1
|
Tandon M, Chakraborty S, Barkondaj B, Choudhury S, Pal DK. Role of multiparametric MRI in predicting muscle invasiveness in urinary bladder neoplasms with pathological correlations. Urologia 2024; 91:55-60. [PMID: 37886848 DOI: 10.1177/03915603231204078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Urinary bladder cancer (BC) is one of the most frequent malignancies and the ninth most common malignancy worldwide. The objective of this study is to assess the role of multiparametric magnetic resonance imaging (mp-MRI) in predicting the invasiveness of urinary bladder space occupying lesions. Thirty-five patients diagnosed with bladder masses underwent an mp-MRI study. The results of three image sets were analysed and compared with the histopathological results as a reference standard: T2-weighted image (T2WI) plus dynamic contrast-enhanced (DCE), T2WI plus diffusion-weighted images (DWI), and mp-MRI, including T2WI plus DWI and DCE. The diagnostic accuracy of mp-MRI was evaluated using receiver operating characteristic curve analysis. We discovered a highly significant correlation between muscle invasiveness as staged by HPE (Histopathological examination) and mp-MRI utilising a VI-RADS score >3 (p 0.001) with a sensitivity of 100% and a specificity of 85.7%. With a diagnostic accuracy of 77.14%, a sensitivity of 92.31%, a specificity of 72.72%, a positive predictive value of 66.67%, and a negative predictive value of 94.11%, In terms of muscle invasiveness, there is good concordance between HPE staging and mp-MRI utilising the VI-RADS score. The mean apparent diffusion coefficient (ADC) values were higher in low grades than in high grades. The ROC curve study revealed a very strong correlation between HPE grade and ADC (p = 0.045). In 77.14% of patients, Mp-MRI correctly identified the local T stage. Mp-MRI is imaging biomarker for invasiveness and grade of tumour. The tumours with high grade are more invasive. However, the diagnostic accuracy of mp-MRI in determining muscle invasiveness is not very high and it overstages the disease in some cases (33.3%). Its clinical usefulness in determining muscle invasiveness before TURBT and histopathological examination can be questioned.
Collapse
Affiliation(s)
- Mrinal Tandon
- Department of Urology, IPGME&R, Kolkata, West Bengal, India
| | | | | | - Sunirmal Choudhury
- Department of urology, Medical College Hospital, Kolkata, West Bengal, India
| | | |
Collapse
|
2
|
Akin O, Lema-Dopico A, Paudyal R, Konar AS, Chenevert TL, Malyarenko D, Hadjiiski L, Al-Ahmadie H, Goh AC, Bochner B, Rosenberg J, Schwartz LH, Shukla-Dave A. Multiparametric MRI in Era of Artificial Intelligence for Bladder Cancer Therapies. Cancers (Basel) 2023; 15:5468. [PMID: 38001728 PMCID: PMC10670574 DOI: 10.3390/cancers15225468] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/27/2023] [Accepted: 10/30/2023] [Indexed: 11/26/2023] Open
Abstract
This review focuses on the principles, applications, and performance of mpMRI for bladder imaging. Quantitative imaging biomarkers (QIBs) derived from mpMRI are increasingly used in oncological applications, including tumor staging, prognosis, and assessment of treatment response. To standardize mpMRI acquisition and interpretation, an expert panel developed the Vesical Imaging-Reporting and Data System (VI-RADS). Many studies confirm the standardization and high degree of inter-reader agreement to discriminate muscle invasiveness in bladder cancer, supporting VI-RADS implementation in routine clinical practice. The standard MRI sequences for VI-RADS scoring are anatomical imaging, including T2w images, and physiological imaging with diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI). Physiological QIBs derived from analysis of DW- and DCE-MRI data and radiomic image features extracted from mpMRI images play an important role in bladder cancer. The current development of AI tools for analyzing mpMRI data and their potential impact on bladder imaging are surveyed. AI architectures are often implemented based on convolutional neural networks (CNNs), focusing on narrow/specific tasks. The application of AI can substantially impact bladder imaging clinical workflows; for example, manual tumor segmentation, which demands high time commitment and has inter-reader variability, can be replaced by an autosegmentation tool. The use of mpMRI and AI is projected to drive the field toward the personalized management of bladder cancer patients.
Collapse
Affiliation(s)
- Oguz Akin
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Alfonso Lema-Dopico
- Department of Medical Physics, Memorial Sloan Kettering Cancer, New York, NY 10065, USA
| | - Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer, New York, NY 10065, USA
| | | | | | - Dariya Malyarenko
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lubomir Hadjiiski
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hikmat Al-Ahmadie
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Alvin C. Goh
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Bernard Bochner
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Jonathan Rosenberg
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Lawrence H. Schwartz
- Department of Medical Physics, Memorial Sloan Kettering Cancer, New York, NY 10065, USA
| | - Amita Shukla-Dave
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Department of Medical Physics, Memorial Sloan Kettering Cancer, New York, NY 10065, USA
| |
Collapse
|
3
|
Gupta R, Mahajan M, Sharma P, Bhardwaj S, Gupta V, Mahajan A. Application of Vesical Imaging-Reporting and Data System in Evaluation of Urinary Bladder Cancer Using Multiparametric Magnetic Resonance Imaging: A Hospital-Based Cross-Sectional Study. Avicenna J Med 2022; 12:162-168. [PMID: 36570433 PMCID: PMC9771629 DOI: 10.1055/s-0042-1755334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Background Multiparametric magnetic resonance imaging (mp-MRI) of urinary bladder (UB) is a novel imaging to predict detrusor muscle invasion in Bladder cancer (BC). The Vesical Imaging-Reporting and Data System (VI-RADS) was introduced in 2018 to standardize the reporting of BC with mp-MRI and to diagnose muscle invasion. This study was performed to evaluate the role of mp-MRI using VI-RADS to predict muscle invasive BC. Methods This prospective study was carried from June 2020 to May 2021 in a tertiary care institute. Thirty-six patients with untreated BC underwent mp-MRI followed by transuretheral resection of the tumor (TURBT). Mp-MRI findings were evaluated by two radiologists and BC was categorized according to VI-RADS scoring system. Resected tumors along with separate biopsy from the base were reported by two pathologists. Histopathological findings were compared with VI-RADS score and the performance of VI-RADS for determining detrusor muscle invasion was analyzed. Results VI-RADS scores of 4 and 5 were assigned to 9 (25%) and 15 (41.7%) cases, respectively, while 4 (13.3%) cases had VI-RADS score 3 on mp-MRI. VI-RADS 1 and 2 lesions were observed in six (16.7%) and two (5.5%) cases, respectively. On histopathology, 23 cases (63.9%) had muscle-invasive cancer and 13 cases (36.1%) had non-muscle-invasive cancer. The sensitivity and diagnostic accuracy of mp-MRI in predicting muscle invasive BC was 95.6 and 80.6%, respectively. Conclusion Mp-MRI has high sensitivity and diagnostic accuracy in predicting muscle invasive BC and should be advocated for evaluation of BC prior to surgery.
Collapse
Affiliation(s)
- Rahul Gupta
- Department of Urology, Government Medical College, Jammu, Jammu and Kashmir, India
| | - Manik Mahajan
- Department of Radio-Diagnosis and Imaging, Government Medical College, Jammu, Jammu and Kashmir, India
| | - Poonam Sharma
- Department of Pathology, All India Institute of Medical Sciences, Vijaypur, Jammu, Jammu and Kashmir, India,Address for correspondence Poonam Sharma, MD House no. 109, Sector 7, Channi Himmat, Jammu (J&K) 180015India
| | - Subhash Bhardwaj
- Department of Pathology, Government Medical College, Jammu, Jammu and Kashmir, India
| | - Vikrant Gupta
- Department of Radiology, Government Medical College, Jammu, Jammu and Kashmir, India
| | - Arti Mahajan
- Department of Anaesthesia, Government Medical College, Jammu, Jammu and Kashmir, India
| |
Collapse
|
4
|
Maffei ME. Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics. Int J Mol Sci 2022; 23:1339. [PMID: 35163262 PMCID: PMC8835851 DOI: 10.3390/ijms23031339] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/22/2022] [Accepted: 01/22/2022] [Indexed: 02/08/2023] Open
Abstract
Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.
Collapse
Affiliation(s)
- Massimo E Maffei
- Department Life Sciences and Systems Biology, University of Turin, Via Quarello 15/a, 10135 Turin, Italy
| |
Collapse
|