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Couchoux T, Jaouen T, Melodelima-Gonindard C, Baseilhac P, Branchu A, Arfi N, Aziza R, Barry Delongchamps N, Bladou F, Bratan F, Brunelle S, Colin P, Correas JM, Cornud F, Descotes JL, Eschwege P, Fiard G, Guillaume B, Grange R, Grenier N, Lang H, Lefèvre F, Malavaud B, Marcelin C, Moldovan PC, Mottet N, Mozer P, Potiron E, Portalez D, Puech P, Renard-Penna R, Roumiguié M, Roy C, Timsit MO, Tricard T, Villers A, Walz J, Debeer S, Mansuy A, Mège-Lechevallier F, Decaussin-Petrucci M, Badet L, Colombel M, Ruffion A, Crouzet S, Rabilloud M, Souchon R, Rouvière O. Performance of a Region of Interest-based Algorithm in Diagnosing International Society of Urological Pathology Grade Group ≥2 Prostate Cancer on the MRI-FIRST Database-CAD-FIRST Study. Eur Urol Oncol 2024:S2588-9311(24)00056-7. [PMID: 38493072 DOI: 10.1016/j.euo.2024.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 03/01/2024] [Indexed: 03/18/2024]
Abstract
BACKGROUND AND OBJECTIVE Prostate multiparametric magnetic resonance imaging (MRI) shows high sensitivity for International Society of Urological Pathology grade group (GG) ≥2 cancers. Many artificial intelligence algorithms have shown promising results in diagnosing clinically significant prostate cancer on MRI. To assess a region-of-interest-based machine-learning algorithm aimed at characterising GG ≥2 prostate cancer on multiparametric MRI. METHODS The lesions targeted at biopsy in the MRI-FIRST dataset were retrospectively delineated and assessed using a previously developed algorithm. The Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) score assigned prospectively before biopsy and the algorithm score calculated retrospectively in the regions of interest were compared for diagnosing GG ≥2 cancer, using the areas under the curve (AUCs), and sensitivities and specificities calculated with predefined thresholds (PIRADSv2 scores ≥3 and ≥4; algorithm scores yielding 90% sensitivity in the training database). Ten predefined biopsy strategies were assessed retrospectively. KEY FINDINGS AND LIMITATIONS After excluding 19 patients, we analysed 232 patients imaged on 16 different scanners; 85 had GG ≥2 cancer at biopsy. At patient level, AUCs of the algorithm and PI-RADSv2 were 77% (95% confidence interval [CI]: 70-82) and 80% (CI: 74-85; p = 0.36), respectively. The algorithm's sensitivity and specificity were 86% (CI: 76-93) and 65% (CI: 54-73), respectively. PI-RADSv2 sensitivities and specificities were 95% (CI: 89-100) and 38% (CI: 26-47), and 89% (CI: 79-96) and 47% (CI: 35-57) for thresholds of ≥3 and ≥4, respectively. Using the PI-RADSv2 score to trigger a biopsy would have avoided 26-34% of biopsies while missing 5-11% of GG ≥2 cancers. Combining prostate-specific antigen density, the PI-RADSv2 and algorithm's scores would have avoided 44-47% of biopsies while missing 6-9% of GG ≥2 cancers. Limitations include the retrospective nature of the study and a lack of PI-RADS version 2.1 assessment. CONCLUSIONS AND CLINICAL IMPLICATIONS The algorithm provided robust results in the multicentre multiscanner MRI-FIRST database and could help select patients for biopsy. PATIENT SUMMARY An artificial intelligence-based algorithm aimed at diagnosing aggressive cancers on prostate magnetic resonance imaging showed results similar to expert human assessment in a prospectively acquired multicentre test database.
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Affiliation(s)
- Thibaut Couchoux
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | | | | | - Pierre Baseilhac
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Arthur Branchu
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Nicolas Arfi
- Department of Urology, Hôpital Saint Joseph Saint Luc, Lyon, France
| | - Richard Aziza
- Department of Radiology, Institut Universitaire du Cancer de Toulouse, Toulouse, France
| | | | - Franck Bladou
- Department of Urology, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France
| | - Flavie Bratan
- Department of Diagnostic and Interventional Imaging, Hôpital Saint Joseph Saint Luc, Lyon, France
| | - Serge Brunelle
- Department of Radiology and Medical Imaging, Institut Paoli-Calmettes Cancer Center, Marseille, France
| | - Pierre Colin
- Department of Urology, Hôpital privé La Louvrière, Lille, France
| | - Jean-Michel Correas
- Department of Radiology, Hôpital Necker, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - François Cornud
- Department of Radiology, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Jean-Luc Descotes
- Université Grenoble Alpes, Grenoble, France; Department of Urology, Centre Hospitalier Universitaire de Grenoble, Grenoble, France
| | - Pascal Eschwege
- Department of Urology, Centre Hospitalier Régional et Universitaire de Nancy, Vandoeuvre, France
| | - Gaelle Fiard
- Université Grenoble Alpes, Grenoble, France; Department of Urology, Centre Hospitalier Universitaire de Grenoble, Grenoble, France
| | - Bénédicte Guillaume
- Department of Radiology, Centre Hospitalier Universitaire de Grenoble, Université Grenoble Apes, Grenoble, France
| | - Rémi Grange
- Department of Radiology, University Hospital of Saint-Etienne, Saint-Priest-en-Jarez, France
| | - Nicolas Grenier
- Department of Radiology, Centre Hospitalier Universitaire de Bordeaux, Hôpital Pellegrin, Bordeaux, France
| | - Hervé Lang
- Department of Urology, Centre Hospitalier Universitaire de Strasbourg, Nouvel Hôpital Civil, Strasbourg, France
| | - Frédéric Lefèvre
- Department of Radiology, Centre Hospitalier Régional et Universitaire de Nancy, Vandoeuvre, France
| | - Bernard Malavaud
- Department of Urology, Institut Universitaire du Cancer de Toulouse, Toulouse, France
| | - Clément Marcelin
- Department of Radiology, Centre Hospitalier Universitaire de Bordeaux, Hôpital Pellegrin, Bordeaux, France
| | - Paul C Moldovan
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Nicolas Mottet
- Department of Urology, University Hospital of Saint-Etienne, Saint-Priest-en-Jarez, France
| | - Pierre Mozer
- Department of Urology, Hôpital Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Eric Potiron
- Clinique Urologique de Nantes, Saint-Herblain, France
| | - Daniel Portalez
- Department of Radiology, Institut Universitaire du Cancer de Toulouse, Toulouse, France
| | - Philippe Puech
- Department of Radiology, Centre Hospitalier Régional et Universitaire de Lille, Lille, France
| | - Raphaele Renard-Penna
- Department of Radiology, Hôpital Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, France; GRC no 5, ONCOTYPE-URO, Sorbonne Universités, Paris, France
| | - Matthieu Roumiguié
- Department of Urology, Toulouse-Rangueil University Hospital, Toulouse France
| | - Catherine Roy
- Department of Radiology B, Centre Hospitalier Universitaire de Strasbourg, Nouvel Hôpital Civil, Strasbourg, France
| | - Marc-Olivier Timsit
- Department of Urology, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Thibault Tricard
- Department of Urology, Centre Hospitalier Universitaire de Strasbourg, Nouvel Hôpital Civil, Strasbourg, France
| | - Arnauld Villers
- Department of Urology, Univ. Lille, CHU Lille, Lille, France
| | - Jochen Walz
- Department of Urology, Institut Paoli-Calmettes Cancer Center, Marseille, France
| | - Sabine Debeer
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Adeline Mansuy
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | | | | | - Lionel Badet
- Department of Urology, University Hospital of Saint-Etienne, Saint-Priest-en-Jarez, France; Department of Urology, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France; Université Lyon 1, Université de Lyon, Lyon, France
| | - Marc Colombel
- Department of Urology, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France; Université Lyon 1, Université de Lyon, Lyon, France
| | - Alain Ruffion
- Université Lyon 1, Université de Lyon, Lyon, France; Department of Urology, Centre Hospitalier Lyon Sud, Hospices Cibvils de Lyon, Pierre-Bénite, France
| | - Sébastien Crouzet
- LabTau, INSERM Unit 1032, Lyon, France; Department of Urology, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France; Université Lyon 1, Université de Lyon, Lyon, France
| | - Muriel Rabilloud
- Université Lyon 1, Université de Lyon, Lyon, France; Pôle Santé Publique, Service de Biostatistique et Bioinformatique, Hospices Civils de Lyon, Lyon, France; CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Évolutive, Équipe Biostatistique-Santé, Villeurbanne, France
| | | | - Olivier Rouvière
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France; LabTau, INSERM Unit 1032, Lyon, France; Université Lyon 1, Université de Lyon, Lyon, France.
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Arber T, Jaouen T, Campoy S, Rabilloud M, Souchon R, Abbas F, Moldovan PC, Colombel M, Crouzet S, Ruffion A, Neuville P, Rouvière O. Zone-specific computer-aided diagnosis system aimed at characterizing ISUP ≥ 2 prostate cancers on multiparametric magnetic resonance images: evaluation in a cohort of patients on active surveillance. World J Urol 2023; 41:3527-3533. [PMID: 37845554 DOI: 10.1007/s00345-023-04643-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 09/15/2023] [Indexed: 10/18/2023] Open
Abstract
PURPOSE To assess a region-of-interest-based computer-assisted diagnosis system (CAD) in characterizing aggressive prostate cancer on magnetic resonance imaging (MRI) from patients under active surveillance (AS). METHODS A prospective biopsy database was retrospectively searched for patients under AS who underwent MRI and subsequent biopsy at our institution. MRI lesions targeted at baseline biopsy were retrospectively delineated to calculate the CAD score that was compared to the Prostate Imaging-Reporting and Data System (PI-RADS) version 2 score assigned at baseline biopsy. RESULTS 186 patients were selected. At baseline biopsy, 51 and 15 patients had International Society of Urological Pathology (ISUP) grade ≥ 2 and ≥ 3 cancer respectively. The CAD score had significantly higher specificity for ISUP ≥ 2 cancers (60% [95% confidence interval (CI): 51-68]) than the PI-RADS score (≥ 3 dichotomization: 24% [CI: 17-33], p = 0.0003; ≥ 4 dichotomization: 32% [CI: 24-40], p = 0.0003). It had significantly lower sensitivity than the PI-RADS ≥ 3 dichotomization (85% [CI: 74-92] versus 98% [CI: 91-100], p = 0.015) but not than the PI-RADS ≥ 4 dichotomization (94% [CI:85-98], p = 0.104). Combining CAD findings and PSA density could have avoided 47/184 (26%) baseline biopsies, while missing 3/51 (6%) ISUP 2 and no ISUP ≥ 3 cancers. Patients with baseline negative CAD findings and PSAd < 0.15 ng/mL2 who stayed on AS after baseline biopsy had a 9% (4/44) risk of being diagnosed with ISUP ≥ 2 cancer during a median follow-up of 41 months, as opposed to 24% (18/74) for the others. CONCLUSION The CAD could help define AS patients with low risk of aggressive cancer at baseline assessment and during subsequent follow-up.
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Affiliation(s)
- Théo Arber
- Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre-Bénite, France
| | | | - Séphora Campoy
- Service de Biostatistique Et Bioinformatique, Hospices Civils de Lyon, Pôle Santé Publique, 69003, Lyon, France
- UMR 5558, Laboratoire de Biométrie Et Biologie Évolutive, CNRS, Équipe Biostatistique-Santé, 69100, Villeurbanne, France
| | - Muriel Rabilloud
- Service de Biostatistique Et Bioinformatique, Hospices Civils de Lyon, Pôle Santé Publique, 69003, Lyon, France
- UMR 5558, Laboratoire de Biométrie Et Biologie Évolutive, CNRS, Équipe Biostatistique-Santé, 69100, Villeurbanne, France
- Université de Lyon, Lyon, France
- Université Lyon 1, Lyon, France
| | | | - Fatima Abbas
- Service de Biostatistique Et Bioinformatique, Hospices Civils de Lyon, Pôle Santé Publique, 69003, Lyon, France
- UMR 5558, Laboratoire de Biométrie Et Biologie Évolutive, CNRS, Équipe Biostatistique-Santé, 69100, Villeurbanne, France
| | - Paul C Moldovan
- Department of Radiology, Hospices Civils de Lyon, Hôpital Edouard Herriot, 69437, Lyon, France
| | - Marc Colombel
- Université de Lyon, Lyon, France
- Université Lyon 1, Lyon, France
- Department of Urology, Hospices Civils de Lyon, Hôpital Edouard Herriot, 69437, Lyon, France
- Faculté de Médecine Lyon Est, Lyon, France
| | - Sébastien Crouzet
- LabTau, INSERM U1032, Lyon, France
- Université de Lyon, Lyon, France
- Université Lyon 1, Lyon, France
- Department of Urology, Hospices Civils de Lyon, Hôpital Edouard Herriot, 69437, Lyon, France
- Faculté de Médecine Lyon Est, Lyon, France
| | - Alain Ruffion
- Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre-Bénite, France
- Université de Lyon, Lyon, France
- Université Lyon 1, Lyon, France
- Faculté de Médecine Lyon Sud, Pierre Bénite, France
| | - Paul Neuville
- Department of Urology, Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Pierre-Bénite, France
| | - Olivier Rouvière
- LabTau, INSERM U1032, Lyon, France.
- Université de Lyon, Lyon, France.
- Université Lyon 1, Lyon, France.
- Department of Radiology, Hospices Civils de Lyon, Hôpital Edouard Herriot, 69437, Lyon, France.
- Faculté de Médecine Lyon Est, Lyon, France.
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Jaouen T, Souchon R, Moldovan PC, Bratan F, Duran A, Hoang-Dinh A, Di Franco F, Debeer S, Dubreuil-Chambardel M, Arfi N, Ruffion A, Colombel M, Crouzet S, Gonindard-Melodelima C, Rouvière O. Characterization of high-grade prostate cancer at multiparametric MRI using a radiomic-based computer-aided diagnosis system as standalone and second reader. Diagn Interv Imaging 2023; 104:465-476. [PMID: 37345961 DOI: 10.1016/j.diii.2023.04.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/16/2023] [Accepted: 04/18/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE The purpose of this study was to develop and test across various scanners a zone-specific region-of-interest (ROI)-based computer-aided diagnosis system (CAD) aimed at characterizing, on MRI, International Society of Urological Pathology (ISUP) grade≥2 prostate cancers. MATERIALS AND METHODS ROI-based quantitative models were selected in multi-vendor training (265 pre-prostatectomy MRIs) and pre-test (112 pre-biopsy MRIs) datasets. The best peripheral and transition zone models were combined and retrospectively assessed in internal (158 pre-biopsy MRIs) and external (104 pre-biopsy MRIs) test datasets. Two radiologists (R1/R2) retrospectively delineated the lesions targeted at biopsy in test datasets. The CAD area under the receiver operating characteristic curve (AUC) for characterizing ISUP≥2 cancers was compared to that of the Prostate Imaging-Reporting and Data System version2 (PI-RADSv2) score prospectively assigned to targeted lesions. RESULTS The best models used the 25th apparent diffusion coefficient (ADC) percentile in transition zone and the 2nd ADC percentile and normalized wash-in rate in peripheral zone. The PI-RADSv2 AUCs were 82% (95% confidence interval [CI]: 74-87) and 86% (95% CI: 81-91) in the internal and external test datasets respectively. They were not different from the CAD AUCs obtained with R1 and R2 delineations, in the internal (82% [95% CI: 76-89], P = 0.95 and 85% [95% CI: 78-91], P = 0.55) and external (82% [95% CI: 74-91], P = 0.41 and 86% [95% CI:78-95], P = 0.98) test datasets. The CAD yielded sensitivities of 86-89% and 90-91%, and specificities of 64-65% and 69-75% in the internal and external test datasets respectively. CONCLUSION The CAD performance for characterizing ISUP grade≥2 prostate cancers on MRI is not different from that of PI-RADSv2 score across two test datasets.
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Affiliation(s)
| | | | - Paul C Moldovan
- Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Vascular and Urinary Imaging, Lyon, 69003, France
| | - Flavie Bratan
- Hôpital Saint Joseph Saint Luc, Department of Radiology, Lyon, 69007, France
| | - Audrey Duran
- Univ Lyon, CNRS, Inserm, INSA Lyon, UCBL, CREATIS, UMR5220, U1294, Villeurbanne, 69100, France
| | - Au Hoang-Dinh
- INSERM, LabTAU, U1032, Lyon, 69003, France; Hanoi Medical University, Department of Radiology, Hanoi, 116001, Vietnam
| | - Florian Di Franco
- Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Vascular and Urinary Imaging, Lyon, 69003, France
| | - Sabine Debeer
- Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Vascular and Urinary Imaging, Lyon, 69003, France
| | - Marine Dubreuil-Chambardel
- Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Vascular and Urinary Imaging, Lyon, 69003, France
| | - Nicolas Arfi
- Hôpital Saint Joseph Saint Luc, Department of Urology, Lyon, 69007, France
| | - Alain Ruffion
- Hospices Civils de Lyon, Centre Hospitalier Lyon Sud, Department of Urology, Pierre-Bénite, 69310, France; Equipe 2 - Centre d'Innovation en Cancérologie de Lyon (EA 3738 CICLY), Pierre-Bénite, 69310, France; Université de Lyon, Lyon, 69003, France; Université Lyon 1, Lyon, 69003, France; Faculté de Médecine Lyon Sud, Pierre-Bénite, 69310, France
| | - Marc Colombel
- Université de Lyon, Lyon, 69003, France; Université Lyon 1, Lyon, 69003, France; Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Urology, Lyon, 69003, France; Faculté de Médecine Lyon Est, Lyon, 69003, France
| | - Sébastien Crouzet
- INSERM, LabTAU, U1032, Lyon, 69003, France; Université de Lyon, Lyon, 69003, France; Université Lyon 1, Lyon, 69003, France; Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Urology, Lyon, 69003, France; Faculté de Médecine Lyon Est, Lyon, 69003, France
| | - Christelle Gonindard-Melodelima
- Université Grenoble Alpes, Laboratoire d'Ecologie Alpine, BP 53, Grenoble 38041, France; CNRS, UMR 5553, BP 53, Grenoble, 38041, France
| | - Olivier Rouvière
- INSERM, LabTAU, U1032, Lyon, 69003, France; Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Vascular and Urinary Imaging, Lyon, 69003, France; Université de Lyon, Lyon, 69003, France; Université Lyon 1, Lyon, 69003, France; Faculté de Médecine Lyon Est, Lyon, 69003, France.
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Jaouen T, Pulkkinen A, Rumo M, Kremer G, Salzmann B, Nicholson CW, Mottas ML, Giannini E, Tricot S, Schieffer P, Hildebrand B, Monney C. Carrier-Density Control of the Quantum-Confined 1T-TiSe_{2} Charge Density Wave. Phys Rev Lett 2023; 130:226401. [PMID: 37327408 DOI: 10.1103/physrevlett.130.226401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 05/10/2023] [Indexed: 06/18/2023]
Abstract
Using angle-resolved photoemission spectroscopy, combined with first principle and coupled self-consistent Poisson-Schrödinger calculations, we demonstrate that potassium (K) atoms adsorbed on the low-temperature phase of 1T-TiSe_{2} induce the creation of a two-dimensional electron gas (2DEG) and quantum confinement of its charge-density wave (CDW) at the surface. By further changing the K coverage, we tune the carrier density within the 2DEG that allows us to nullify, at the surface, the electronic energy gain due to exciton condensation in the CDW phase while preserving a long-range structural order. Our Letter constitutes a prime example of a controlled exciton-related many-body quantum state in reduced dimensionality by alkali-metal dosing.
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Affiliation(s)
- T Jaouen
- Univ Rennes, CNRS, (IPR Institut de Physique de Rennes)-UMR 6251, F-35000 Rennes, France
| | - A Pulkkinen
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
- New Technologies Research Centre, University of West Bohemia, CZ-30100 Pilsen, Czech Republic
| | - M Rumo
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
- Haute école d'ingénierie et d'architecture de Fribourg, CH-1700 Fribourg, Switzerland
| | - G Kremer
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
- Institut Jean Lamour, UMR 7198, CNRS-Université de Lorraine, Campus ARTEM, 2 allée André Guinier, BP 50840, 54011 Nancy, France
| | - B Salzmann
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - C W Nicholson
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
- Fritz-Haber-Institute der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
| | - M-L Mottas
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - E Giannini
- Department of Quantum Matter Physics, University of Geneva, 24 Quai Ernest-Ansermet, 1211 Geneva 4, Switzerland
| | - S Tricot
- Univ Rennes, CNRS, (IPR Institut de Physique de Rennes)-UMR 6251, F-35000 Rennes, France
| | - P Schieffer
- Univ Rennes, CNRS, (IPR Institut de Physique de Rennes)-UMR 6251, F-35000 Rennes, France
| | - B Hildebrand
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - C Monney
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
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Rouvière O, Jaouen T, Baseilhac P, Benomar ML, Escande R, Crouzet S, Souchon R. Artificial intelligence algorithms aimed at characterizing or detecting prostate cancer on MRI: How accurate are they when tested on independent cohorts? – A systematic review. Diagn Interv Imaging 2022; 104:221-234. [PMID: 36517398 DOI: 10.1016/j.diii.2022.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 11/22/2022] [Indexed: 12/14/2022]
Abstract
PURPOSE The purpose of this study was to perform a systematic review of the literature on the diagnostic performance, in independent test cohorts, of artificial intelligence (AI)-based algorithms aimed at characterizing/detecting prostate cancer on magnetic resonance imaging (MRI). MATERIALS AND METHODS Medline, Embase and Web of Science were searched for studies published between January 2018 and September 2022, using a histological reference standard, and assessing prostate cancer characterization/detection by AI-based MRI algorithms in test cohorts composed of more than 40 patients and with at least one of the following independency criteria as compared to the training cohort: different institution, different population type, different MRI vendor, different magnetic field strength or strict temporal splitting. RESULTS Thirty-five studies were selected. The overall risk of bias was low. However, 23 studies did not use predefined diagnostic thresholds, which may have optimistically biased the results. Test cohorts fulfilled one to three of the five independency criteria. The diagnostic performance of the algorithms used as standalones was good, challenging that of human reading. In the 12 studies with predefined diagnostic thresholds, radiomics-based computer-aided diagnosis systems (assessing regions-of-interest drawn by the radiologist) tended to provide more robust results than deep learning-based computer-aided detection systems (providing probability maps). Two of the six studies comparing unassisted and assisted reading showed significant improvement due to the algorithm, mostly by reducing false positive findings. CONCLUSION Prostate MRI AI-based algorithms showed promising results, especially for the relatively simple task of characterizing predefined lesions. The best management of discrepancies between human reading and algorithm findings still needs to be defined.
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Affiliation(s)
- Olivier Rouvière
- Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Vascular and Urinary Imaging, Lyon 69003, France; Université Lyon 1, Faculté de médecine Lyon Est, Lyon 69003, France; LabTAU, INSERM, U1032, Lyon 69003, France.
| | | | - Pierre Baseilhac
- Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Vascular and Urinary Imaging, Lyon 69003, France
| | - Mohammed Lamine Benomar
- LabTAU, INSERM, U1032, Lyon 69003, France; University of Ain Temouchent, Faculty of Science and Technology, Algeria
| | - Raphael Escande
- Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Vascular and Urinary Imaging, Lyon 69003, France
| | - Sébastien Crouzet
- Université Lyon 1, Faculté de médecine Lyon Est, Lyon 69003, France; LabTAU, INSERM, U1032, Lyon 69003, France; Hospices Civils de Lyon, Hôpital Edouard Herriot, Department of Urology, Lyon 69003, France
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Rouvière O, Souchon R, Lartizien C, Mansuy A, Magaud L, Colom M, Dubreuil-Chambardel M, Debeer S, Jaouen T, Duran A, Rippert P, Riche B, Monini C, Vlaeminck-Guillem V, Haesebaert J, Rabilloud M, Crouzet S. Detection of ISUP ≥2 prostate cancers using multiparametric MRI: prospective multicentre assessment of the non-inferiority of an artificial intelligence system as compared to the PI-RADS V.2.1 score (CHANGE study). BMJ Open 2022; 12:e051274. [PMID: 35140147 PMCID: PMC8830410 DOI: 10.1136/bmjopen-2021-051274] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
INTRODUCTION Prostate multiparametric MRI (mpMRI) has shown good sensitivity in detecting cancers with an International Society of Urological Pathology (ISUP) grade of ≥2. However, it lacks specificity, and its inter-reader reproducibility remains moderate. Biomarkers, such as the Prostate Health Index (PHI), may help select patients for prostate biopsy. Computer-aided diagnosis/detection (CAD) systems may also improve mpMRI interpretation. Different prototypes of CAD systems are currently developed under the Recherche Hospitalo-Universitaire en Santé / Personalized Focused Ultrasound Surgery of Localized Prostate Cancer (RHU PERFUSE) research programme, tackling challenging issues such as robustness across imaging protocols and magnetic resonance (MR) vendors, and ability to characterise cancer aggressiveness. The study primary objective is to evaluate the non-inferiority of the area under the receiver operating characteristic curve of the final CAD system as compared with the Prostate Imaging-Reporting and Data System V.2.1 (PI-RADS V.2.1) in predicting the presence of ISUP ≥2 prostate cancer in patients undergoing prostate biopsy. METHODS This prospective, multicentre, non-inferiority trial will include 420 men with suspected prostate cancer, a prostate-specific antigen level of ≤30 ng/mL and a clinical stage ≤T2 c. Included men will undergo prostate mpMRI that will be interpreted using the PI-RADS V.2.1 score. Then, they will undergo systematic and targeted biopsy. PHI will be assessed before biopsy. At the end of patient inclusion, MR images will be assessed by the final version of the CAD system developed under the RHU PERFUSE programme. Key secondary outcomes include the prediction of ISUP grade ≥2 prostate cancer during a 3-year follow-up, and the number of biopsy procedures saved and ISUP grade ≥2 cancers missed by several diagnostic pathways combining PHI and MRI findings. ETHICS AND DISSEMINATION Ethical approval was obtained from the Comité de Protection des Personnes Nord Ouest III (ID-RCB: 2020-A02785-34). After publication of the results, access to MR images will be possible for testing other CAD systems. TRIAL REGISTRATION NUMBER NCT04732156.
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Affiliation(s)
- Olivier Rouvière
- Université Lyon 1, Université de Lyon, Lyon, France
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
- LabTau, INSERM U1032, Lyon, France
| | | | - Carole Lartizien
- CREATIS, INSERM U1294, Villeurbanne, France
- CNRS UMR 5220, INSA-Lyon, Villeurbanne, France
| | - Adeline Mansuy
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Laurent Magaud
- Service Recherche et Epidémiologie Cliniques, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France
| | - Matthieu Colom
- Direction de la Recherche Clinique et de l'Innovation, Hospices Civils de Lyon, Lyon, France
| | - Marine Dubreuil-Chambardel
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Sabine Debeer
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
| | | | - Audrey Duran
- CREATIS, INSERM U1294, Villeurbanne, France
- CNRS UMR 5220, INSA-Lyon, Villeurbanne, France
| | - Pascal Rippert
- Service Recherche et Epidémiologie Cliniques, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France
| | - Benjamin Riche
- Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France
- Laboratoire de Biométrie et Biologie Évolutive CNRS UMR 5558, Équipe Biostatistiques Santé, Université de Lyon, Lyon, France
| | | | - Virginie Vlaeminck-Guillem
- Université Lyon 1, Université de Lyon, Lyon, France
- Service de Biochimie et Biologie Moléculaire Sud, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France
| | - Julie Haesebaert
- Université Lyon 1, Université de Lyon, Lyon, France
- Service Recherche et Epidémiologie Cliniques, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France
- Research on Healthcare Performance (RESHAPE), INSERM U1290, Lyon, France
| | - Muriel Rabilloud
- Université Lyon 1, Université de Lyon, Lyon, France
- Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France
- Laboratoire de Biométrie et Biologie Évolutive CNRS UMR 5558, Équipe Biostatistiques Santé, Université de Lyon, Lyon, France
| | - Sébastien Crouzet
- Université Lyon 1, Université de Lyon, Lyon, France
- LabTau, INSERM U1032, Lyon, France
- Department of Urology, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
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Duran A, Dussert G, Rouviére O, Jaouen T, Jodoin PM, Lartizien C. ProstAttention-Net: a deep attention model for prostate cancer segmentation by aggressiveness in MRI scans. Med Image Anal 2022; 77:102347. [DOI: 10.1016/j.media.2021.102347] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 12/20/2021] [Accepted: 12/31/2021] [Indexed: 11/27/2022]
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Naudin S, Li K, Jaouen T, Assi N, Kyrø C, Tjønneland A, Overvad K, Boutron-Ruault MC, Rebours V, Védié AL, Boeing H, Kaaks R, Katzke V, Bamia C, Naska A, Trichopoulou A, Berrino F, Tagliabue G, Palli D, Panico S, Tumino R, Sacerdote C, Peeters PH, Bueno-de-Mesquita B, Weiderpass E, Gram IT, Skeie G, Chirlaque MD, Rodríguez-Barranco M, Barricarte A, Quirós J, Dorronsoro M, Johansson I, Sund M, Sternby H, Bradbury KE, Wareham N, Riboli E, Gunter M, Brennan P, Duell EJ, Ferrari P. Lifetime and baseline alcohol intakes and risk of pancreatic cancer in the European Prospective Investigation into Cancer and Nutrition study. Int J Cancer 2018; 143:801-812. [PMID: 29524225 PMCID: PMC6481554 DOI: 10.1002/ijc.31367] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 01/18/2018] [Accepted: 02/02/2018] [Indexed: 02/06/2023]
Abstract
Recent evidence suggested a weak relationship between alcohol consumption and pancreatic cancer (PC) risk. In our study, the association between lifetime and baseline alcohol intakes and the risk of PC was evaluated, including the type of alcoholic beverages and potential interaction with smoking. Within the European Prospective Investigation into Cancer and Nutrition (EPIC) study, 1,283 incident PC (57% women) were diagnosed from 476,106 cancer-free participants, followed up for 14 years. Amounts of lifetime and baseline alcohol were estimated through lifestyle and dietary questionnaires, respectively. Cox proportional hazard models with age as primary time variable were used to estimate PC hazard ratios (HR) and their 95% confidence interval (CI). Alcohol intake was positively associated with PC risk in men. Associations were mainly driven by extreme alcohol levels, with HRs comparing heavy drinkers (>60 g/day) to the reference category (0.1-4.9 g/day) equal to 1.77 (95% CI: 1.06, 2.95) and 1.63 (95% CI: 1.16, 2.29) for lifetime and baseline alcohol, respectively. Baseline alcohol intakes from beer (>40 g/day) and spirits/liquors (>10 g/day) showed HRs equal to 1.58 (95% CI: 1.07, 2.34) and 1.41 (95% CI: 1.03, 1.94), respectively, compared to the reference category (0.1-2.9 g/day). In women, HR estimates did not reach statistically significance. The alcohol and PC risk association was not modified by smoking status. Findings from a large prospective study suggest that baseline and lifetime alcohol intakes were positively associated with PC risk, with more apparent risk estimates for beer and spirits/liquors than wine intake.
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Affiliation(s)
- Sabine Naudin
- Nutritional Methodology and Biostatistics group, International Agency for Research on Cancer, Lyon, France
| | - Kuanrong Li
- Nutritional Methodology and Biostatistics group, International Agency for Research on Cancer, Lyon, France
| | - Tristan Jaouen
- Nutritional Methodology and Biostatistics group, International Agency for Research on Cancer, Lyon, France
| | - Nada Assi
- Nutritional Methodology and Biostatistics group, International Agency for Research on Cancer, Lyon, France
| | - Cecilie Kyrø
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | | | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Marie-Christine Boutron-Ruault
- CESP, INSERM U1018, University of Paris-Sud, UVSQ, University of Paris-Saclay, Villejuif, France
- Institut Gustave Roussy, Villejuif, France
| | - Vinciane Rebours
- Pancreatology Unit, Beaujon Hospital, Clichy, France, INSERM U1149, University Paris 7, Paris, France
| | - Anne-Laure Védié
- Pancreatology Unit, Beaujon Hospital, Clichy, France, INSERM U1149, University Paris 7, Paris, France
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Postdam, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Christina Bamia
- Hellenic Health Foundation, Athens, Greece
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Greece
| | - Androniki Naska
- Hellenic Health Foundation, Athens, Greece
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Greece
| | - Antonia Trichopoulou
- Hellenic Health Foundation, Athens, Greece
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Greece
| | - Franco Berrino
- Department of Preventive & Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Giovanna Tagliabue
- Lombardy Cancer Registry Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Domenico Palli
- Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute (ISPO), Florence, Italy
| | - Salvatore Panico
- Department of Clinical and Experimental Medecine, University Federico II, Naples, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Civic M.P.Arezzo Hospital, Ragusa, Italy, Ragusa, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University, Hospital and Center for Cancer Prevention (CPO), Turin, Italy
| | - Petra H. Peeters
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Bas Bueno-de-Mesquita
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Elisabete Weiderpass
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
- Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Genetic Epidemiology Group, Folkhälsan Research Center, Helsinki, Finland
| | - Inger Torhild Gram
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
| | - Guri Skeie
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
| | - Maria-Dolores Chirlaque
- Department of Epidemiology, Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Health and Social Sciences, University of Murcia, Murcia, Spain
| | - Miguel Rodríguez-Barranco
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Biosanitary Investigation Institute (IBS) of Granada, University Hospital and University of Granada, Granada, Spain
| | - Aurelio Barricarte
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Navarra Public Health Institute, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | | | - Miren Dorronsoro
- Subdirección de Salud Pública de Gipuzkoa, Gobierno Vasco, San Sebastian, Spain
| | | | - Malin Sund
- Department of Surgical and Perioperative Sciences, Umeå University, Umeå, Sweden
| | - Hanna Sternby
- Department of Surgery, Institution of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Kathryn E Bradbury
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Nick Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Elio Riboli
- School of Public Health, Imperial College London, United Kingdom
| | - Marc Gunter
- Nutrition and Epidemiology group, International Agency for Research on Cancer, Lyon, France
| | - Paul Brennan
- Genetic Epidemiology group, International Agency for Research on Cancer, Lyon, France
| | - Eric J Duell
- Unit of Nutrition and Cancer, Catalan Institute of Oncology (ICO-Idibell), Barcelona, Spain
| | - Pietro Ferrari
- Nutritional Methodology and Biostatistics group, International Agency for Research on Cancer, Lyon, France
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Hildebrand B, Jaouen T, Mottas ML, Monney G, Barreteau C, Giannini E, Bowler DR, Aebi P. Local Real-Space View of the Achiral 1T-TiSe_{2} 2×2×2 Charge Density Wave. Phys Rev Lett 2018; 120:136404. [PMID: 29694190 DOI: 10.1103/physrevlett.120.136404] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Indexed: 06/08/2023]
Abstract
The transition metal dichalcogenide 1T-TiSe_{2}-two-dimensional layered material undergoing a commensurate 2×2×2 charge density wave (CDW) transition with a weak periodic lattice distortion (PLD) below ≈200 K. Scanning tunneling microscopy (STM) combined with intentionally introduced interstitial Ti atoms allows us to go beyond the usual spatial resolution of STM and to intimately probe the three-dimensional character of the PLD. Furthermore, the inversion-symmetric achiral nature of the CDW in the z direction is revealed, contradicting the claimed existence of helical CDW stacking and associated chiral order. This study paves the way to a simultaneous real-space probing of both charge and structural reconstructions in CDW compounds.
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Affiliation(s)
- B Hildebrand
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - T Jaouen
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - M-L Mottas
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - G Monney
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - C Barreteau
- Department of Quantum Matter Physics, University of Geneva, 24 Quai Ernest-Ansermet, 1211 Geneva 4, Switzerland
| | - E Giannini
- Department of Quantum Matter Physics, University of Geneva, 24 Quai Ernest-Ansermet, 1211 Geneva 4, Switzerland
| | - D R Bowler
- London Centre for Nanotechnology and Department of Physics and Astronomy, University College London, London WC1E 6BT, United Kingdom
| | - P Aebi
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
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Razzoli E, Jaouen T, Mottas ML, Hildebrand B, Monney G, Pisoni A, Muff S, Fanciulli M, Plumb NC, Rogalev VA, Strocov VN, Mesot J, Shi M, Dil JH, Beck H, Aebi P. Selective Probing of Hidden Spin-Polarized States in Inversion-Symmetric Bulk MoS_{2}. Phys Rev Lett 2017; 118:086402. [PMID: 28282191 DOI: 10.1103/physrevlett.118.086402] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Indexed: 06/06/2023]
Abstract
Spin- and angle-resolved photoemission spectroscopy is used to reveal that a large spin polarization is observable in the bulk centrosymmetric transition metal dichalcogenide MoS_{2}. It is found that the measured spin polarization can be reversed by changing the handedness of incident circularly polarized light. Calculations based on a three-step model of photoemission show that the valley and layer-locked spin-polarized electronic states can be selectively addressed by circularly polarized light, therefore providing a novel route to probe these hidden spin-polarized states in inversion-symmetric systems as predicted by Zhang et al. [Nat. Phys. 10, 387 (2014).NPAHAX1745-247310.1038/nphys2933].
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Affiliation(s)
- E Razzoli
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - T Jaouen
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - M-L Mottas
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - B Hildebrand
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - G Monney
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - A Pisoni
- Laboratory of Physics of Complex Matter, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - S Muff
- Swiss Light Source, Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland
- Institute of Physics, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - M Fanciulli
- Swiss Light Source, Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland
- Institute of Physics, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - N C Plumb
- Swiss Light Source, Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland
| | - V A Rogalev
- Swiss Light Source, Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland
| | - V N Strocov
- Swiss Light Source, Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland
| | - J Mesot
- Swiss Light Source, Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland
- Institute of Physics, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
- Laboratory for Solid State Physics, ETH Zürich, CH-8093 Zürich, Switzerland
| | - M Shi
- Swiss Light Source, Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland
| | - J H Dil
- Swiss Light Source, Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland
- Institute of Physics, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - H Beck
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
| | - P Aebi
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland
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Jaouen T, Tricot S, Delhaye G, Lépine B, Sébilleau D, Jézéquel G, Schieffer P. Layer-resolved study of Mg atom incorporation at the MgO/Ag(001) buried interface. Phys Rev Lett 2013; 111:027601. [PMID: 23889444 DOI: 10.1103/physrevlett.111.027601] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2013] [Indexed: 06/02/2023]
Abstract
By combining x-ray excited Auger electron diffraction experiments and multiple scattering calculations we reveal a layer-resolved shift for the Mg KL23L23 Auger transition in MgO ultrathin films (4-6 Å) on Ag(001). This resolution is exploited to demonstrate the possibility of controlling Mg atom incorporation at the MgO/Ag(001) interface by exposing the MgO films to a Mg flux. A substantial reduction of the MgO/Ag(001) work function is observed during the exposition phase and reflects both band-offset variations at the interface and band bending effects in the oxide film.
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Affiliation(s)
- T Jaouen
- Département de Physique and Fribourg Center for Nanomaterials, Université de Fribourg, CH-1700 Fribourg, Switzerland.
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