Comparison of the impact of rectal susceptibility artifacts in prostate magnetic resonance imaging on subjective evaluation and deep learning: a two-center retrospective study

被引:1
作者
Wang, Zheng [1 ,2 ]
Lu, Peng [1 ,2 ]
Liu, Song [1 ,2 ]
Fu, Chengzhi [1 ,2 ]
Ye, Yong [1 ,2 ]
Yu, Chengxin [1 ,2 ]
Hu, Lei [3 ,4 ]
机构
[1] China Three Gorges Univ, Yichang Cent Peoples Hosp, Coll Clin Med Sci 1, Dept Radiol, 183 Yiling Ave, Yichang 443000, Peoples R China
[2] China Three Gorges Univ, Inst Med Imaging, 183 Yiling Ave, Yichang 443000, Peoples R China
[3] Southern Med Univ, Guangdong Prov Peoples Hosp, Guangdong Acad Med Sci, Dept Radiol, 106 Zhongshan Er Rd, Guangzhou 510080, Peoples R China
[4] Guangdong Prov Key Lab Artificial Intelligence Med, 106 Zhongshan Er Rd, Guangzhou 510080, Peoples R China
基金
中国国家自然科学基金;
关键词
Rectal susceptibility artifact; Magnetic resonance imaging; Prostate cancer; Deep learning; SYSTEM; MRI;
D O I
10.1186/s12880-025-01602-7
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background To compare the influence of rectal susceptibility artifacts on the subjective evaluation and deep learning (DL) in prostate cancer (PCa) diagnosis. Methods This retrospective two-center study included 1052 patients who underwent MRI and biopsy due to clinically suspected PCa between November 2019 and November 2023. The extent of rectal artifacts in these patients' images was evaluated using the Likert four-level method. The PCa diagnosis was performed by six radiologists and an automated PCa diagnosis DL method. The performance of DL and radiologists was evaluated using the area under the receiver operating characteristic curve (AUC) and the area under the multi-reader multi-case receiver operating characteristic curve, respectively. Results Junior radiologists and DL demonstrated statistically significantly higher AUCs in patients without artifacts compared to those with artifacts (R1: 0.73 vs. 0.64; P = 0.01; R2: 0.74 vs. 0.67; P = 0.03; DL: 0.77 vs. 0.61; P < 0.001). In subgroup analysis, no statistically significant differences in the AUC were observed among different grades of rectal artifacts for both all radiologists (0.08 <= P <= 0.90) and DL models (0.12 <= P <= 0.96). The AUC for DL without artifacts significantly exceeded those with artifacts in both the peripheral zone (PZ) and transitional zone (TZ) (DLPZ: 0.78 vs. 0.61; P = 0.003; DLTZ: 0.73 vs. 0.59; P = 0.011). Conversely, there were no statistically significant differences in AUC with and without artifacts for all radiologists in PZ and TZ (0.08 <= P <= 0.98). Conclusions Rectal susceptibility artifacts have significant negative effects on subjective evaluation of junior radiologists and DL.
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页数:11
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共 32 条
[1]   Diffusion weighted imaging demystified: the technique and potential clinical applications for soft tissue imaging [J].
Ahlawat, Shivani ;
Fayad, Laura M. .
SKELETAL RADIOLOGY, 2018, 47 (03) :313-328
[2]   Susceptibility artifacts and PIRADS 3 lesions in prostatic MRI: how often is the dynamic contrast-enhance sequence necessary? [J].
Antunes, Natalie ;
Vas, Daniel ;
Sebastia, Carmen ;
Salvador, Rafael ;
Ribal, Maria Jose ;
Nicolau, Carlos .
ABDOMINAL RADIOLOGY, 2021, 46 (07) :3401-3409
[3]   Rectal preparation significantly improves prostate imaging quality: Assessment of the PI-QUAL score with visual grading characteristics [J].
Arnoldner, Michael A. ;
Polanec, Stephan H. ;
Lazar, Mathias ;
Khadjavi, Sam Noori ;
Clauser, Paola ;
Poetsch, Nina ;
Schwarz-Nemec, Ursula ;
Korn, Stephan ;
Huebner, Nicolai ;
Shariat, Shahrokh F. ;
Helbich, Thomas H. ;
Baltzer, Pascal A. T. .
EUROPEAN JOURNAL OF RADIOLOGY, 2022, 147
[4]   Diagnostic Accuracy of Abbreviated Bi-Parametric MRI (a-bpMRI) for Prostate Cancer Detection and Screening: A Multi-Reader Study [J].
Brembilla, Giorgio ;
Giganti, Francesco ;
Sidhu, Harbir ;
Imbriaco, Massimo ;
Mallett, Sue ;
Stabile, Armando ;
Freeman, Alex ;
Ahmed, Hashim U. ;
Moore, Caroline ;
Emberton, Mark ;
Punwani, Shonit .
DIAGNOSTICS, 2022, 12 (02)
[5]   Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study [J].
Bulten, Wouter ;
Pinckaers, Hans ;
van Boven, Hester ;
Vink, Robert ;
de Bel, Thomas ;
van Ginneken, Bram ;
van der Laak, Jeroen ;
Hulsbergen-van de Kaa, Christina ;
Litjens, Geert .
LANCET ONCOLOGY, 2020, 21 (02) :233-241
[6]   Evaluating the effect of rectal distension on prostate multiparametric MRI image quality [J].
Caglic, Iztok ;
Hansen, Nienke L. ;
Slough, Rhys A. ;
Patterson, Andrew J. ;
Barrett, Tristan .
EUROPEAN JOURNAL OF RADIOLOGY, 2017, 90 :174-180
[7]   Impact of bowel preparation with Fleet's™ enema on prostate MRI quality [J].
Coskun, Mehmet ;
Mehralivand, Sherif ;
Shih, Joanna H. ;
Merino, Maria J. ;
Wood, Bradford J. ;
Pinto, Peter A. ;
Barrett, Tristan ;
Choyke, Peter L. ;
Turkbey, Baris .
ABDOMINAL RADIOLOGY, 2020, 45 (12) :4252-4259
[8]   Artifacts in 3-T MRI: Physical background and reduction strategies [J].
Dietrich, Olaf ;
Reiser, Maximilian F. ;
Schoenberg, Stefan O. .
EUROPEAN JOURNAL OF RADIOLOGY, 2008, 65 (01) :29-35
[9]   Adversarial attacks on medical machine learning [J].
Finlayson, Samuel G. ;
Bowers, John D. ;
Ito, Joichi ;
Zittrain, Jonathan L. ;
Beam, Andrew L. ;
Kohane, Isaac S. .
SCIENCE, 2019, 363 (6433) :1287-1289
[10]   Monitoring Prostate Cancer Incidence Trends: Value of Multiple Imputation and Delay Adjustment to Discern Disparities in Stage-specific Trends [J].
Gomez, Scarlett Lin ;
Washington, Samuel L., III ;
Cheng, Iona ;
Huang, Franklin W. ;
Cooperberg, Matthew R. .
EUROPEAN UROLOGY, 2021, 79 (01) :42-43