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Mikaeili M, Bilge HŞ. Trajectory estimation of ultrasound images based on convolutional neural network. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2022.103965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Correlation of in-vivo imaging with histopathology: A review. Eur J Radiol 2021; 144:109964. [PMID: 34619617 DOI: 10.1016/j.ejrad.2021.109964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 08/26/2021] [Accepted: 09/17/2021] [Indexed: 11/21/2022]
Abstract
Despite tremendous advancements in in vivo imaging modalities, there remains substantial uncertainty with respect to tumor delineation on in these images. Histopathology remains the gold standard for determining the extent of malignancy, with in vivo imaging to histopathologic correlation enabling spatial comparisons. In this review, the steps necessary for successful imaging to histopathologic correlation are described, including in vivo imaging, resection, fixation, specimen sectioning (sectioning technique, securing technique, orientation matching, slice matching), microtome sectioning and staining, correlation (including image registration) and performance evaluation. The techniques used for each of these steps are also discussed. Hundreds of publications from the past 20 years were surveyed, and 62 selected for detailed analysis. For these 62 publications, each stage of the correlative pathology process (and the sub-steps of specimen sectioning) are listed. A statistical analysis was conducted based on 19 studies that reported target registration error as their performance metric. While some methods promise greater accuracy, they may be expensive. Due to the complexity of the processes involved, correlative pathology studies generally include a small number of subjects, which hinders advanced developments in this field.
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Applegate CC, Lowerison MR, Hambley E, Song P, Wallig MA, Erdman JW. Dietary tomato inhibits angiogenesis in TRAMP prostate cancer but is not protective with a Western-style diet in this pilot study. Sci Rep 2021; 11:18548. [PMID: 34535690 PMCID: PMC8448771 DOI: 10.1038/s41598-021-97539-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 08/20/2021] [Indexed: 12/09/2022] Open
Abstract
Prostate cancer (PCa) remains the second most diagnosed cancer worldwide. Higher body weight is associated with chronic inflammation, increased angiogenesis, and treatment-resistant tumor phenotypes. Dietary tomato reduces PCa risk, which may be due to tomato inhibition of angiogenesis and disruption of androgen signaling. This pilot study investigated the interplay between tomato powder (TP), incorporated into control (CON) and obesogenic (OB) diets, and PCa tumor growth and blood perfusion over time in a transgenic model of PCa (TRAMP). Ultrasound microvessel imaging (UMI) results showed good agreement with gold-standard immunohistochemistry quantification of endothelial cell density, indicating that this technique can be applied to non-invasively monitor tumor blood perfusion in vivo. Greater body weight was positively associated with tumor growth. We also found that TP significantly inhibited prostate tumor angiogenesis but that this inhibition differentially affected measured outcomes depending on CON or OB diets. TP led to reduced tumor growth, intratumoral inflammation, and intratumoral androgen-regulated gene expression (srd5a1, srd5a2) when incorporated with the CON diet but greater tumor growth and intratumoral gene expression when incorporated with the OB diet. Results from this study show that protective benefits from dietary tomato are lost, or may become deleterious, when combined with a Western-style diet.
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Affiliation(s)
- Catherine C Applegate
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
| | - Matthew R Lowerison
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Emma Hambley
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Division of Biology, Kansas State University, Manhattan, KS, 66506, USA
| | - Pengfei Song
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Matthew A Wallig
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - John W Erdman
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
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Registration of Magnetic Resonance Tomography (MRT) Data with a Low Frequency Adaption of Fourier-Mellin-SOFT (LF-FMS). SENSORS 2021; 21:s21082581. [PMID: 33917045 PMCID: PMC8067751 DOI: 10.3390/s21082581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 03/26/2021] [Accepted: 03/30/2021] [Indexed: 11/27/2022]
Abstract
Fourier-Mellin-SOFT (FMS) is a rigid 3D registration method, which allows the robust registration of 3 degrees-of-freedom (dof) rotation, 1-dof scale, and 3-dof translation between scans on discrete grids. FMS is based on a spectral decomposition of these 7-dof. This complete spectral representation of the input data enables an adaption to certain frequency ranges. This special property is used here to focus on relevant mutual 3D information between bone structures with a Low Frequency adaptation of FMS (LF-FMS), that is, it is utilized for matching and concurrently determining corresponding transformation parameters. This process is applied on a set of Magnetic Resonance Tomography (MRT) data representing the hand region, in particular the carpal bone area, in a sequence of different hand positions. This data set is available for different probands, which allows a comparison of resulting parameter plots and furthermore matching in between bone structures.
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Contrast-enhanced ultrasound with dispersion analysis for the localization of prostate cancer: correlation with radical prostatectomy specimens. World J Urol 2020; 38:2811-2818. [PMID: 32078707 DOI: 10.1007/s00345-020-03103-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 01/21/2020] [Indexed: 10/25/2022] Open
Abstract
PURPOSE To determine the value of two-dimensional (2D) contrast-enhanced ultrasound (CEUS) imaging and the additional value of contrast ultrasound dispersion imaging (CUDI) for the localization of clinically significant prostate cancer (csPCa). METHODS In this multicentre study, subjects scheduled for a radical prostatectomy underwent 2D CEUS imaging preoperatively. CUDI maps were generated from the CEUS recordings. Both CEUS recordings and CUDI maps were scored on the likelihood of presenting csPCa (any Gleason ≥ 4 + 3 and Gleason 3 + 4 larger than 0.5 mL) by five observers and compared to radical prostatectomy histopathology. An automated three-dimensional (3D) fusion protocol was used to match imaging with histopathology. Receiver operator curve (ROC) analysis was performed per observer and imaging modality. RESULTS 133 of 216 (62%) patients were included in the final analysis. Average area under the ROC for all five readers for CEUS, CUDI and the combination was 0.78, 0.79 and 0.78, respectively. This yields a sensitivity and specificity of 81 and 64% for CEUS, 83 and 56% for CUDI and 83 and 55% for the combination. Interobserver agreement for CEUS, CUDI and the combination showed kappa values of 0.20, 0.18 and 0.18 respectively. CONCLUSION The sensitivity and specificity of 2D CEUS and CUDI for csPCa localization are moderate. Despite compressing CEUS in one image, CUDI showed a similar performance to 2D CEUS. With a sensitivity of 83% at cutoff point 3, it could become a useful imaging procedure, especially with 4D acquisition, improved quantification and combination with other US imaging techniques such as elastography.
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Xing Q, Chitnis P, Sikdar S, Alshiek J, Shobeiri SA, Wei Q. M3VR-A multi-stage, multi-resolution, and multi-volumes-of-interest volume registration method applied to 3D endovaginal ultrasound. PLoS One 2019; 14:e0224583. [PMID: 31751356 PMCID: PMC6872108 DOI: 10.1371/journal.pone.0224583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 10/16/2019] [Indexed: 11/24/2022] Open
Abstract
Heterogeneity of echo-texture and lack of sharply delineated tissue boundaries in diagnostic ultrasound images make three-dimensional (3D) registration challenging, especially when the volumes to be registered are considerably different due to local changes. We implemented a novel computational method that optimally registers volumetric ultrasound image data containing significant and local anatomical differences. It is A Multi-stage, Multi-resolution, and Multi-volumes-of-interest Volume Registration Method. A single region registration is optimized first for a close initial alignment to avoid convergence to a locally optimal solution. Multiple sub-volumes of interest can then be selected as target alignment regions to achieve confident consistency across the volume. Finally, a multi-resolution rigid registration is performed on these sub-volumes associated with different weights in the cost function. We applied the method on 3D endovaginal ultrasound image data acquired from patients during biopsy procedure of the pelvic floor muscle. Systematic assessment of our proposed method through cross validation demonstrated its accuracy and robustness. The algorithm can also be applied on medical imaging data of other modalities for which the traditional rigid registration methods would fail.
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Affiliation(s)
- Qi Xing
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
- The School of Information Science and Technology, Southwest Jiaotong University, Sichuan, China
| | - Parag Chitnis
- Department of Bioengineering, George Mason University, Fairfax, Virginia, United States of America
| | - Siddhartha Sikdar
- Department of Bioengineering, George Mason University, Fairfax, Virginia, United States of America
| | - Jonia Alshiek
- Department of Obstetrics & Gynecology, INOVA Health System, Falls Church, Virginia, United States of America
| | - S. Abbas Shobeiri
- Department of Bioengineering, George Mason University, Fairfax, Virginia, United States of America
- Department of Obstetrics & Gynecology, INOVA Health System, Falls Church, Virginia, United States of America
| | - Qi Wei
- Department of Bioengineering, George Mason University, Fairfax, Virginia, United States of America
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Wildeboer RR, Van Sloun RJG, Schalk SG, Mannaerts CK, Van Der Linden JC, Huang P, Wijkstra H, Mischi M. Convective-Dispersion Modeling in 3D Contrast-Ultrasound Imaging for the Localization of Prostate Cancer. IEEE TRANSACTIONS ON MEDICAL IMAGING 2018; 37:2593-2602. [PMID: 29993539 DOI: 10.1109/tmi.2018.2843396] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Despite being the solid tumor with the highest incidence in western men, prostate cancer (PCa) still lacks reliable imaging solutions that can overcome the need for systematic biopsies. Dynamic contrast-enhanced ultrasound imaging (DCE-US) allows us to quantitatively characterize the vascular bed in the prostate, due to its ability to visualize an intravenously administered bolus of contrast agents. Previous research has demonstrated that DCE-US parameters related to the vascular architecture are useful markers for the localization of PCa lesions. In this paper, we propose a novel method to assess the convective dispersion (D) and velocity (v) of the contrast bolus spreading through the prostate from three-dimensional (3D) DCE-US recordings. By assuming that D and v are locally constant, we solve the convective-dispersion equation by minimizing the corresponding regularized least-squares problem. 3D multiparametric maps of D and v were compared with 3D histopathology retrieved from the radical prostatectomy specimens of six patients. With a pixel-wise area under the receiver operating characteristic curve of 0.72 and 0.80, respectively, the method shows diagnostic value for the localization of PCa.
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Multiparametric ultrasound: evaluation of greyscale, shear wave elastography and contrast-enhanced ultrasound for prostate cancer detection and localization in correlation to radical prostatectomy specimens. BMC Urol 2018; 18:98. [PMID: 30409150 PMCID: PMC6225621 DOI: 10.1186/s12894-018-0409-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 10/17/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The diagnostic pathway for prostate cancer (PCa) is advancing towards an imaging-driven approach. Multiparametric magnetic resonance imaging, although increasingly used, has not shown sufficient accuracy to replace biopsy for now. The introduction of new ultrasound (US) modalities, such as quantitative contrast-enhanced US (CEUS) and shear wave elastography (SWE), shows promise but is not evidenced by sufficient high quality studies, especially for the combination of different US modalities. The primary objective of this study is to determine the individual and complementary diagnostic performance of greyscale US (GS), SWE, CEUS and their combination, multiparametric ultrasound (mpUS), for the detection and localization of PCa by comparison with corresponding histopathology. METHODS/DESIGN In this prospective clinical trial, US imaging consisting of GS, SWE and CEUS with quantitative mapping on 3 prostate imaging planes (base, mid and apex) will be performed in 50 patients with biopsy-proven PCa before planned radical prostatectomy using a clinical ultrasound scanner. All US imaging will be evaluated by US readers, scoring the four quadrants of each imaging plane for the likelihood of significant PCa based on a 1 to 5 Likert Scale. Following resection, PCa tumour foci will be identified, graded and attributed to the imaging-derived quadrants in each prostate plane for all prostatectomy specimens. Primary outcome measure will be the sensitivity, specificity, negative predictive value and positive predictive value of each US modality and mpUS to detect and localize significant PCa evaluated for different Likert Scale thresholds using receiver operating characteristics curve analyses. DISCUSSION In the evaluation of new PCa imaging modalities, a structured comparison with gold standard radical prostatectomy specimens is essential as first step. This trial is the first to combine the most promising ultrasound modalities into mpUS. It complies with the IDEAL stage 2b recommendations and will be an important step towards the evaluation of mpUS as a possible option for accurate detection and localization of PCa. TRIAL REGISTRATION The study protocol for multiparametric ultrasound was prospectively registered on Clinicaltrials.gov on 14 March 2017 with the registry name 'Multiparametric Ultrasound-Study for the Detection of Prostate Cancer' and trial registration number NCT03091231.
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Accurate validation of ultrasound imaging of prostate cancer: a review of challenges in registration of imaging and histopathology. J Ultrasound 2018; 21:197-207. [PMID: 30062440 PMCID: PMC6113189 DOI: 10.1007/s40477-018-0311-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 07/11/2018] [Indexed: 01/20/2023] Open
Abstract
As the development of modalities for prostate cancer (PCa) imaging advances, the challenge of accurate registration between images and histopathologic ground truth becomes more pressing. Localization of PCa, rather than detection, requires a pixel-to-pixel validation of imaging based on histopathology after radical prostatectomy. Such a registration procedure is challenging for ultrasound modalities; not only the deformations of the prostate after resection have to be taken into account, but also the deformation due to the employed transrectal probe and the mismatch in orientation between imaging planes and pathology slices. In this work, we review the latest techniques to facilitate accurate validation of PCa localization in ultrasound imaging studies and extrapolate a general strategy for implementation of a registration procedure.
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Ogunleke A, Recur B, Balacey H, Chen HH, Delugin M, Hwu Y, Javerzat S, Petibois C. 3D chemical imaging of the brain using quantitative IR spectro-microscopy. Chem Sci 2018; 9:189-198. [PMID: 29629087 PMCID: PMC5869290 DOI: 10.1039/c7sc03306k] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2017] [Accepted: 10/13/2017] [Indexed: 01/14/2023] Open
Abstract
Three-dimensional (3D) histology is the next frontier for modern anatomo-pathology. Characterizing abnormal parameters in a tissue is essential to understand the rationale of pathology development. However, there is no analytical technique, in vivo or histological, that is able to discover such abnormal features and provide a 3D distribution at microscopic resolution. Here, we introduce a unique high-throughput infrared (IR) microscopy method that combines automated image correction and subsequent spectral data analysis for 3D-IR image reconstruction. We performed spectral analysis of a complete organ for a small animal model, a mouse brain with an implanted glioma tumor. The 3D-IR image is reconstructed from 370 consecutive tissue sections and corrected using the X-ray tomogram of the organ for an accurate quantitative analysis of the chemical content. A 3D matrix of 89 × 106 IR spectra is generated, allowing us to separate the tumor mass from healthy brain tissues based on various anatomical, chemical, and metabolic parameters. We demonstrate that quantitative metabolic parameters can be extracted from the IR spectra for the characterization of the brain vs. tumor metabolism (assessing the Warburg effect in tumors). Our method can be further exploited by searching for the whole spectral profile, discriminating tumor vs. healthy tissue in a non-supervised manner, which we call 'spectromics'.
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Affiliation(s)
- Abiodun Ogunleke
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Benoit Recur
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Hugo Balacey
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Hsiang-Hsin Chen
- Academia Sinica , Institute of Physics , 128 Sec. 2, Academia Rd., Nankang , Taipei 11529 , Taiwan , Republic of China
| | - Maylis Delugin
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Yeukuang Hwu
- Academia Sinica , Institute of Physics , 128 Sec. 2, Academia Rd., Nankang , Taipei 11529 , Taiwan , Republic of China
| | - Sophie Javerzat
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
| | - Cyril Petibois
- University of Bordeaux , Inserm U1029 LAMC , Allée Geoffroy Saint-Hilaire Bat. B2, F33600 Pessac , France . ;
- Academia Sinica , Institute of Physics , 128 Sec. 2, Academia Rd., Nankang , Taipei 11529 , Taiwan , Republic of China
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First-in-Human Ultrasound Molecular Imaging With a VEGFR2-Specific Ultrasound Molecular Contrast Agent (BR55) in Prostate Cancer. Invest Radiol 2017; 52:419-427. [DOI: 10.1097/rli.0000000000000362] [Citation(s) in RCA: 98] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Wildeboer RR, Schalk SG, Demi L, Wijkstra H, Mischi M. Three-dimensional histopathological reconstruction as a reliable ground truth for prostate cancer studies. Biomed Phys Eng Express 2017. [DOI: 10.1088/2057-1976/aa7073] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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van Sloun RJG, Demi L, Postema AW, de la Rosette JJMCH, Wijkstra H, Mischi M. Ultrasound-contrast-agent dispersion and velocity imaging for prostate cancer localization. Med Image Anal 2017; 35:610-619. [DOI: 10.1016/j.media.2016.09.010] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 07/21/2016] [Accepted: 09/26/2016] [Indexed: 11/25/2022]
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