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Rodney J Landreneau - One of the best experts on this subject based on the ideXlab platform.
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general thoracic surgery lung Cancerpreoperative 3 dimensional computed tomography lung reconstruction before anatomic segmentectomy or lobectomy for stage i non small cell lung Cancer
The Journal of Thoracic and Cardiovascular Surgery, 2015Co-Authors: Ernest G Chan, James R Landreneau, Matthew J Schuchert, David D Odell, James D Luketich, Rodney J LandreneauAbstract:Objectives Accurate Cancer Localization and negative resection margins are necessary for successful segmentectomy. In this study, we evaluate a newly developed software package that permits automated segmentation of the pulmonary parenchyma, allowing 3-dimensional assessment of tumor size, location, and estimates of surgical margins.
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preoperative 3 dimensional computed tomography lung reconstruction before anatomic segmentectomy or lobectomy for stage i non small cell lung Cancer
The Journal of Thoracic and Cardiovascular Surgery, 2015Co-Authors: Ernest G Chan, James R Landreneau, Matthew J Schuchert, David D Odell, James D Luketich, Rodney J LandreneauAbstract:Abstract Objectives Accurate Cancer Localization and negative resection margins are necessary for successful segmentectomy. In this study, we evaluate a newly developed software package that permits automated segmentation of the pulmonary parenchyma, allowing 3-dimensional assessment of tumor size, location, and estimates of surgical margins. Methods A pilot study using a newly developed 3-dimensional computed tomography analytic software package was performed to retrospectively evaluate preoperative computed tomography images of patients who underwent segmentectomy (n = 36) or lobectomy (n = 15) for stage 1 non–small cell lung Cancer. The software accomplishes an automated reconstruction of anatomic pulmonary segments of the lung based on bronchial arborization. Estimates of anticipated surgical margins and pulmonary segmental volume were made on the basis of 3-dimensional reconstruction. Results Autosegmentation was achieved in 72.7% (32/44) of preoperative computed tomography images with slice thicknesses of 3 mm or less. Reasons for segmentation failure included local severe emphysema or pneumonitis, and lower computed tomography resolution. Tumor segmental Localization was achieved in all autosegmented studies. The 3-dimensional computed tomography analysis provided a positive predictive value of 87% in predicting a marginal clearance greater than 1 cm and a 75% positive predictive value in predicting a margin to tumor diameter ratio greater than 1 in relation to the surgical pathology assessment. Conclusions This preoperative 3-dimensional computed tomography analysis of segmental anatomy can confirm the tumor location within an anatomic segment and aid in predicting surgical margins. This 3-dimensional computed tomography information may assist in the preoperative assessment regarding the suitability of segmentectomy for peripheral lung Cancers.
Jelle O. Barentsz - One of the best experts on this subject based on the ideXlab platform.
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prostate Cancer multiparametric mr imaging for detection Localization and staging
Radiology, 2011Co-Authors: Caroline M A Hoeks, Stijn W. T. P. J. Heijmink, Henkjan J Huisman, Tom W J Scheenen, Jelle O. Barentsz, Thomas Hambrock, Derya Yakar, Diederik M Somford, Pieter C Vos, Inge M Van OortAbstract:This review presents the current state of the art regarding multiparametric magnetic resonance (MR) imaging of prostate Cancer. Technical requirements and clinical indications for the use of multiparametric MR imaging in detection, Localization, characterization, staging, biopsy guidance, and active surveillance of prostate Cancer are discussed. Although reported accuracies of the separate and combined multiparametric MR imaging techniques vary for diverse clinical prostate Cancer indications, multiparametric MR imaging of the prostate has shown promising results and may be of additional value in prostate Cancer Localization and local staging. Consensus on which technical approaches (field strengths, sequences, use of an endorectal coil) and combination of multiparametric MR imaging techniques should be used for specific clinical indications remains a challenge. Because guidelines are currently lacking, suggestions for a general minimal protocol for multiparametric MR imaging of the prostate based on the literature and the authors' experience are presented. Computer programs that allow evaluation of the various components of a multiparametric MR imaging examination in one view should be developed. In this way, an integrated interpretation of anatomic and functional MR imaging techniques in a multiparametric MR imaging examination is possible. Education and experience of specialist radiologists are essential for correct interpretation of multiparametric prostate MR imaging findings. Supportive techniques, such as computer-aided diagnosis are needed to obtain a fast, cost-effective, easy, and more reproducible prostate Cancer diagnosis out of more and more complex multiparametric MR imaging data.
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prostate Cancer body array versus endorectal coil mr imaging at 3 t comparison of image quality Localization and staging performance
Radiology, 2007Co-Authors: Stijn W. T. P. J. Heijmink, Jurgen J Futterer, Henkjan J Huisman, Tom W J Scheenen, Alfred J Witjes, Thomas Hambrock, Satoru Takahashi, Ben C Knipscheer, Lambertus A Kiemeney, Jelle O. BarentszAbstract:PURPOSE: To prospectively compare image quality and accuracy of prostate Cancer Localization and staging with body-array coil (BAC) versus endorectal coil (ERC) T2-weighted magnetic resonance (MR) imaging at 3 T, with histopathologic findings as the reference standard. MATERIALS AND METHODS: After institutional review board approval and written informed consent, 46 men underwent 3-T T2-weighted MR imaging with a BAC (voxel size, 0.43 x 0.43 x 4.00 mm) and an ERC (voxel size, 0.26 x 0.26 x 2.50 mm) before radical prostatectomy. Four radiologists independently evaluated data sets obtained with the BAC and ERC separately. Ten image quality characteristics related to prostate Cancer Localization and staging were assigned scores. Prostate Cancer presence was recorded with a five-point probability scale in each of 14 segments that included the whole prostate. Disease stage was classified as organ-confined or locally advanced with a five-point probability scale. Whole-mount-section histopathologic examination was the reference standard. Areas under the receiver operating characteristic curve (AUCs) and diagnostic performance parameters were determined. A difference with a P value of less than .05 was considered significant. RESULTS: Forty-six patients (mean age, 61 years) were included for analysis. Significantly more motion artifacts were present with ERC imaging (P<.001). All other image quality characteristics improved significantly (P<.001) with ERC imaging. With ERC imaging, the AUC for Localization of prostate Cancer was significantly increased from 0.62 to 0.68 (P<.001). ERC imaging significantly increased the AUCs for staging, and sensitivity for detection of locally advanced disease by experienced readers was increased from 7% (one of 15) to a range of 73% (11 of 15) to 80% (12 of 15) (P<.05), whereas a high specificity of 97% (30 of 31) to 100% (31 of 31) was maintained. Extracapsular extension as small as 0.5 mm at histopathologic examination could be accurately detected only with ERC imaging. CONCLUSION: Image quality and Localization improved significantly with ERC imaging compared with BAC imaging. For experienced radiologists, the staging performance was significantly better with ERC imaging.
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prostate Cancer Localization with dynamic contrast enhanced mr imaging and proton mr spectroscopic imaging
Radiology, 2006Co-Authors: Jurgen J Futterer, Stijn W. T. P. J. Heijmink, Jeroen Veltman, Henkjan J Huisman, Paul F M Krabbe, Tom W J Scheenen, Alfred J Witjes, Arend Heerschap, Jelle O. BarentszAbstract:Purpose: To prospectively determine the accuracies of T2-weighted magnetic resonance (MR) imaging, dynamic contrast material–enhanced MR imaging, and quantitative three-dimensional (3D) proton MR spectroscopic imaging of the entire prostate for prostate Cancer Localization, with whole-mount histopathologic section findings as the reference standard. Materials and Methods: This study was approved by the institutional review board, and informed consent was obtained from all patients. Thirty-four consecutive men with a mean age of 60 years and a mean prostate-specific antigen level of 8 ng/mL were examined. The median biopsy Gleason score was 6. T2-weighted MR imaging, dynamic contrast-enhanced MR imaging, and 3D MR spectroscopic imaging were performed, and on the basis of the image data, two readers with different levels of experience recorded the location of the suspicious peripheral zone and central gland tumor nodules on each of 14 standardized regions of interest (ROIs) in the prostate. The degree of di...
Massimo Mischi - One of the best experts on this subject based on the ideXlab platform.
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automated multiparametric Localization of prostate Cancer based on b mode shear wave elastography and contrast enhanced ultrasound radiomics
European Radiology, 2020Co-Authors: R R Wildeboer, Hessel Wijkstra, Ruud J G Van Sloun, Christophe K Mannaerts, Lars Budaus, Derya Tilki, Georg Salomon, Massimo MischiAbstract:The aim of this study was to assess the potential of machine learning based on B-mode, shear-wave elastography (SWE), and dynamic contrast-enhanced ultrasound (DCE-US) radiomics for the Localization of prostate Cancer (PCa) lesions using transrectal ultrasound. This study was approved by the institutional review board and comprised 50 men with biopsy-confirmed PCa that were referred for radical prostatectomy. Prior to surgery, patients received transrectal ultrasound (TRUS), SWE, and DCE-US for three imaging planes. The images were automatically segmented and registered. First, model-based features related to contrast perfusion and dispersion were extracted from the DCE-US videos. Subsequently, radiomics were retrieved from all modalities. Machine learning was applied through a random forest classification algorithm, using the co-registered histopathology from the radical prostatectomy specimens as a reference to draw benign and malignant regions of interest. To avoid overfitting, the performance of the multiparametric classifier was assessed through leave-one-patient-out cross-validation. The multiparametric classifier reached a region-wise area under the receiver operating characteristics curve (ROC-AUC) of 0.75 and 0.90 for PCa and Gleason > 3 + 4 significant PCa, respectively, thereby outperforming the best-performing single parameter (i.e., contrast velocity) yielding ROC-AUCs of 0.69 and 0.76, respectively. Machine learning revealed that combinations between perfusion-, dispersion-, and elasticity-related features were favored. In this paper, technical feasibility of multiparametric machine learning to improve upon single US modalities for the Localization of PCa has been demonstrated. Extended datasets for training and testing may establish the clinical value of automatic multiparametric US classification in the early diagnosis of PCa. • Combination of B-mode ultrasound, shear-wave elastography, and contrast ultrasound radiomics through machine learning is technically feasible. • Multiparametric ultrasound demonstrated a higher prostate Cancer Localization ability than single ultrasound modalities. • Computer-aided multiparametric ultrasound could help clinicians in biopsy targeting.
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imaging of the dispersion coefficient of ultrasound contrast agents by wiener system identification for prostate Cancer Localization
Internaltional Ultrasonics Symposium, 2015Co-Authors: Ruud J G Van Sloun, Hessel Wijkstra, Libertario Demi, Arnoud W Postema, Jean J M C H De La Rosette, Massimo MischiAbstract:Prostate Cancer (PCa) is the most prevalent form of Cancer in Western men; however, reliable tools for PCa detection and Localization are lacking. Dynamic Contrast Enhanced Ultrasound (DCE-US) is a diagnostic tool that allows analysis of vascularization, by imaging an intravenously injected microbubble bolus. The Localization of angiogenic vascularization associated with the development of tumors is of particular interest. Recently, methods aiming at estimating contrast dispersion to localize angiogenesis have shown promise. However, independent estimation of dispersion was not possible due to the ambiguity between dispersive and convective processes. Therefore, in this study we propose a new method that considers the vascular network as a dynamic linear system, whose impulse response can be locally identified by solving the Wiener-Hopf equations. To facilitate characterization, model-based parameter estimation is employed, permitting the determination of the apparent dispersion coefficient (D), velocity (v), and Peclet number (Pe) of the system. A preliminary clinical evaluation using data recorded from 10 patients shows that the proposed method can be applied effectively to DCE-US, and is able to locally characterize the hemodynamics in the prostate.
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Contrast-ultrasound dispersion imaging of Cancer neovascularization by mutual-information analysis
2014 IEEE International Ultrasonics Symposium, 2014Co-Authors: Massimo Mischi, Maarten Petrus Joseph Kuenen, Libertario Demi, Nabil Bouhouch, Arnoud Postema, Jean J. De La Rosette, Tjalling J. Tjalkens, Hessel WijkstraAbstract:Being an established marker for Cancer growth, neovascularization is probed by several approaches with the aim of Cancer imaging. Recently, analysis of the dispersion kinetics of ultrasound contrast agents (UCAs) has been proposed as a promising approach for localizing neovascularization in prostate Cancer. Determined by multipath trajectories through the microvasculature, dispersion enables characterization of the microvascular architecture and, therefore, Localization of Cancer neovascularization. Analysis of the spatiotemporal similarity among indicator dilution curves (IDCs) measured at each pixel by dynamic contrast-enhanced ultrasound imaging has been proposed to assess the local dispersion kinetics of UCAs. Only linear similarity measures, such as temporal correlation or spectral coherence, have been used up until now. Here we investigate the use of nonlinear similarity measures by estimation of the statistical dependency between IDCs. In particular, dispersion maps are generated by estimation of the mutual information between IDCs. The method is tested for prostate Cancer Localization and the results compared with the histology results in 15 patients referred for radical prostatectomy because of biopsy-proven prostate Cancer. With sensitivity and specificity equal to 84% and 85%, respectively, and receiver operating characteristic curve area equal to 0.92, our results outperformed those obtained by any other parameter, motivating further validation with a larger dataset and with other types of Cancer.
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contrast ultrasound dispersion imaging for prostate Cancer Localization by improved spatiotemporal similarity analysis
Ultrasound in Medicine and Biology, 2013Co-Authors: Maarten Petrus Joseph Kuenen, Hessel Wijkstra, T Tamerlan A Saidov, Massimo MischiAbstract:Angiogenesis plays a major role in prostate Cancer growth. Despite extensive research on blood perfusion imaging aimed at angiogenesis detection, the diagnosis of prostate Cancer still requires systematic biopsies. This may be due to the complex relationship between angiogenesis and microvascular perfusion. Analysis of ultrasound-contrast-agent dispersion kinetics, determined by multipath trajectories in the microcirculation, may provide better characterization of the microvascular architecture. We propose the physical rationale for dispersion estimation by an existing spatiotemporal similarity analysis. After an intravenous ultrasound-contrast-agent bolus injection, dispersion is estimated by coherence analysis among time-intensity curves measured at neighbor pixels. The accuracy of the method is increased by time-domain windowing and anisotropic spatial filtering for speckle regularization. The results in 12 patient data sets indicated superior agreement with histology (receiver operating characteristic curve area = 0.88) compared with those obtained by reported perfusion and dispersion analyses, providing a valuable contribution to prostate Cancer Localization.
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angiogenesis imaging by spatiotemporal analysis of ultrasound contrast agent dispersion kinetics
IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, 2012Co-Authors: Massimo Mischi, Maarten Petrus Joseph Kuenen, Hessel WijkstraAbstract:The key role of angiogenesis in Cancer growth has motivated extensive research with the goal of noninvasive Cancer detection by blood perfusion imaging. However, the results are still limited and the diagnosis of major forms of Cancer, such as prostate Cancer, are currently based on systematic biopsies. The difficulty in the detection of angiogenesis partly resides in a complex relationship between angiogenesis and perfusion. This may be overcome by analysis of the dispersion kinetics of ultrasound contrast agents. Determined by multipath trajectories through the microvasculature, dispersion permits a better characterization of the microvascular architecture and, therefore, more accurate detection of angiogenesis. In this paper, a novel dispersion analysis method is proposed for prostate Cancer Localization. An ultrasound contrast agent bolus is injected intravenously. Spatiotemporal analysis of the concentration evolution measured at different pixels in the prostate is used to assess the local dispersion kinetics of the injected agent. In particular, based on simulations of the convective diffusion equation, the similarity between the concentration evolutions at neighbor pixels is the adopted dispersion measure. Six measurements in patients, compared with the histology, provided a receiver operating characteristic curve integral equal to 0.87. This result was superior to that obtained by the previous approaches reported in the literature.
Hessel Wijkstra - One of the best experts on this subject based on the ideXlab platform.
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automated multiparametric Localization of prostate Cancer based on b mode shear wave elastography and contrast enhanced ultrasound radiomics
European Radiology, 2020Co-Authors: R R Wildeboer, Hessel Wijkstra, Ruud J G Van Sloun, Christophe K Mannaerts, Lars Budaus, Derya Tilki, Georg Salomon, Massimo MischiAbstract:The aim of this study was to assess the potential of machine learning based on B-mode, shear-wave elastography (SWE), and dynamic contrast-enhanced ultrasound (DCE-US) radiomics for the Localization of prostate Cancer (PCa) lesions using transrectal ultrasound. This study was approved by the institutional review board and comprised 50 men with biopsy-confirmed PCa that were referred for radical prostatectomy. Prior to surgery, patients received transrectal ultrasound (TRUS), SWE, and DCE-US for three imaging planes. The images were automatically segmented and registered. First, model-based features related to contrast perfusion and dispersion were extracted from the DCE-US videos. Subsequently, radiomics were retrieved from all modalities. Machine learning was applied through a random forest classification algorithm, using the co-registered histopathology from the radical prostatectomy specimens as a reference to draw benign and malignant regions of interest. To avoid overfitting, the performance of the multiparametric classifier was assessed through leave-one-patient-out cross-validation. The multiparametric classifier reached a region-wise area under the receiver operating characteristics curve (ROC-AUC) of 0.75 and 0.90 for PCa and Gleason > 3 + 4 significant PCa, respectively, thereby outperforming the best-performing single parameter (i.e., contrast velocity) yielding ROC-AUCs of 0.69 and 0.76, respectively. Machine learning revealed that combinations between perfusion-, dispersion-, and elasticity-related features were favored. In this paper, technical feasibility of multiparametric machine learning to improve upon single US modalities for the Localization of PCa has been demonstrated. Extended datasets for training and testing may establish the clinical value of automatic multiparametric US classification in the early diagnosis of PCa. • Combination of B-mode ultrasound, shear-wave elastography, and contrast ultrasound radiomics through machine learning is technically feasible. • Multiparametric ultrasound demonstrated a higher prostate Cancer Localization ability than single ultrasound modalities. • Computer-aided multiparametric ultrasound could help clinicians in biopsy targeting.
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imaging of the dispersion coefficient of ultrasound contrast agents by wiener system identification for prostate Cancer Localization
Internaltional Ultrasonics Symposium, 2015Co-Authors: Ruud J G Van Sloun, Hessel Wijkstra, Libertario Demi, Arnoud W Postema, Jean J M C H De La Rosette, Massimo MischiAbstract:Prostate Cancer (PCa) is the most prevalent form of Cancer in Western men; however, reliable tools for PCa detection and Localization are lacking. Dynamic Contrast Enhanced Ultrasound (DCE-US) is a diagnostic tool that allows analysis of vascularization, by imaging an intravenously injected microbubble bolus. The Localization of angiogenic vascularization associated with the development of tumors is of particular interest. Recently, methods aiming at estimating contrast dispersion to localize angiogenesis have shown promise. However, independent estimation of dispersion was not possible due to the ambiguity between dispersive and convective processes. Therefore, in this study we propose a new method that considers the vascular network as a dynamic linear system, whose impulse response can be locally identified by solving the Wiener-Hopf equations. To facilitate characterization, model-based parameter estimation is employed, permitting the determination of the apparent dispersion coefficient (D), velocity (v), and Peclet number (Pe) of the system. A preliminary clinical evaluation using data recorded from 10 patients shows that the proposed method can be applied effectively to DCE-US, and is able to locally characterize the hemodynamics in the prostate.
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Contrast-ultrasound dispersion imaging of Cancer neovascularization by mutual-information analysis
2014 IEEE International Ultrasonics Symposium, 2014Co-Authors: Massimo Mischi, Maarten Petrus Joseph Kuenen, Libertario Demi, Nabil Bouhouch, Arnoud Postema, Jean J. De La Rosette, Tjalling J. Tjalkens, Hessel WijkstraAbstract:Being an established marker for Cancer growth, neovascularization is probed by several approaches with the aim of Cancer imaging. Recently, analysis of the dispersion kinetics of ultrasound contrast agents (UCAs) has been proposed as a promising approach for localizing neovascularization in prostate Cancer. Determined by multipath trajectories through the microvasculature, dispersion enables characterization of the microvascular architecture and, therefore, Localization of Cancer neovascularization. Analysis of the spatiotemporal similarity among indicator dilution curves (IDCs) measured at each pixel by dynamic contrast-enhanced ultrasound imaging has been proposed to assess the local dispersion kinetics of UCAs. Only linear similarity measures, such as temporal correlation or spectral coherence, have been used up until now. Here we investigate the use of nonlinear similarity measures by estimation of the statistical dependency between IDCs. In particular, dispersion maps are generated by estimation of the mutual information between IDCs. The method is tested for prostate Cancer Localization and the results compared with the histology results in 15 patients referred for radical prostatectomy because of biopsy-proven prostate Cancer. With sensitivity and specificity equal to 84% and 85%, respectively, and receiver operating characteristic curve area equal to 0.92, our results outperformed those obtained by any other parameter, motivating further validation with a larger dataset and with other types of Cancer.
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contrast ultrasound dispersion imaging for prostate Cancer Localization by improved spatiotemporal similarity analysis
Ultrasound in Medicine and Biology, 2013Co-Authors: Maarten Petrus Joseph Kuenen, Hessel Wijkstra, T Tamerlan A Saidov, Massimo MischiAbstract:Angiogenesis plays a major role in prostate Cancer growth. Despite extensive research on blood perfusion imaging aimed at angiogenesis detection, the diagnosis of prostate Cancer still requires systematic biopsies. This may be due to the complex relationship between angiogenesis and microvascular perfusion. Analysis of ultrasound-contrast-agent dispersion kinetics, determined by multipath trajectories in the microcirculation, may provide better characterization of the microvascular architecture. We propose the physical rationale for dispersion estimation by an existing spatiotemporal similarity analysis. After an intravenous ultrasound-contrast-agent bolus injection, dispersion is estimated by coherence analysis among time-intensity curves measured at neighbor pixels. The accuracy of the method is increased by time-domain windowing and anisotropic spatial filtering for speckle regularization. The results in 12 patient data sets indicated superior agreement with histology (receiver operating characteristic curve area = 0.88) compared with those obtained by reported perfusion and dispersion analyses, providing a valuable contribution to prostate Cancer Localization.
-
angiogenesis imaging by spatiotemporal analysis of ultrasound contrast agent dispersion kinetics
IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, 2012Co-Authors: Massimo Mischi, Maarten Petrus Joseph Kuenen, Hessel WijkstraAbstract:The key role of angiogenesis in Cancer growth has motivated extensive research with the goal of noninvasive Cancer detection by blood perfusion imaging. However, the results are still limited and the diagnosis of major forms of Cancer, such as prostate Cancer, are currently based on systematic biopsies. The difficulty in the detection of angiogenesis partly resides in a complex relationship between angiogenesis and perfusion. This may be overcome by analysis of the dispersion kinetics of ultrasound contrast agents. Determined by multipath trajectories through the microvasculature, dispersion permits a better characterization of the microvascular architecture and, therefore, more accurate detection of angiogenesis. In this paper, a novel dispersion analysis method is proposed for prostate Cancer Localization. An ultrasound contrast agent bolus is injected intravenously. Spatiotemporal analysis of the concentration evolution measured at different pixels in the prostate is used to assess the local dispersion kinetics of the injected agent. In particular, based on simulations of the convective diffusion equation, the similarity between the concentration evolutions at neighbor pixels is the adopted dispersion measure. Six measurements in patients, compared with the histology, provided a receiver operating characteristic curve integral equal to 0.87. This result was superior to that obtained by the previous approaches reported in the literature.
Stijn W. T. P. J. Heijmink - One of the best experts on this subject based on the ideXlab platform.
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prostate Cancer multiparametric mr imaging for detection Localization and staging
Radiology, 2011Co-Authors: Caroline M A Hoeks, Stijn W. T. P. J. Heijmink, Henkjan J Huisman, Tom W J Scheenen, Jelle O. Barentsz, Thomas Hambrock, Derya Yakar, Diederik M Somford, Pieter C Vos, Inge M Van OortAbstract:This review presents the current state of the art regarding multiparametric magnetic resonance (MR) imaging of prostate Cancer. Technical requirements and clinical indications for the use of multiparametric MR imaging in detection, Localization, characterization, staging, biopsy guidance, and active surveillance of prostate Cancer are discussed. Although reported accuracies of the separate and combined multiparametric MR imaging techniques vary for diverse clinical prostate Cancer indications, multiparametric MR imaging of the prostate has shown promising results and may be of additional value in prostate Cancer Localization and local staging. Consensus on which technical approaches (field strengths, sequences, use of an endorectal coil) and combination of multiparametric MR imaging techniques should be used for specific clinical indications remains a challenge. Because guidelines are currently lacking, suggestions for a general minimal protocol for multiparametric MR imaging of the prostate based on the literature and the authors' experience are presented. Computer programs that allow evaluation of the various components of a multiparametric MR imaging examination in one view should be developed. In this way, an integrated interpretation of anatomic and functional MR imaging techniques in a multiparametric MR imaging examination is possible. Education and experience of specialist radiologists are essential for correct interpretation of multiparametric prostate MR imaging findings. Supportive techniques, such as computer-aided diagnosis are needed to obtain a fast, cost-effective, easy, and more reproducible prostate Cancer diagnosis out of more and more complex multiparametric MR imaging data.
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prostate Cancer body array versus endorectal coil mr imaging at 3 t comparison of image quality Localization and staging performance
Radiology, 2007Co-Authors: Stijn W. T. P. J. Heijmink, Jurgen J Futterer, Henkjan J Huisman, Tom W J Scheenen, Alfred J Witjes, Thomas Hambrock, Satoru Takahashi, Ben C Knipscheer, Lambertus A Kiemeney, Jelle O. BarentszAbstract:PURPOSE: To prospectively compare image quality and accuracy of prostate Cancer Localization and staging with body-array coil (BAC) versus endorectal coil (ERC) T2-weighted magnetic resonance (MR) imaging at 3 T, with histopathologic findings as the reference standard. MATERIALS AND METHODS: After institutional review board approval and written informed consent, 46 men underwent 3-T T2-weighted MR imaging with a BAC (voxel size, 0.43 x 0.43 x 4.00 mm) and an ERC (voxel size, 0.26 x 0.26 x 2.50 mm) before radical prostatectomy. Four radiologists independently evaluated data sets obtained with the BAC and ERC separately. Ten image quality characteristics related to prostate Cancer Localization and staging were assigned scores. Prostate Cancer presence was recorded with a five-point probability scale in each of 14 segments that included the whole prostate. Disease stage was classified as organ-confined or locally advanced with a five-point probability scale. Whole-mount-section histopathologic examination was the reference standard. Areas under the receiver operating characteristic curve (AUCs) and diagnostic performance parameters were determined. A difference with a P value of less than .05 was considered significant. RESULTS: Forty-six patients (mean age, 61 years) were included for analysis. Significantly more motion artifacts were present with ERC imaging (P<.001). All other image quality characteristics improved significantly (P<.001) with ERC imaging. With ERC imaging, the AUC for Localization of prostate Cancer was significantly increased from 0.62 to 0.68 (P<.001). ERC imaging significantly increased the AUCs for staging, and sensitivity for detection of locally advanced disease by experienced readers was increased from 7% (one of 15) to a range of 73% (11 of 15) to 80% (12 of 15) (P<.05), whereas a high specificity of 97% (30 of 31) to 100% (31 of 31) was maintained. Extracapsular extension as small as 0.5 mm at histopathologic examination could be accurately detected only with ERC imaging. CONCLUSION: Image quality and Localization improved significantly with ERC imaging compared with BAC imaging. For experienced radiologists, the staging performance was significantly better with ERC imaging.
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prostate Cancer body array versus endorectal coil mr imaging at 3 t comparison of image quality Localization and staging performance
Radiology, 2007Co-Authors: Stijn W. T. P. J. Heijmink, Jurgen J Futterer, Henkjan J Huisman, Tom W J Scheenen, Thomas Hambrock, Satoru Takahashi, Christina Hulsbergenvan A De Kaa, Ben C Knipscheer, Lambertus A Kiemeney, Alfred J WitjesAbstract:Purpose: To prospectively compare image quality and accuracy of prostate Cancer Localization and staging with body-array coil (BAC) versus endorectal coil (ERC) T2-weighted magnetic resonance (MR) imaging at 3 T, with histopathologic findings as the reference standard. Materials and Methods: After institutional review board approval and written informed consent, 46 men underwent 3-T T2-weighted MR imaging with a BAC (voxel size, 0.43 × 0.43 × 4.00 mm) and an ERC (voxel size, 0.26 × 0.26 × 2.50 mm) before radical prostatectomy. Four radiologists independently evaluated data sets obtained with the BAC and ERC separately. Ten image quality characteristics related to prostate Cancer Localization and staging were assigned scores. Prostate Cancer presence was recorded with a five-point probability scale in each of 14 segments that included the whole prostate. Disease stage was classified as organ-confined or locally advanced with a five-point probability scale. Whole-mount-section histopathologic examination wa...
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prostate Cancer Localization with dynamic contrast enhanced mr imaging and proton mr spectroscopic imaging
Radiology, 2006Co-Authors: Jurgen J Futterer, Stijn W. T. P. J. Heijmink, Jeroen Veltman, Henkjan J Huisman, Paul F M Krabbe, Tom W J Scheenen, Alfred J Witjes, Arend Heerschap, Jelle O. BarentszAbstract:Purpose: To prospectively determine the accuracies of T2-weighted magnetic resonance (MR) imaging, dynamic contrast material–enhanced MR imaging, and quantitative three-dimensional (3D) proton MR spectroscopic imaging of the entire prostate for prostate Cancer Localization, with whole-mount histopathologic section findings as the reference standard. Materials and Methods: This study was approved by the institutional review board, and informed consent was obtained from all patients. Thirty-four consecutive men with a mean age of 60 years and a mean prostate-specific antigen level of 8 ng/mL were examined. The median biopsy Gleason score was 6. T2-weighted MR imaging, dynamic contrast-enhanced MR imaging, and 3D MR spectroscopic imaging were performed, and on the basis of the image data, two readers with different levels of experience recorded the location of the suspicious peripheral zone and central gland tumor nodules on each of 14 standardized regions of interest (ROIs) in the prostate. The degree of di...
