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Li Pomi F, Papa V, Borgia F, Vaccaro M, Pioggia G, Gangemi S. Artificial Intelligence: A Snapshot of Its Application in Chronic Inflammatory and Autoimmune Skin Diseases. Life (Basel) 2024; 14:516. [PMID: 38672786 PMCID: PMC11051135 DOI: 10.3390/life14040516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/10/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Immuno-correlated dermatological pathologies refer to skin disorders that are closely associated with immune system dysfunction or abnormal immune responses. Advancements in the field of artificial intelligence (AI) have shown promise in enhancing the diagnosis, management, and assessment of immuno-correlated dermatological pathologies. This intersection of dermatology and immunology plays a pivotal role in comprehending and addressing complex skin disorders with immune system involvement. The paper explores the knowledge known so far and the evolution and achievements of AI in diagnosis; discusses segmentation and the classification of medical images; and reviews existing challenges, in immunological-related skin diseases. From our review, the role of AI has emerged, especially in the analysis of images for both diagnostic and severity assessment purposes. Furthermore, the possibility of predicting patients' response to therapies is emerging, in order to create tailored therapies.
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Affiliation(s)
- Federica Li Pomi
- Department of Precision Medicine in Medical, Surgical and Critical Care (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy;
| | - Vincenzo Papa
- Department of Clinical and Experimental Medicine, School and Operative Unit of Allergy and Clinical Immunology, University of Messina, 98125 Messina, Italy; (V.P.); (S.G.)
| | - Francesco Borgia
- Department of Clinical and Experimental Medicine, Section of Dermatology, University of Messina, 98125 Messina, Italy;
| | - Mario Vaccaro
- Department of Clinical and Experimental Medicine, Section of Dermatology, University of Messina, 98125 Messina, Italy;
| | - Giovanni Pioggia
- Institute for Biomedical Research and Innovation (IRIB), National Research Council of Italy (CNR), 98164 Messina, Italy;
| | - Sebastiano Gangemi
- Department of Clinical and Experimental Medicine, School and Operative Unit of Allergy and Clinical Immunology, University of Messina, 98125 Messina, Italy; (V.P.); (S.G.)
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Factors Associated With Ultrasound Color Doppler Twinkling by Breast Biopsy Markers: In Vitro and Ex Vivo Evaluation of 35 Commercially Available Markers. AJR Am J Roentgenol 2023; 220:358-370. [PMID: 36043610 DOI: 10.2214/ajr.22.28107] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
BACKGROUND. Targeted axillary lymph node dissection after neoadjuvant systemic therapy (NST) for breast cancer depends on identifying marked metastatic lymph nodes. However, ultrasound visualization of biopsy markers is challenging. OBJECTIVE. The purpose of our study was to identify biopsy markers that show actionable twinkling in cadaveric breast and to assess the association of actionable twinkling with markers' surface roughness. METHODS. Commercial breast biopsy markers were evaluated for twinkling artifact in various experimental conditions relating to scanning medium (solid gel phantom, ultrasound coupling gel, cadaveric breast), transducer (ML6-15, 9L, C1-6), and embedding material (present vs absent). Markers were assigned twinkling scores from 0 (confident in no twinkling) to 4 (confident in exuberant twinkling); a score of 3 or greater represented actionable twinkling (sufficient confidence to rely solely on twinkling for target localization). Markers were hierarchically advanced to evaluation with increasingly complex media if showing at least minimal twinkling for a given medium. A 3D coherence optical profiler measured marker surface roughness. Mixed-effects proportional odds regression models assessed associations between twinkling scores and transducer and embedding material; Wilcoxon rank sum test evaluated associations between actionable twinkling and surface roughness. RESULTS. Thirty-five markers (21 with embedding material) were evaluated. Ten markers without embedding material advanced to evaluation in cadaveric breast. Higher twinkling scores were associated with presence of embedding material (odds ratio [OR] = 5.05 in solid gel phantom, 9.84 in coupling gel) and transducer (using the C1-6 transducer as reference; 9L transducer: OR = 0.36, 0.83, and 0.04 in solid gel phantom, ultrasound coupling gel, and cadaveric breast; ML6-15 transducer: OR = 0.07, 0.18, and 0.00 respectively; post hoc p between 9L and ML6-15: p < .001, p = .02, and p = .04). In cadaveric breast, three markers (Cork, Professional Q, MRI [Flex]) exhibited actionable twinkling for two or more transducers; surface roughness was significantly higher for markers with than without actionable twinkling for C1-6 (median values: 0.97 vs 0.35, p = .02) and 9L (1.75 vs 0.36; p = .002) transducers. CONCLUSION. Certain breast biopsy markers exhibited actionable twinkling in cadaveric breast. Twinkling was observed with greater confidence for the C1-6 and 9L transducers than the ML6-15 transducer. Actionable twinkling was associated with higher marker surface roughness. CLINICAL IMPACT. Use of twinkling for marker detection could impact preoperative or intraoperative localization after NST.
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Lee CU, Urban MW, Lee Miller A, Uthamaraj S, Jakub JW, Hesley GK, Wood BG, Brinkman NJ, Herrick JL, Larson NB, Yaszemski MJ, Greenleaf JF. Twinkling-guided ultrasound detection of polymethyl methacrylate as a potential breast biopsy marker: a comparative investigation. Eur Radiol Exp 2022; 6:26. [PMID: 35711010 PMCID: PMC9203632 DOI: 10.1186/s41747-022-00283-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 04/22/2022] [Indexed: 11/10/2022] Open
Abstract
Since its first description 25 years ago, color Doppler twinkling has been a compelling ultrasound feature in diagnosing urinary stones. While the fundamental cause of twinkling remains elusive, the distinctive twinkling signature is diagnostically valuable in clinical practice. It can be inferred that if an entity twinkles, it empirically has certain physical features. This work investigates a manipulable polymeric material, polymethyl methacrylate (PMMA), which twinkles and has measurable surface roughness and porosity that likely contribute to twinkling. Comparative investigation of these structural properties and of the twinkling signatures of breast biopsy markers made from PMMA and selected commercially available markers showed how twinkling can improve ultrasound detection of devices intentionally designed to twinkle. While this specific application of detecting breast biopsy markers by twinkling may provide a way to approach an unmet need in the care of patients with breast cancer, this work ultimately provides a platform from which the keys to unlocking the fundamental physics of twinkling can be rigorously explored.
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Affiliation(s)
- Christine U Lee
- Department of Radiology, Division of Breast Imaging and Intervention, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA.
| | - Matthew W Urban
- Department of Radiology, Division of Radiology Research, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA.,Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - A Lee Miller
- Department of Orthopedic Surgery, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - Susheil Uthamaraj
- Division of Engineering, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - James W Jakub
- Department of Surgery, Division of Surgical Oncology, Mayo Clinic, 4500 San Pablo Rd, Jacksonville, FL, 32224, USA
| | - Gina K Hesley
- Department of Radiology, Division of Breast Imaging and Intervention, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - Benjamin G Wood
- Mayo Graduate School of Biomedical Sciences, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - Nathan J Brinkman
- Department of Pharmacy, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - James L Herrick
- Department of Orthopedic Surgery, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - Nicholas B Larson
- Department of Quantitative Health Sciences, Division of Clinical Trials and Biostatistics, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - Michael J Yaszemski
- Department of Orthopedic Surgery, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
| | - James F Greenleaf
- Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 First St, SW, Rochester, MN, 55905, USA
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Lee CU, Hesley GK, Uthamaraj S, Larson NB, Greenleaf JF, Urban MW. Using Ultrasound Color Doppler Twinkling to Identify Biopsy Markers in the Breast and Axilla. ULTRASOUND IN MEDICINE & BIOLOGY 2021; 47:3122-3134. [PMID: 34412903 DOI: 10.1016/j.ultrasmedbio.2021.04.018] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 03/16/2021] [Accepted: 04/15/2021] [Indexed: 06/13/2023]
Abstract
In breast radiology, ultrasound detection of biopsy markers or clips for localization purposes is often challenging, especially in the axilla. The purpose of this research was to test the hypothesis that the surface roughness of biopsy clips would elicit a twinkling signature on color Doppler, making them more readily identifiable by ultrasound. Ultrasound color Doppler imaging of 12 biopsy markers was performed and consensus scoring of the degree of twinkling (0 [no twinkling] to 4 [exuberant twinkling]) was obtained for each of the markers. The surface roughness characteristics of the markers were measured using 3-D coherence scanning interferometry. The 3 markers scoring at least 3 for twinkling in vitro were cork, Q and Vision. Of these 3 markers, only the cork marker scored a 4 ex vivo and in cadaveric tissue. Surface roughness metrics demonstrated a positive estimated correlation with the twinkling scores (rho = 0.33, 95% CI = [-0.48 to 0.84]). Of the 12 markers tested, the markers that twinkled corresponded to surface roughness measured with non-contact 3-D optical imaging. Qualitatively, lower color scales and color frequencies optimized twinkling, but the most specific qualitative predictor of confidence in twinkling was insensitivity to changes in color scale and color frequency values.
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Affiliation(s)
- Christine U Lee
- Department of Radiology, Breast Imaging and Intervention Division, Mayo Clinic, Rochester, MN, USA.
| | - Gina K Hesley
- Department of Radiology, Breast Imaging and Intervention Division, Mayo Clinic, Rochester, MN, USA
| | | | - Nicholas B Larson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - James F Greenleaf
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Matthew W Urban
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA; Department of Radiology, Division of Radiology Research, Mayo Clinic, Rochester, MN, USA
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Scientific validation of three-dimensional stereophotogrammetry compared to the IGAIS clinical scale for assessing wrinkles and scars after laser treatment. Sci Rep 2021; 11:12385. [PMID: 34117340 PMCID: PMC8196213 DOI: 10.1038/s41598-021-91922-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 06/01/2021] [Indexed: 11/08/2022] Open
Abstract
Measuring outcomes from treatments to the skin is either reliant upon patient’s subjective feedback or scale-based peer assessments. Three-Dimensional stereophotogrammetry intend to accurately quantify skin microtopography before and after treatments. The objective of this study is comparing the accuracy of stereophotogrammetry with a scale-based peer evaluation in assessing topographical changes to skin surface following laser treatment. A 3D stereophotogrammetry system photographed skin surface of 48 patients with facial wrinkles or scars before and three months after laser resurfacing, followed immediately by topical application of vitamin C. The software measured changes in skin roughness, wrinkle depth and scar volume. Images were presented to three observers, each independently scoring cutaneous improvement according to Investigator Global Aesthetic Improvement Scale (IGAIS). As for the results, a trend reflecting skin/scar improvement was reported by 3D SPM measurements and raters. The percentage of topographical change given by the raters matched 3D SPM findings. Agreement was highest when observers analysed 3D images. However, observers overestimated skin improvement in a nontreatment control whilst 3D SPM was precise in detecting absence of intervention. This study confirmed a direct correlation between the IGAIS clinical scale and 3D SPM and confirmed the efficacy and accuracy of the latter when assessing cutaneous microtopography alterations as a response to laser treatment.
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Yu K, Syed MN, Bernardis E, Gelfand JM. Machine Learning Applications in the Evaluation and Management of Psoriasis: A Systematic Review. ACTA ACUST UNITED AC 2021; 5:147-159. [PMID: 33733038 PMCID: PMC7963214 DOI: 10.1177/2475530320950267] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background Machine learning (ML), a subset of artificial intelligence (AI) that aims to teach machines to automatically learn tasks by inferring patterns from data, holds significant promise to aid psoriasis care. Applications include evaluation of skin images for screening and diagnosis as well as clinical management including treatment and complication prediction. Objective To summarize literature on ML applications to psoriasis evaluation and management and to discuss challenges and opportunities for future advances. Methods We searched MEDLINE, Google Scholar, ACM Digital Library, and IEEE Xplore for peer-reviewed publications published in English through December 1, 2019. Our search queries identified publications with any of the 10 computing-related keywords and "psoriasis" in the title and/or abstract. Results Thirty-three studies were identified. Articles were organized by topic and synthesized as evaluation- or management-focused articles covering 5 content categories: (A) Evaluation using skin images: (1) identification and differential diagnosis of psoriasis lesions, (2) lesion segmentation, and (3) lesion severity and area scoring; (B) clinical management: (1) prediction of complications and (2) treatment. Conclusion Machine learning has significant potential to aid psoriasis evaluation and management. Current topics popular in ML research on psoriasis are the evaluation of medical images, prediction of complications, and treatment discovery. For patients to derive the greatest benefit from ML advancements, it is helpful for dermatologists to have an understanding of ML and how it can effectively aid their assessments and decision-making.
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Affiliation(s)
- Kimberley Yu
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Maha N Syed
- Department of Dermatology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Elena Bernardis
- Department of Dermatology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Joel M Gelfand
- Department of Dermatology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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Vairavan R, Abdullah O, Retnasamy PB, Sauli Z, Shahimin MM, Retnasamy V. A Brief Review on Breast Carcinoma and Deliberation on Current Non Invasive Imaging Techniques for Detection. Curr Med Imaging 2020; 15:85-121. [PMID: 31975658 DOI: 10.2174/1573405613666170912115617] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 08/27/2017] [Accepted: 08/29/2017] [Indexed: 12/22/2022]
Abstract
BACKGROUND Breast carcinoma is a life threatening disease that accounts for 25.1% of all carcinoma among women worldwide. Early detection of the disease enhances the chance for survival. DISCUSSION This paper presents comprehensive report on breast carcinoma disease and its modalities available for detection and diagnosis, as it delves into the screening and detection modalities with special focus placed on the non-invasive techniques and its recent advancement work done, as well as a proposal on a novel method for the application of early breast carcinoma detection. CONCLUSION This paper aims to serve as a foundation guidance for the reader to attain bird's eye understanding on breast carcinoma disease and its current non-invasive modalities.
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Affiliation(s)
- Rajendaran Vairavan
- School of Microelectronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
| | - Othman Abdullah
- Hospital Sultan Abdul Halim, 08000 Sg. Petani, Kedah, Malaysia
| | | | - Zaliman Sauli
- School of Microelectronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
| | - Mukhzeer Mohamad Shahimin
- Department of Electrical and Electronic Engineering, Faculty of Engineering, National Defence University of Malaysia (UPNM), Kem Sungai Besi, 57000 Kuala Lumpur, Malaysia
| | - Vithyacharan Retnasamy
- School of Microelectronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
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First review on psoriasis severity risk stratification: An engineering perspective. Comput Biol Med 2015; 63:52-63. [DOI: 10.1016/j.compbiomed.2015.05.005] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Revised: 05/05/2015] [Accepted: 05/06/2015] [Indexed: 01/03/2023]
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