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      Synthetic MRI plus FSE-PROPELLER DWI for differentiating malignant from benign head and neck tumors: a preliminary study

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          Abstract

          Background

          Preoperative classification of head and neck (HN) tumors remains challenging, especially distinguishing early cancerogenic masses from benign lesions. Synthetic MRI offers a new way for quantitative analysis of tumors. The present study investigated the application of synthetic MRI and stimulus and fast spin echo diffusion-weighted imaging with periodically rotated overlapping parallel lines with enhanced reconstruction (FSE-PROPELLER DWI) to differentiate malignant from benign HN tumors.

          Materials and methods

          Forty-eight patients with pathologically confirmed HN tumors were retrospectively recruited between August 2022 and October 2022. The patients were divided into malignant (n = 28) and benign (n = 20) groups. All patients were scanned using synthetic MRI and FSE-PROPELLER DWI. T1, T2, and proton density (PD) values were acquired on the synthetic MRI and ADC values on the FSE-PROPELLER DWI.

          Results

          Benign tumors (ADC: 2.03 ± 0.31 × 10 -3 mm 2/s, T1: 1741.13 ± 662.64 ms, T2: 157.43 ± 72.23 ms) showed higher ADC, T1, and T2 values compared to malignant tumors (ADC: 1.46 ± 0.37 × 10 -3 mm 2/s, T1: 1390.06 ± 241.09 ms, T2: 97.64 ± 14.91 ms) (all P<0.05), while no differences were seen for PD values. ROC analysis showed that T2+ADC (cut-off value, > 0.55; AUC, 0.950) had optimal diagnostic performance vs. T1 (cut-off value, ≤ 1675.84 ms; AUC, 0.698), T2 (cut-off value, ≤ 113.24 ms; AUC, 0.855) and PD (cut off value, > 80.67 pu; AUC, 0.568) alone in differentiating malignant from benign lesions (all P<0.05); yet, the difference in AUC between ADC and T2+ADC or T2 did not reach statistical significance.

          Conclusion

          Synthetic MRI and FSE-PROPELLER DWI can quantitatively differentiate malignant from benign HN tumors. T2 value is comparable to ADC value, and T2+ADC values could improve diagnostic efficacy., apparent diffusion coeffificient, head and neck tumors

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          Most cited references28

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          Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach

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            Cancer Statistics, 2017.

            Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data were collected by the National Center for Health Statistics. In 2017, 1,688,780 new cancer cases and 600,920 cancer deaths are projected to occur in the United States. For all sites combined, the cancer incidence rate is 20% higher in men than in women, while the cancer death rate is 40% higher. However, sex disparities vary by cancer type. For example, thyroid cancer incidence rates are 3-fold higher in women than in men (21 vs 7 per 100,000 population), despite equivalent death rates (0.5 per 100,000 population), largely reflecting sex differences in the "epidemic of diagnosis." Over the past decade of available data, the overall cancer incidence rate (2004-2013) was stable in women and declined by approximately 2% annually in men, while the cancer death rate (2005-2014) declined by about 1.5% annually in both men and women. From 1991 to 2014, the overall cancer death rate dropped 25%, translating to approximately 2,143,200 fewer cancer deaths than would have been expected if death rates had remained at their peak. Although the cancer death rate was 15% higher in blacks than in whites in 2014, increasing access to care as a result of the Patient Protection and Affordable Care Act may expedite the narrowing racial gap; from 2010 to 2015, the proportion of blacks who were uninsured halved, from 21% to 11%, as it did for Hispanics (31% to 16%). Gains in coverage for traditionally underserved Americans will facilitate the broader application of existing cancer control knowledge across every segment of the population. CA Cancer J Clin 2017;67:7-30. © 2017 American Cancer Society.
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              The Correlation between Apparent Diffusion Coefficient and Tumor Cellularity in Patients: A Meta-Analysis

              Objective To perform a meta-analysis exploring the correlation between the apparent diffusion coefficient (ADC) and tumor cellularity in patients. Materials and Methods We searched medical and scientific literature databases for studies discussing the correlation between the ADC and tumor cellularity in patients. Only studies that were published in English or Chinese prior to November 2012 were considered for inclusion. Summary correlation coefficient (r) values were extracted from each study, and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses were performed to investigate potential heterogeneity. Results Of 189 studies, 28 were included in the meta-analysis, comprising 729 patients. The pooled r for all studies was −0.57 (95% CI: −0.62, −0.52), indicating notable heterogeneity (P<0.001). After the sensitivity analysis, two studies were excluded, and the pooled r was −0.61 (95% CI: −0.66, −0.56) and was not significantly heterogeneous (P = 0.127). Regarding tumor type subgroup analysis, there were sufficient data to support a strong negative correlation between the ADC and cellularity for brain tumors. There was no notable evidence of publication bias. Conclusions There is a strong negative correlation between the ADC and tumor cellularity in patients, particularly in the brain. However, larger, prospective studies are warranted to validate these findings in other cancer types.
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                Author and article information

                Contributors
                Journal
                Front Oncol
                Front Oncol
                Front. Oncol.
                Frontiers in Oncology
                Frontiers Media S.A.
                2234-943X
                27 September 2023
                2023
                : 13
                : 1225420
                Affiliations
                [1] 1Department of MRI, the First Affiliated Hospital of Zhengzhou University , Zhengzhou, China
                [2] 2MR Research China, GE Healthcare , Beijing, China
                Author notes

                Edited by: Zhimin Li, Northwestern University, United States

                Reviewed by: Han Lv, Capital Medical University, China; Guolin Ma, China-Japan Friendship Hospital, China; Ruiyang Zhao, GE Healthcare, United States

                *Correspondence: Yong Zhang, zzuzhangyong2013@ 123456163.com ; Jingliang Cheng, fccchengjl@ 123456zzu.edu.cn

                †These authors have contributed equally to this work

                Article
                10.3389/fonc.2023.1225420
                10565487
                37829331
                2645f38e-9f33-4e06-b778-0076afb8c723
                Copyright © 2023 Wen, Zhang, Zhu, Liu, Liu, Ma, Wang, Xie, Zhang and Cheng

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 May 2023
                : 04 September 2023
                Page count
                Figures: 3, Tables: 4, Equations: 0, References: 28, Pages: 10, Words: 4106
                Funding
                Henan Medical Science and Technology Research Plan (LHGJ20190157) supported this study.
                Categories
                Oncology
                Original Research
                Custom metadata
                Head and Neck Cancer

                Oncology & Radiotherapy
                synthetic,magnetic resonance imaging,diffusion-weighted image,apparent diffusion coefficient,head and neck tumors

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