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Diffusion-Weighted MRI of Breast Cancer: Improved Lesion Visibility and image Quality Using Synthetic b-Values

JOURNAL OF MAGNETIC RESONANCE IMAGING 2019年第6期50卷 1754-1761页

作者： Bickel, Hubert Polanec, Stephan H. Wengert, Georg Pinker, Katja Bogner, Wolfgang Helbich, Thomas H. Baltzer, Pascal A. Med Univ Vienna Div Mol & Gender Imaging Dept Biomed Imaging & Image Guided Therapy Vienna Austria Mem Sloan Kettering Canc Ctr Breast Imaging Serv Dept Radiol 1275 York Ave New York NY 10021 USA Med Univ Vienna Dept Biomed Imaging & Image Guided Therapy High Field MR Ctr Vienna Austria

Background: Diffusion-weighted imaging (DWI) is an MRI technique with the potential to serve as an unenhanced breast cancer detection tool. Synthetic b-values produce images with high diffusion weighting to suppress residual background signal, while avoiding additional measurement times and reducing artifacts. Purpose: To compare acquired DWI images (at b = 850 s/mm(2)) and different synthetic b-values (at b = 1000-2000 s/mm(2)) in terms of lesion visibility, image quality, and tumor-to-tissue contrast in patients with malignant breast tumors. Study Type: Retrospective. Population: Fifty-three females with malignant breast lesions. Field Strength/Sequence: T(2)w, DWI EPI with STIR fat-suppression, and dynamic contrast-enhanced T(1)w at 3T. Assessment: From acquired images using b-values of 50 and 850 s/mm(2), synthetic images were calculated at b = 1000, 1200, 1400, 1600, 1800, and 2000 s/mm(2). Four readers independently rated image quality, lesion visibility, preferred b-value, as well as the lowest and highest b-value, over the range of b-values tested, to provide a diagnostic image. Statistical Tests: Medians and mean ranks were calculated and compared using the Friedman test and Wilcoxon signed-rank test. Reproducibility was analyzed by intraclass correlation (ICC), Fleiss, and Cohen's kappa. Results: Relative signal-to-noise and contrast-to-noise ratios decreased with increasing b-values, while the signal-intensity ratio between tumor and tissue increased significantly (P < 0.001). Intermediate b-values (1200-1800 s/mm(2)) were rated best concerning image quality and lesion visibility;the preferred b-value mostly lay at 1200-1600 s/mm(2). Lowest and highest acceptable b-values were 850 s/mm(2) and 2000 s/mm(2). Interreader agreement was moderate to high concerning image quality (ICC: 0.50-0.67) and lesion visibility (0.70-0.93), but poor concerning preferred and acceptable b-values (kappa = 0.032-0.446). Data Conclusion: Synthetically increased b-values may be

关键词： Breast neoplasms magnetic resonance imaging diffusion magnetic resonance imaging computer-assisted image processing

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image processing - mechanical vision in production

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ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb 1998年第10期93卷 511-514页

作者： Adam, Wolfgang Nickolay, Bertram

In the course of the automation of manufacturing processes, industry has identified the benefits of computer-assisted image processing as one of the decisive factors in achieving cost-effective production. This article provides an insight into the development of industrial image processing and shows how it can be put to use in new fields of application.

关键词： Investigational New Drug Application image processing Insight Automation image Manufacturing process computer-assisted image processing

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Novel mammographic image features differentiate between interval and screen-detected breast cancer: a case-case study

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BREAST CANCER RESEARCH 2016年第1期10卷 1-10页

作者： Strand, Fredrik Humphreys, Keith Cheddad, Abbas Tornberg, Sven Azavedo, Edward Shepherd, John Hall, Per Czene, Kamila Karolinska Inst Dept Med Epidemiol & Biostat POB 281 SE-17177 Stockholm Sweden Karolinska Univ Hosp Diagnost Radiol Solna Sweden Karolinska Inst Swedish eSci Res Ctr Solna Sweden Stockholm Gotland Reg Canc Ctr Dept Canc Screening Stockholm Sweden Karolinska Inst Dept Mol Med & Surg Solna Sweden Univ Calif San Francisco UCSF Sch Med Dept Radiol & Biomed Imaging San Francisco CA 94143 USA

Background: Interval breast cancers are often diagnosed at a more advanced stage than screen-detected cancers. Our aim was to identify features in screening mammograms of the normal breast that would differentiate between future interval cancers and screen-detected cancers, and to understand how each feature affects tumor detectability. Methods: From a population-based cohort of invasive breast cancer cases in Stockholm-Gotland, Sweden, diagnosed from 2001 to 2008, we analyzed the contralateral mammogram at the preceding negative screening of 394 interval cancer cases and 1009 screen-detected cancers. We examined 32 different image features in digitized film mammograms, based on three alternative dense area identification methods, by a set of logistic regression models adjusted for percent density with interval cancer versus screen-detected cancer as the outcome. Features were forward-selected into a multiple logistic regression model adjusted for mammographic percent density, age, BMI and use of hormone replacement therapy. The associations of the identified features were assessed also in a sample from an independent cohort. Results: Two image features, 'skewness of the intensity gradient' and 'eccentricity', were associated with the risk of interval compared with screen-detected cancer. For the first feature, the per-standard deviation odds ratios were 1.32 (95 % CI: 1.12 to 1.56) and 1.21 (95 % CI: 1.04 to 1.41) in the primary and validation cohort respectively. For the second feature, they were 1.20 (95 % CI: 1.04 to 1.39) and 1.17 (95% CI: 0.98 to 1.39) respectively. The first feature was associated with the tumor size at screen detection, while the second feature was associated with the tumor size at interval detection. Conclusions: We identified two novel mammographic features in screening mammograms of the normal breast that differentiated between future interval cancers and screen-detected cancers. We present a starting point for further research into featu

关键词： Breast cancer Interval cancer Cancer screening Early detection Mammography computer-assisted image processing

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Integration of interactive three-dimensional image post-processing software into undergraduate radiology education effectively improves diagnostic skills and visual-spatial ability

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EUROPEAN JOURNAL OF RADIOLOGY 2013年第8期82卷 1366-1371页

作者： Rengier, Fabian Haefner, Matthias F. Unterhinninghofen, Roland Nawrotzki, Ralph Kirsch, Joachim Kauczor, Hans-Ulrich Giesel, Frederik L. Univ Heidelberg Hosp Dept Diagnost & Intervent Radiol D-69120 Heidelberg Germany Univ Heidelberg Hosp Dept Radiat Oncol D-69120 Heidelberg Germany Karlsruhe Inst Technol Inst Anthropomat Dept Informat D-76131 Karlsruhe Germany Heidelberg Univ Inst Anat & Cell Biol D-69120 Heidelberg Germany Univ Heidelberg Hosp Dept Nucl Med D-69120 Heidelberg Germany

Purpose: Integrating interactive three-dimensional post-processing software into undergraduate radiology teaching might be a promising approach to synergistically improve both visual-spatial ability and radiological skills, thereby reducing students' deficiencies in image interpretation. The purpose of this study was to test our hypothesis that a hands-on radiology course for medical students using interactive three-dimensional image post-processing software improves radiological knowledge, diagnostic skills and visual-spatial ability. Materials and methods: A hands-on radiology course was developed using interactive three-dimensional image post-processing software. The course consisted of seven seminars held on a weekly basis. The 25 participating fourth- and fifth-year medical students learnt to systematically analyse cross-sectional imaging data and correlated the two-dimensional images with three-dimensional reconstructions. They were instructed by experienced radiologists and collegiate tutors. The improvement in radiological knowledge, diagnostic skills and visual-spatial ability was assessed immediately before and after the course by multiple-choice tests comprising 64 questions each. Wilcoxon signed rank test for paired samples was applied. Results: The total number of correctly answered questions improved from 36.9 +/- 4.8 to 49.5 +/- 5.4 (p < 0.001) which corresponded to a mean improvement of 12.6 (95% confidence interval 9.9-15.3) or 19.8%. Radiological knowledge improved by 36.0% (p < 0.001), diagnostic skills for cross-sectional imaging by 38.7% (p < 0.001), diagnostic skills for other imaging modalities - which were not included in the course - by 14.0% (p = 0.001), and visual-spatial ability by 11.3% (p < 0.001). Conclusion: The integration of interactive three-dimensional image post-processing software into undergraduate radiology education effectively improves radiological reasoning, diagnostic skills and visual-spatial ability, and thereby even dia

关键词： Undergraduate medical education Radiology computer-assisted image processing Teaching Visual-spatial ability

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Assessment of first-trimester utero-placental vascular morphology by 3D power Doppler ultrasound image analysis using a skeletonization algorithm: the Rotterdam Periconception Cohort

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HUMAN REPRODUCTION 2022年第11期37卷 2532-2545页

作者： de Vos, Eline S. Koning, Anton H. J. Steegers-Theunissen, Regine P. M. Willemsen, Sten P. van Rijn, Bas B. Steegers, Eric A. P. Mulders, Annemarie G. M. G. J. Erasmus MC Dept Obstet & Gynecol Univ Med Ctr Rotterdam POB 2040 NL-3000 CA Rotterdam Netherlands Erasmus MC Dept Pathol Univ Med Ctr Rotterdam Rotterdam Netherlands Erasmus MC Dept Biostat Univ Med Ctr Rotterdam Rotterdam Netherlands

STUDY QUESTION Can three-dimensional (3D) Power Doppler (PD) ultrasound and a skeletonization algorithm be used to assess first-trimester development of the utero-placental vascular morphology? SUMMARY ANSWER The application of 3D PD ultrasonography and a skeletonization algorithm facilitates morphologic assessment of utero-placental vascular development in the first trimester and reveals less advanced vascular morphologic development in pregnancies with placenta-related complications than in pregnancies without placenta-related complications. WHAT IS KNOWN ALREADY Suboptimal development of the utero-placental vasculature is one of the main contributors to the periconceptional origin of placenta-related complications. The nature and attribution of aberrant vascular structure and branching patterns remain unclear, as validated markers monitoring first-trimester utero-placental vascular morphologic development are lacking. STUDY DESIGN, SIZE, DURATION In this prospective observational cohort, 214 ongoing pregnancies were included before 10 weeks gestational age (GA) at a tertiary hospital between January 2017 and July 2018, as a subcohort of the ongoing Rotterdam Periconception Cohort study. PARTICIPANTS/MATERIALS, SETTING, METHODS By combining 3D PD ultrasonography and virtual reality, utero-placental vascular volume (uPVV) measurements were obtained at 7, 9 and 11 weeks GA. A skeletonization algorithm was applied to the uPVV measurements to generate the utero-placental vascular skeleton (uPVS), a network-like structure containing morphologic characteristics of the vasculature. Quantification of vascular morphology was performed by assigning a morphologic characteristic to each voxel in the uPVS (end-, vessel-, bifurcation- or crossing-point) and calculating total vascular network length. A Mann-Whitney U test was performed to investigate differences in morphologic development of the first-trimester utero-placental vasculature between pregnancies with and without pla

关键词： computer-assisted image processing virtual reality ultrasonography placental vascular development preeclampsia

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Clinical feasibility of deep learning-based automatic head CBCT image segmentation and landmark detection in computer- aided surgical simulation for orthognathic surgery

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INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY 2023年第7期52卷 793-800页

作者： Deng, H. H. Liu, Q. Chen, A. Kuang, T. Yuan, P. Gateno, J. Kim, D. Barber, J. C. Xiong, K. G. Yu, P. Gu, K. J. Xu, X. Yan, P. Shen, D. Xia, J. J. Houston Methodist Res Inst Dept Oral & Maxillofacial Surg Houston TX 77030 USA Univ N Carolina Dept Radiol Chapel Hill NC USA Cornell Univ Weill Med Coll Dept Surg Oral & Maxillofacial Surg New York NY USA Rensselaer Polytech Inst Dept Biomed Engn Troy NY USA

The purpose of this ambispective study was to investigate whether deep learning-based automatic segmentation and landmark detection, the SkullEngine, could be used for orthognathic surgical planning. Sixty-one sets of cone beam computed tomography (CBCT) images were automatically inferred for midface, mandible, upper and lower teeth, and 68 landmarks. The experimental group included automatic segmentation and landmarks, while the control group included manual ones that were previously used to plan orthognathic surgery. The qualitative analysis of segmentation showed that all of the automatic results could be used for computeraided surgical simulation. Among these, 98.4% of midface, 70.5% of mandible, 98.4% of upper teeth, and 93.4% of lower teeth could be directly used without manual revision. The Dice similarity coefficient was 96% and the average symmetric surface distance was 0.1 mm for all four structures. With SkullEngine, it took 4 minutes to complete the automatic segmentation and an additional 10 minutes for a manual touchup. The results also showed the overall mean difference between the two groups was 2.3 mm for the midface and 2.4 mm for the mandible. In summary, the authors believe that automatic segmentation using SkullEngine is ready for daily practice. However, the accuracy of automatic landmark digitization needs to be improved.

关键词： Feasibility studies Deep learning computer-assisted image processing Algorithms computer-assisted Three-Dimensional Imaging Cone-beam computed tomography Orthognathic surgery computer-aided surgery

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image registration improves human knee cartilage T1 mapping with delayed gadolinium-enhanced MRI of cartilage (dGEMRIC)

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EUROPEAN RADIOLOGY 2013年第1期23卷 246-252页

作者： Bron, Esther E. van Tiel, Jasper Smit, Henk Poot, Dirk H. J. Niessen, Wiro J. Krestin, Gabriel P. Weinans, Harrie Oei, Edwin H. G. Kotek, Gyula Klein, Stefan Univ Med Ctr Rotterdam Erasmus MC Biomed Imaging Grp Rotterdam Dept Med Informat NL-3000 CA Rotterdam Netherlands Univ Med Ctr Rotterdam Erasmus MC Biomed Imaging Grp Rotterdam Dept Radiol NL-3000 CA Rotterdam Netherlands Erasmus MC Dept Orthopaed Surg Rotterdam Netherlands Delft Univ Technol Dept Appl Sci Delft Netherlands Delft Univ Technol Dept Biomech Engn Delft Netherlands

To evaluate the effect of automated registration in delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) of the knee on the occurrence of movement artefacts on the T1 map and the reproducibility of region-of-interest (ROI)-based measurements. Eleven patients with early-stage knee osteoarthritis and ten healthy controls underwent dGEMRIC twice at 3 T. Controls underwent unenhanced imaging. ROIs were manually drawn on the femoral and tibial cartilage. T1 calculation was performed with and without registration of the T1-weighted images. Automated three-dimensional rigid registration was performed on the femur and tibia cartilage separately. Registration quality was evaluated using the square root Cram,r-Rao lower bound (CRLB sigma). Additionally, the reproducibility of dGEMRIC was assessed by comparing automated registration with manual slice-matching. Automated registration of the T1-weighted images improved the T1 maps as the 90% percentile of the CRLB sigma was significantly (P < 0.05) reduced with a median reduction of 55.8 ms (patients) and 112.9 ms (controls). Manual matching and automated registration of the re-imaged T1 map gave comparable intraclass correlation coefficients of respectively 0.89/0.90 (patients) and 0.85/0.85 (controls). Registration in dGEMRIC reduces movement artefacts on T1 maps and provides a good alternative to manual slice-matching in longitudinal studies.

关键词： Magnetic resonance imaging Articular cartilage Knee osteoarthritis computer-assisted image processing Reproducibility of results

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Metallic dental artifact reduction in computed tomography (Smart MAR): Improvement of image quality and diagnostic confidence in patients with suspected head and neck pathology and oral implants

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EUROPEAN JOURNAL OF RADIOLOGY 2019年 118卷 153-160页

作者： Feldhaus, Felix Boening, Georg Jonczyk, Martin Kahn, Johannes Fehrenbach, Uli Maurerb, M. Benz, D. Hamm, Bernd Streitparth, Florian Charite Univ Med Berlin Augustenburger Pl 1 D-13353 Berlin Germany Free Univ Berlin Augustenburger Pl 1 D-13353 Berlin Germany Humboldt Univ Augustenburger Pl 1 D-13353 Berlin Germany Berlin Inst Hlth Dept Radiol Augustenburger Pl 1 D-13353 Berlin Germany Univ Bern Inselspital Dept Diagnost Intervent & Pediat Radiol CH-3010 Bern Switzerland Univ Jena Dept Radiol Klinikum 1 D-07747 Jena Germany Ludwig Maximilians Univ Munchen Dept Radiol Marchioninistr 15 D-81377 Munich Germany

Purpose: We determined whether the Smart MAR metal artifact reduction tool - a three-stage, projection-based, post processing algorithm - improves subjective and objective image quality and diagnostic confidence in patients with dental artifacts and suspected head and neck pathology compared to standard adaptive statistical iterative reconstructions (ASIR V) alone. Method: The study included 100 consecutive patients with nonremovable oral implants or dental fillings and suspected oropharyngeal cancer or abscess. CT raw data of a single-source multislice CT scanner were post-processed using ASIR V alone and with additional Smart MAR reconstruction. image quality of baseline ASIR V and Smart MAR-based reconstruction series was compared both quantitatively (5 regions of interest, ROIs) and qualitatively (two independent raters). Results: Additional Smart MAR reconstruction significantly seems to improve both attenuation and noise adjacent to implants and in more distant areas (all p < 0.001) compared to standard ASIR V reconstructions alone. Signal-to-noise ratio (SNR;p = 0.001) and contrast-to-noise ratio were improved significantly (CNR;p = 0.001). Smart MAR improved visualization of tumor/abscess (detected in 36 of 100 patients, 36%) and representative oropharyngeal tissue (p < 0.001). In 8 of 36 patients (22%), tumor was only detected in Smart MAR series. Mean total DLP was 506.8mGy*cm;average CTDIvol was 5.5 mGy. Conclusions: The supplementary use of the Smart MAR post-processing tool seems to significantly improve both subjective and objective image quality as well as diagnostic confidence and lesion detection in CT of the head and neck. In 22% of cases, the tumor was detected only in Smart MAR reconstructed images.

关键词： computer-assisted image processing Artifacts Neck Squamous cell carcinoma

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image Fusion of Preprocedural CTA with Real-time Fluoroscopy to Guide Proper Hepatic Artery Catheterization During Transarterial Chemoembolization of Hepatocellular Carcinoma: A Feasibility Study

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CARDIOVASCULAR AND INTERVENTIONAL RADIOLOGY 2013年第2期36卷 526-530页

作者： Bargellini, Irene Turini, Francesca Bozzi, Elena Lauretti, Dario Cicorelli, Antonio Lunardi, Alessandro Cioni, Roberto Bartolozzi, Carlo Univ Pisa Dept Diagnost & Intervent Radiol I-56100 Pisa Italy

To assess feasibility of proper hepatic artery catheterization using a 3D model obtained from preprocedural computed tomographic angiography (CTA), fused with real-time fluoroscopy, during transarterial chemoembolization of hepatocellular carcinoma. Twenty consecutive cirrhotic patients with hepatocellular carcinoma undergoing transarterial chemoembolization were prospectively enrolled onto the study. The early arterial phase axial images of the preprocedural CTA were postprocessed on an independent workstation connected to the angiographic system (Innova 4100;GE Healthcare, Milwaukee, WI), obtaining a 3D volume rendering image (VR) that included abdominal aorta, splanchnic arteries, and first and second lumbar vertebrae. The VR image was manually registered to the real-time X-ray fluoroscopy, with the lumbar spine used as the reference. The VR image was then used as guidance to selectively catheterize the proper hepatic artery. The procedure was considered successful when performed with no need for intraarterial contrast injections or angiographic acquisitions. The procedure was successful in 19 (95 %) of 20 patients. In one patient, celiac trunk angiography was required for the presence of a significant ostial stenosis that was underestimated at computed tomography. Time for image reconstruction and registration was < 10 min in all cases. The use of preprocedural CTA model with fluoroscopy enables confident and direct catheterization of the proper hepatic artery with no need for preliminary celiac trunk angiography, thus reducing radiation exposure and contrast media administration.

关键词： Catheterization Chemoembolization Computed tomography computer-assisted image processing Fluoroscopy Hepatocellular carcinoma

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Demystification of AI-driven medical image interpretation: past, present and future

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EUROPEAN RADIOLOGY 2019年第3期29卷 1616-1624页

作者： Savadjiev, Peter Chong, Jaron Dohan, Anthony Vakalopoulou, Maria Reinhold, Caroline Paragios, Nikos Gallix, Benoit McGill Univ Dept Diagnost Radiol Montreal PQ Canada McGill Univ Hlth Ctr Dept Diagnost Radiol Montreal PQ Canada Univ Diderot Paris 7 Hop Lariboisiere AP HP Dept Body & Intervent Imaging F-75475 Paris 10 France INSERM U965 F-75475 Paris 10 France Ecole Cent Supelec F-91190 Gif Sur Yvette France Ecole Cent Supelec F-91120 PAL Palaiseau France Inria Saclay Ile de France F-91120 Palaiseau France TheraPanacea F-75014 Paris France

The recent explosion of big data' has ushered in a new era of artificial intelligence (AI) algorithms in every sphere of technological activity, including medicine, and in particular radiology. However, the recent success of AI in certain flagship applications has, to some extent, masked decades-long advances in computational technology development for medical image analysis. In this article, we provide an overview of the history of AI methods for radiological image analysis in order to provide a context for the latest developments. We review the functioning, strengths and limitations of more classical methods as well as of the more recent deep learning techniques. We discuss the unique characteristics of medical data and medical science that set medicine apart from other technological domains in order to highlight not only the potential of AI in radiology but also the very real and often overlooked constraints that may limit the applicability of certain AI methods. Finally, we provide a comprehensive perspective on the potential impact of AI on radiology and on how to evaluate it not only from a technical point of view but also from a clinical one, so that patients can ultimately benefit from *** Points center dot Artificial intelligence (AI) research in medical imaging has a long history center dot The functioning, strengths and limitations of more classical AI methods is reviewed, together with that of more recent deep learning *** dot A perspective is provided on the potential impact of AI on radiology and on its evaluation from both technical and clinical points of view.

关键词： Diagnostic imaging Artificial intelligence (AI) Machine learning computer-assisted image processing computer-assisted image interpretation

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