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Alyami AS, Madkhali Y, Majrashi NA, Alwadani B, Elbashir M, Ali S, Ageeli W, El-Bahkiry HS, Althobity AA, Refaee T. The role of molecular imaging in detecting fibrosis in Crohn's disease. Ann Med 2024; 56:2313676. [PMID: 38346385 PMCID: PMC10863520 DOI: 10.1080/07853890.2024.2313676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 01/30/2024] [Indexed: 02/15/2024] Open
Abstract
Fibrosis is a pathological process that occurs due to chronic inflammation, leading to the proliferation of fibroblasts and the excessive deposition of extracellular matrix (ECM). The process of long-term fibrosis initiates with tissue hypofunction and progressively culminates in the ultimate manifestation of organ failure. Intestinal fibrosis is a significant complication of Crohn's disease (CD) that can result in persistent luminal narrowing and strictures, which are difficult to reverse. In recent years, there have been significant advances in our understanding of the cellular and molecular mechanisms underlying intestinal fibrosis in inflammatory bowel disease (IBD). Significant progress has been achieved in the fields of pathogenesis, diagnosis, and management of intestinal fibrosis in the last few years. A significant amount of research has also been conducted in the field of biomarkers for the prediction or detection of intestinal fibrosis, including novel cross-sectional imaging modalities such as positron emission tomography (PET) and single photon emission computed tomography (SPECT). Molecular imaging represents a promising biomedical approach that enables the non-invasive visualization of cellular and subcellular processes. Molecular imaging has the potential to be employed for early detection, disease staging, and prognostication in addition to assessing disease activity and treatment response in IBD. Molecular imaging methods also have a potential role to enabling minimally invasive assessment of intestinal fibrosis. This review discusses the role of molecular imaging in combination of AI in detecting CD fibrosis.
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Affiliation(s)
- Ali S. Alyami
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Yahia Madkhali
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Naif A. Majrashi
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Bandar Alwadani
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Meaad Elbashir
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Sarra Ali
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Wael Ageeli
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Hesham S. El-Bahkiry
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
| | - Abdullah A. Althobity
- Department of Radiological Sciences and Medical Imaging, College of Applied Medical Sciences, Majmaah University, Majmaah, Saudi Arabia
| | - Turkey Refaee
- Department of Diagnostic Radiography Technology, College of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia
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Baniasadi A, Das JP, Prendergast CM, Beizavi Z, Ma HY, Jaber MY, Capaccione KM. Imaging at the nexus: how state of the art imaging techniques can enhance our understanding of cancer and fibrosis. J Transl Med 2024; 22:567. [PMID: 38872212 PMCID: PMC11177383 DOI: 10.1186/s12967-024-05379-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Accepted: 06/06/2024] [Indexed: 06/15/2024] Open
Abstract
Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes.
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Affiliation(s)
- Alireza Baniasadi
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA.
| | - Jeeban P Das
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Conor M Prendergast
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA
| | - Zahra Beizavi
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA
| | - Hong Y Ma
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA
| | | | - Kathleen M Capaccione
- Department of Radiology, Columbia University Irving Medical Center, 622 W 168Th Street, New York, NY, 10032, USA
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Zeng X, Jiang H, Dai Y, Zhang J, Zhao S, Wu Q. A radiomics nomogram based on MSCT and clinical factors can stratify fibrosis in inflammatory bowel disease. Sci Rep 2024; 14:1176. [PMID: 38216597 PMCID: PMC10786819 DOI: 10.1038/s41598-023-51036-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 12/29/2023] [Indexed: 01/14/2024] Open
Abstract
Intestinal fibrosis is one of the major complications of inflammatory bowel disease (IBD) and a pathological process that significantly impacts patient prognosis and treatment selection. Although current imaging assessment and clinical markers are widely used for the diagnosis and stratification of fibrosis, these methods suffer from subjectivity and limitations. In this study, we aim to develop a radiomics diagnostic model based on multi-slice computed tomography (MSCT) and clinical factors. MSCT images and relevant clinical data were collected from 218 IBD patients, and a large number of quantitative image features were extracted. Using these features, we constructed a radiomics model and transformed it into a user-friendly diagnostic nomogram. A nomogram was developed to predict fibrosis in IBD by integrating multiple factors. The nomogram exhibited favorable discriminative ability, with an AUC of 0.865 in the validation sets, surpassing both the logistic regression (LR) model (AUC = 0.821) and the clinical model (AUC = 0.602) in the test set. In the train set, the LR model achieved an AUC of 0.975, while the clinical model had an AUC of 0.735. The nomogram demonstrated superior performance with an AUC of 0.971, suggesting its potential as a valuable tool for predicting fibrosis in IBD and improving clinical decision-making. The radiomics nomogram, incorporating MSCT and clinical factors, demonstrates promise in stratifying fibrosis in IBD. The nomogram outperforms traditional clinical models and offers personalized risk assessment. However, further validation and addressing identified limitations are necessary to enhance its applicability.
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Affiliation(s)
- Xu Zeng
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, No.246 Xuefu Road, Nangang District, Harbin, 150081, Helongjiang Province, People's Republic of China
| | - Huijie Jiang
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, No.246 Xuefu Road, Nangang District, Harbin, 150081, Helongjiang Province, People's Republic of China.
| | - Yanmei Dai
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, No.246 Xuefu Road, Nangang District, Harbin, 150081, Helongjiang Province, People's Republic of China
| | - Jin Zhang
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, No.246 Xuefu Road, Nangang District, Harbin, 150081, Helongjiang Province, People's Republic of China
| | - Sheng Zhao
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, No.246 Xuefu Road, Nangang District, Harbin, 150081, Helongjiang Province, People's Republic of China
| | - Qiong Wu
- Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, No.246 Xuefu Road, Nangang District, Harbin, 150081, Helongjiang Province, People's Republic of China
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Mignini I, Maresca R, Ainora ME, Larosa L, Scaldaferri F, Gasbarrini A, Zocco MA. Predicting Treatment Response in Inflammatory Bowel Diseases: Cross-Sectional Imaging Markers. J Clin Med 2023; 12:5933. [PMID: 37762874 PMCID: PMC10532020 DOI: 10.3390/jcm12185933] [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: 07/31/2023] [Revised: 09/05/2023] [Accepted: 09/09/2023] [Indexed: 09/29/2023] Open
Abstract
Therapeutic options for inflammatory bowel diseases (IBD) have largely expanded in the last decades, both in Crohn's disease and ulcerative colitis, including multiple biological drugs targeting different inflammation pathways. However, choosing the best treatment and timing for each patient is still an undeniable challenge for IBD physicians due to the marked heterogeneity among patients and disease behavior. Therefore, early prediction of the response to biological drugs becomes of utmost importance, allowing prompt optimization of therapeutic strategies and thus paving the way towards precision medicine. In such a context, researchers have recently focused on cross-sectional imaging techniques (intestinal ultrasound, computed tomography, and magnetic resonance enterography) in order to identify predictive markers of response or non-response to biologic therapies. In this review, we aim to summarize data about imaging factors that may early predict disease behavior during biological treatment, potentially helping to define more precise and patient-tailored strategies.
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Affiliation(s)
- Irene Mignini
- CEMAD Digestive Diseases Center, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Università Cattolica del Sacro Cuore, Largo A. Gemelli 8, 00168 Rome, Italy; (I.M.); (R.M.); (F.S.); (A.G.); (M.A.Z.)
| | - Rossella Maresca
- CEMAD Digestive Diseases Center, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Università Cattolica del Sacro Cuore, Largo A. Gemelli 8, 00168 Rome, Italy; (I.M.); (R.M.); (F.S.); (A.G.); (M.A.Z.)
| | - Maria Elena Ainora
- CEMAD Digestive Diseases Center, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Università Cattolica del Sacro Cuore, Largo A. Gemelli 8, 00168 Rome, Italy; (I.M.); (R.M.); (F.S.); (A.G.); (M.A.Z.)
| | - Luigi Larosa
- Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Università Cattolica del Sacro Cuore, Largo A. Gemelli 8, 00168 Rome, Italy;
| | - Franco Scaldaferri
- CEMAD Digestive Diseases Center, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Università Cattolica del Sacro Cuore, Largo A. Gemelli 8, 00168 Rome, Italy; (I.M.); (R.M.); (F.S.); (A.G.); (M.A.Z.)
| | - Antonio Gasbarrini
- CEMAD Digestive Diseases Center, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Università Cattolica del Sacro Cuore, Largo A. Gemelli 8, 00168 Rome, Italy; (I.M.); (R.M.); (F.S.); (A.G.); (M.A.Z.)
| | - Maria Assunta Zocco
- CEMAD Digestive Diseases Center, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Università Cattolica del Sacro Cuore, Largo A. Gemelli 8, 00168 Rome, Italy; (I.M.); (R.M.); (F.S.); (A.G.); (M.A.Z.)
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