to a 0−180 kPa scale. Normalized, 250-binned RGB histograms were used as image descriptors based on skewness and area under curve (AUC). The histogram method was compared to conventional SWE metrics, such as (1) the qualitative 5-point scale classification and (2) average stiffness (SWEavg)/maximal tumor stiffness (SWEmax) within the tumor B-mode boundaries. Results: The SWEavg and SWEmax did not discriminate malignant lesions in this database, p > 0.05, rank sum test. RGB histograms, however, differed between malignant and benign tumors, p < 0.001, Kolmogorov−Smirnoff test. The AUC analysis of histograms revealed the reduction of soft-tissue components as a significant SWE biomarker (p = 0.03, rank sum). The diagnostic accuracy of the suggested method is still low (Se = 0.30 for Se = 0.90) and a subject for improvement in future studies. Conclusions: Histogram-based SWE quantitation improved the diagnostic accuracy for malignancy compared to conventional average SWE metrics. The sensitivity is a subject for improvement in future studies.
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13
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Sigle A, Michaelis J, Schöb D, Benndorf M, Schimmöller L, Becker B, Pallauf M, Gross AJ, Herrmann TRW, Klein JT, Lusuardi L, Netsch C, Häcker A, Westphal J, Jilg C, Gratzke C, Miernik A. [Image-guided biopsy of the prostate gland]. UROLOGIE (HEIDELBERG, GERMANY) 2022; 61:1137-1148. [PMID: 36040512 DOI: 10.1007/s00120-022-01929-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
The recommendations on carrying out a multiparametric magnetic resonance imaging (mpMRI) for the primary diagnostics and during active surveillance of prostate cancer, include as a consequence an image-guided sampling from conspicuous areas. In doing so, the information on the localization provided by mpMRI is used for a targeted biopsy of the area suspected of being a tumor. The targeted sampling is mainly performed under sonographic control and after fusion of MRI and ultrasound but can also be (mostly in special cases) carried out directly in the MRI scanner. In an ultrasound-guided biopsy, it is vital to coregister the MR images with the ultrasound images (segmentation of the contour of the prostate and registration of suspect findings). This coregistration can either be carried out cognitively (transfer by the person performing the biopsy alone) or software based. Each method shows specific advantages and disadvantages in the prioritization between diagnostic accuracy and resource expenditure.
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Affiliation(s)
- August Sigle
- Medizinische Fakultät, Klinik für Urologie, Universitätsklinikum Freiburg, Hugstetter Straße 55, 79106, Freiburg, Deutschland.
- Berta-Ottenstein-Programm, Medizinische Fakultät, Universität Freiburg, Freiburg, Deutschland.
| | - Jakob Michaelis
- Medizinische Fakultät, Klinik für Urologie, Universitätsklinikum Freiburg, Hugstetter Straße 55, 79106, Freiburg, Deutschland
| | - Dominik Schöb
- Medizinische Fakultät, Klinik für Urologie, Universitätsklinikum Freiburg, Hugstetter Straße 55, 79106, Freiburg, Deutschland
| | - Matthias Benndorf
- Medizinische Fakultät, Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Freiburg, Freiburg, Deutschland
| | - Lars Schimmöller
- Medizinische Fakultät, Institut für Diagnostische und Interventionelle Radiologie, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Deutschland
| | - Benedikt Becker
- Abteilung für Urologie, Asklepios Klinik Barmbek, Hamburg, Deutschland
| | - Maximilian Pallauf
- Johns Hopkins University, Baltimore, USA
- Department für Urologie und Onkologie, Paracelsus Medizinische Privatuniversität, Salzburg, Österreich
- Department für Urologie, Uniklinikum Salzburg, Salzburg, Österreich
| | - Andreas J Gross
- Abteilung für Urologie, Asklepios Klinik Barmbek, Hamburg, Deutschland
| | - Thomas R W Herrmann
- Urologie, Spital Thurgau AG, Frauenfeld, Schweiz
- Medizinische Hochschule Hannover, Hannover, Deutschland
- Division of Urology, Department of Surgical Sciences, Stellenbosch University, Western Cape, Südafrika
| | - Jan-Thorsten Klein
- Klinik für Urologie und Kinderurologie, Universitätsklinikum Ulm, Ulm, Deutschland
| | - Lukas Lusuardi
- Paracelsus Medizinische Universitätsklinik für Urologie, Salzburger Landeskliniken, Salzburg, Österreich
| | | | - Axel Häcker
- Klinik für Urologie, Universitätsklinikum Mannheim, Mannheim, Deutschland
| | - Jens Westphal
- Klinik für Urologie, Kinderurologie und Urogynäkologie, Krankenhaus Maria-Hilf, Akademisches Lehrkrankenhaus der Heinrich-Heine-Universität Düsseldorf, Krefeld, Deutschland
| | - Cordula Jilg
- Medizinische Fakultät, Klinik für Urologie, Universitätsklinikum Freiburg, Hugstetter Straße 55, 79106, Freiburg, Deutschland
| | - Christian Gratzke
- Medizinische Fakultät, Klinik für Urologie, Universitätsklinikum Freiburg, Hugstetter Straße 55, 79106, Freiburg, Deutschland
| | - Arkadiusz Miernik
- Medizinische Fakultät, Klinik für Urologie, Universitätsklinikum Freiburg, Hugstetter Straße 55, 79106, Freiburg, Deutschland
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14
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Habbit NL, Anbiah B, Anderson L, Suresh J, Hassani I, Eggert M, Brannen A, Davis J, Tian Y, Prabhakarpandian B, Panizzi P, Arnold RD, Lipke EA. Tunable three-dimensional engineered prostate cancer tissues for in vitro recapitulation of heterogeneous in vivo prostate tumor stiffness. Acta Biomater 2022; 147:73-90. [PMID: 35551999 DOI: 10.1016/j.actbio.2022.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 04/21/2022] [Accepted: 05/05/2022] [Indexed: 11/24/2022]
Abstract
In this manuscript we report the establishment and characterization of a three-dimensional in vitro, coculture engineered prostate cancer tissue (EPCaT) disease model based upon and informed by our characterization of in vivo prostate cancer (PCa) xenograft tumor stiffness. In prostate cancer, tissue stiffness is known to impact changes in gene and protein expression, alter therapeutic response, and be positively correlated with an aggressive clinical presentation. To inform an appropriate stiffness range for our in vitro model, PC-3 prostate tumor xenografts were established. Tissue stiffness ranged from 95 to 6,750 Pa. Notably, xenograft cell seeding density significantly impacted tumor stiffness; a two-fold increase in the number of seeded cells not only widened the tissue stiffness range throughout the tumor but also resulted in significant spatial heterogeneity. To fabricate our in vitro EPCaT model, PC-3 castration-resistant prostate cancer cells were co-encapsulated with BJ-5ta fibroblasts within a poly(ethylene glycol)-fibrinogen matrix augmented with excess poly(ethylene glycol)-diacrylate to modulate the matrix mechanical properties. Encapsulated cells temporally remodeled their in vitro microenvironment and enrichment of gene sets associated with tumorigenic progression was observed in response to increased matrix stiffness. Through variation of matrix composition and culture duration, EPCaTs were tuned to mimic the wide range of biomechanical cues provided to PCa cells in vivo; collectively, a range of 50 to 10,000 Pa was achievable. Markedly, this also encompasses published clinical PCa stiffness data. Overall, this study serves to introduce our bioinspired, tunable EPCaT model and provide the foundation for future PCa progression and drug development studies. STATEMENT OF SIGNIFICANCE: The development of cancer models that mimic the native tumor microenvironment (TME) complexities is critical to not only develop effective drugs but also enhance our understanding of disease progression. Here we establish and characterize our 3D in vitro engineered prostate cancer tissue model with tunable matrix stiffness, that is inspired by this study's spatial characterization of in vivo prostate tumor xenograft stiffness. Notably, our model's mimicry of the TME is further augmented by the inclusion of matrix remodeling fibroblasts to introduce cancer-stromal cell-cell interactions. This study addresses a critical unmet need in the field by elucidating the prostate tumor xenograft stiffness range and establishing a foundation for recapitulating the biomechanics of site-of-origin and soft tissue metastatic prostate tumors in vitro.
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Affiliation(s)
- Nicole L Habbit
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, 212 Ross Hall, Auburn, AL 36849, USA
| | - Benjamin Anbiah
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, 212 Ross Hall, Auburn, AL 36849, USA
| | - Luke Anderson
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, 212 Ross Hall, Auburn, AL 36849, USA
| | - Joshita Suresh
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, 212 Ross Hall, Auburn, AL 36849, USA
| | - Iman Hassani
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, 212 Ross Hall, Auburn, AL 36849, USA
| | - Matthew Eggert
- Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 362 Thach Concourse, Auburn, AL 36849, USA
| | - Andrew Brannen
- Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 362 Thach Concourse, Auburn, AL 36849, USA
| | - Joshua Davis
- Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 362 Thach Concourse, Auburn, AL 36849, USA
| | - Yuan Tian
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, 212 Ross Hall, Auburn, AL 36849, USA
| | | | - Peter Panizzi
- Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 362 Thach Concourse, Auburn, AL 36849, USA
| | - Robert D Arnold
- Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, 362 Thach Concourse, Auburn, AL 36849, USA
| | - Elizabeth A Lipke
- Department of Chemical Engineering, Samuel Ginn College of Engineering, Auburn University, 212 Ross Hall, Auburn, AL 36849, USA.
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15
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Artificial Intelligence System for Predicting Prostate Cancer Lesions from Shear Wave Elastography Measurements. Curr Oncol 2022; 29:4212-4223. [PMID: 35735445 PMCID: PMC9221963 DOI: 10.3390/curroncol29060336] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/05/2022] [Accepted: 06/08/2022] [Indexed: 12/12/2022] Open
Abstract
(1) Objective: To design an artificial intelligence system for prostate cancer prediction using the data obtained by shear wave elastography of the prostate, by comparing it with the histopathological exam of the prostate biopsy specimens. (2) Material and methods: We have conducted a prospective study on 356 patients undergoing transrectal ultrasound-guided prostate biopsy, for suspicion of prostate cancer. All patients were examined using bi-dimensional shear wave ultrasonography, which was followed by standard systematic transrectal prostate biopsy. The mean elasticity of each of the twelve systematic biopsy target zones was recorded and compared with the pathological examination results in all patients. The final dataset has included data from 223 patients with confirmed prostate cancer. Three machine learning classification algorithms (logistic regression, a decision tree classifier and a dense neural network) were implemented and their performance in predicting the positive lesions from the elastographic data measurements was assessed. (3) Results: The area under the curve (AUC) results were as follows: for logistic regression—0.88, for decision tree classifier—0.78 and for the dense neural network—0.94. Further use of an upsampling strategy for the training set of the neural network slightly improved its performance. Using an ensemble learning model, which combined the three machine learning models, we have obtained a final accuracy of 98%. (4) Conclusions: Bi-dimensional shear wave elastography could be very useful in predicting prostate cancer lesions, especially when it benefits from the computational power of artificial intelligence and machine learning algorithms.
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16
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Apfelbeck M, Clevert DA, Stief CG, Chaloupka M. [Sonography of the prostate : Relevance for urologists in daily clinical routine]. Urologe A 2022; 61:365-373. [PMID: 35244746 DOI: 10.1007/s00120-022-01767-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/14/2022] [Indexed: 11/25/2022]
Abstract
Despite the continuous technical progress regarding the transrectal ultrasonography of the prostate (TRUS) and its successful use in combination with magnetic resonance imaging (MRI) in MRI-targeted biopsy, there is no radiologic modality being able to rule out clinically significant prostate cancer without the need of systematic biopsy. In the past few years, TRUS regained more attention due to the development of high frequency ultrasound as well as the combination of different ultrasonic modalities like shear wave elastography and contrast-enhanced sonography (CEUS). Currently, multiparametric MRI (mpMRI)-targeted biopsy shows the best results concerning detection rates, sensitivity and specificity of clinically significant prostate cancer compared to systematic biopsy. In the future, transperineal biopsy is probably going to increasingly replace the transrectal biopsy approach. For both approaches, transrectal ultrasonography is necessary to display the prostate and to detect suspicious lesions. Therefore future improvements in transrectal ultrasonography can be expected.
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Affiliation(s)
- Maria Apfelbeck
- Urologische Klinik und Poliklinik des LMU Klinikums, Campus Großhadern, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377, München, Deutschland.
| | - Dirk-André Clevert
- Klinik und Poliklinik für Radiologie des LMU Klinikums, Campus Großhadern, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377, München, Deutschland
| | - Christian G Stief
- Urologische Klinik und Poliklinik des LMU Klinikums, Campus Großhadern, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377, München, Deutschland
| | - Michael Chaloupka
- Urologische Klinik und Poliklinik des LMU Klinikums, Campus Großhadern, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377, München, Deutschland
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17
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Jager A, Vilanova JC, Michi M, Wijkstra H, Oddens JR. The challenge of prostate biopsy guidance in the era of mpMRI detected lesion: ultrasound-guided versus in-bore biopsy. Br J Radiol 2022; 95:20210363. [PMID: 34324383 PMCID: PMC8978231 DOI: 10.1259/bjr.20210363] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
The current recommendation in patients with a clinical suspicion for prostate cancer is to perform systematic biopsies extended with targeted biopsies, depending on mpMRI results. Following a positive mpMRI [i.e. Prostate Imaging Reporting and Data System (PI-RADS) ≥3], three targeted biopsy approaches can be performed: visual registration of the MRI images with real-time ultrasound imaging; software-assisted fusion of the MRI images and real-time ultrasound images, and in-bore biopsy within the MR scanner. This collaborative review discusses the advantages and disadvantages of each targeting approach and elaborates on future developments. Cancer detection rates seem to mostly depend on practitioner experience and selection criteria (biopsy naïve, previous negative biopsy, prostate-specific antigen (PSA) selection criteria, presence of a lesion on MRI), and to a lesser extent dependent on biopsy technique. There is no clear consensus on the optimal targeting approach. The choice of technique depends on local experience and availability of equipment, individual patient characteristics, and onsite cost-benefit analysis. Innovations in imaging techniques and software-based algorithms may lead to further improvements in this field.
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Affiliation(s)
- Auke Jager
- Department of Urology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Joan C Vilanova
- Department of Radiology, Clinica Girona, Diagnostic Imaging Institute (IDI), University of Girona, Girona, Spain
| | - Massimo Michi
- Lab of Biomedical Diagnostics, Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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Kaneko M, Lenon MSL, Storino Ramacciotti L, Medina LG, Sayegh AS, La Riva A, Perez LC, Ghoreifi A, Lizana M, Jadvar DS, Lebastchi AH, Cacciamani GE, Abreu AL. Multiparametric ultrasound of prostate: role in prostate cancer diagnosis. Ther Adv Urol 2022; 14:17562872221145625. [PMID: 36601020 PMCID: PMC9806443 DOI: 10.1177/17562872221145625] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 11/25/2022] [Indexed: 12/28/2022] Open
Abstract
Recent advances in ultrasonography (US) technology established modalities, such as Doppler-US, HistoScanning, contrast-enhanced ultrasonography (CEUS), elastography, and micro-ultrasound. The early results of these US modalities have been promising, although there are limitations including the need for specialized equipment, inconsistent results, lack of standardizations, and external validation. In this review, we identified studies evaluating multiparametric ultrasonography (mpUS), the combination of multiple US modalities, for prostate cancer (PCa) diagnosis. In the past 5 years, a growing number of studies have shown that use of mpUS resulted in high PCa and clinically significant prostate cancer (CSPCa) detection performance using radical prostatectomy histology as the reference standard. Recent studies have demonstrated the role mpUS in improving detection of CSPCa and guidance for prostate biopsy and therapy. Furthermore, some aspects including lower costs, real-time imaging, applicability for some patients who have contraindication for magnetic resonance imaging (MRI) and availability in the office setting are clear advantages of mpUS. Interobserver agreement of mpUS was overall low; however, this limitation can be improved using standardized and objective evaluation systems such as the machine learning model. Whether mpUS outperforms MRI is unclear. Multicenter randomized controlled trials directly comparing mpUS and multiparametric MRI are warranted.
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Affiliation(s)
- Masatomo Kaneko
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Urology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Maria Sarah L. Lenon
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Lorenzo Storino Ramacciotti
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Luis G. Medina
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Aref S. Sayegh
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Anibal La Riva
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Laura C. Perez
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Alireza Ghoreifi
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Maria Lizana
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Donya S. Jadvar
- Dornsife School of Letters and Science, University of Southern California, Los Angeles, CA, USA
| | - Amir H. Lebastchi
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Giovanni E. Cacciamani
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andre Luis Abreu
- Center for Image-Guided Surgery, Focal Therapy, and Artificial Intelligence for Prostate Cancer, USC Institute of Urology and Catherine & Joseph Aresty
- Department of Urology, Keck School of Medicine, University of Southern California, 1441 Eastlake Ave, Suite 7416, Los Angeles, CA 90089, USADepartment of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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