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• Clinical Article •
Value of high-resolution T2-weighted imaging fused with field-of-view optimized and constrained undistorted single-shot diffusion-weighted imaging in preoperative T staging of rectal cancer
FU Shuai  ZHU Pan  HU Meiyu  LI Wenru  CHEN Chang  GUAN Yilin  PAN Ximin 

Cite this article as: FU S, ZHU P, HU M Y, et al. Value of high-resolution T2-weighted imaging fused with field-of-view optimized and constrained undistorted single-shot diffusion-weighted imaging in preoperative T staging of rectal cancer[J]. Chin J Magn Reson Imaging, 2026, 17(9): 129-135, 143. DOI:10.12015/issn.1674-8034.2026.09.017.


[Abstract] Objective To investigate the diagnostic value of high-resolution T2-weighted imaging (HR-T2WI) fused with field-of-view optimized and constrained undistorted single-shot diffusion-weighted imaging (Focus-DWI) in the preoperative T staging of rectal cancer.Materials and Methods This retrospective diagnostic accuracy study included MRI data of 99 patients with rectal cancer who were admitted to the Sixth Affiliated Hospital of Sun Yat-sen University from July 2022 to January 2024. The imaging data included axial HR-T2WI, Focus-DWI, and their fused images (T2WI-Fusion). With postoperative pathological findings as the gold standard, four radiologists (two senior and two junior) independently evaluated the preoperative T staging based on HR-T2WI and T2WI-Fusion, respectively. Weighted Kappa statistics were used to assess agreement with pathological results. Diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were then calculated. Receiver operating characteristic (ROC) curves were plotted to obtain the area under the curve (AUC), and the DeLong test was employed to compare the differences in AUC between the two sequences.Results The postoperative pathological T staging results for the 99 patients were as follows: 49 cases of ≤ T2 stage, 35 cases of T3 stage, and 15 cases of T4 stage. When using HR-T2WI alone, the AUCs of the four radiologists for diagnosing ≤ T2, T3, and T4 stages were 0.765 to 0.847, 0.628 to 0.710, and 0.717 to 0.840, respectively, with Kappa values ranging from 0.611 to 0.751. Senior radiologists showed better diagnostic agreement (0.676 to 0.751) than junior radiologists (0.611 to 0.616). After applying T2WI-Fusion, the AUCs for each T stage increased to 0.858 to 0.949, 0.769 to 0.890, and 0.864 to 0.970, respectively, and the Kappa values increased to 0.784 to 0.910. The DeLong test showed that the differences in AUC between the two sequences were statistically significant (all P < 0.05). Diagnostic consistency improved significantly for both senior and junior radiologists, with junior radiologists experiencing a more marked enhancement in both diagnostic performance and consistency.Conclusions The fused T2WI-Fusion images combining HR-T2WI and Focus-DWI can significantly improve the accuracy of preoperative T staging for rectal cancer and have high clinical application value.
[Keywords] rectal cancer；high-resolution magnetic resonance imaging；field-of-view optimized and constrained undistorted single-shot diffusion-weighted imaging；preoperative staging

FU Shuai1, 2   ZHU Pan1, 2   HU Meiyu1, 2   LI Wenru1, 2   CHEN Chang1, 2   GUAN Yilin1, 2   PAN Ximin1, 2*  

1 Department of Radiology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China

2 Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Huangpu District, Guangzhou 510655, China

Corresponding author: PAN X M, E-mail: panxm9@mail.sysu.edu.cn

Conflicts of interest   None.

Received  2026-04-15
Accepted  2026-08-12
DOI: 10.12015/issn.1674-8034.2026.09.017
Cite this article as: FU S, ZHU P, HU M Y, et al. Value of high-resolution T2-weighted imaging fused with field-of-view optimized and constrained undistorted single-shot diffusion-weighted imaging in preoperative T staging of rectal cancer[J]. Chin J Magn Reson Imaging, 2026, 17(9): 129-135, 143. DOI:10.12015/issn.1674-8034.2026.09.017.

[1]
BRAY F, LAVERSANNE M, SUNG H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263. DOI: 10.3322/caac.21834.
[2]
HAN B F, ZHENG R S, ZENG H M, et al. Cancer incidence and mortality in China, 2022[J]. J Natl Cancer Cent, 2024, 4(1): 47-53. DOI: 10.1016/j.jncc.2024.01.006.
[3]
ZHANG Z, TANG X L, MA R, et al. Global, regional, and national burdens of colorectal cancer and inflammatory bowel disease, 1990-2021 and toprojections 2050: a cross-sectional study[J/OL]. Int J Surg, 2026 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/41677329/. DOI: 10.1097/JS9.0000000000004428.
[4]
BENSON A B, VENOOK A P, ADAM M, et al. NCCN guidelines® insights: rectal cancer, version 3.2024[J]. J Natl Compr Canc Netw, 2024, 22(6): 366-375. DOI: 10.6004/jnccn.2024.0041.
[5]
Department of Medical Administration of National Health Commission, Chinese Medical Association Oncology Branch. National health commission clinical practice guidelines for colorectal cancer in China (2025 edition, abbreviated version)[J]. Chin J Gastrointest Surg, 2026, 29(1): 1-9. DOI: 10.3760/cma.j.cn441530-20251120-00442.
[6]
WANG Y Y, XIE B, WANG K, et al. Multi-parametric MRI habitat radiomics based on interpretable machine learning for preoperative assessment of microsatellite instability in rectal cancer[J]. Acad Radiol, 2025, 32(7): 3975-3988. DOI: 10.1016/j.acra.2025.02.009.
[7]
ZHAO J Y, ZHENG P, XU T, et al. Preoperative assessment of lymph node metastasis in rectal cancer using deep learning: investigating the utility of various MRI sequences[J]. Ann Surg Oncol, 2025, 32(10): 7304-7314. DOI: 10.1245/s10434-025-17717-8.
[8]
LIU Q X, WU S J, YUAN Q, et al. Explainable machine learning model based on DKI, IVIM, and clinical features for preoperative prediction of lymphovascular invasion in rectal cancer[J]. Chin J Magn Reson Imaging, 2025, 16(11): 129-134, 141. DOI: 10.12015/issn.1674-8034.2025.11.019.
[9]
BATES D D B, HOMSI M E, CHANG K J, et al. MRI for rectal cancer: staging, mrCRM, EMVI, lymph node staging and post-treatment response[J]. Clin Colorectal Cancer, 2022, 21(1): 10-18. DOI: 10.1016/j.clcc.2021.10.007.
[10]
PATANÈ V, ATRIPALDI U, SANSONE M, et al. MRI-based radiomics for preoperative T-staging of rectal cancer: a retrospective analysis[J/OL]. Int J Colorectal Dis, 2025, 40(1): 174 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/40778975/. DOI: 10.1007/s00384-025-04969-9.
[11]
JAYAPRAKASAM V S, ALVAREZ J, OMER D M, et al. Watch-and-wait approach to rectal cancer: the role of imaging[J/OL]. Radiology, 2023, 307(1): e221529 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/36880951/. DOI: 10.1148/radiol.221529.
[12]
MAYUMI TAKAMUNE D, MIRANDA J, MARIUSSI M, et al. Diffusion-weighted imaging in rectal cancer MRI from theory to practice[J]. Abdom Radiol, 2026, 51(2): 578-598. DOI: 10.1007/s00261-025-05102-8.
[13]
FU J Y, ZHAO C L, ZHENG G Y, et al. A multivariate model of IVIM-DWI in the preoperative diagnosis of tumor budding grade in rectal cancer[J/OL]. Front Oncol, 2025, 15: 1543607 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/40552266/. DOI: 10.3389/fonc.2025.1543607.
[14]
MODENA HEMING C A, ALVAREZ J A, MIRANDA J, et al. Mastering rectal cancer MRI: From foundational concepts to optimal staging[J/OL]. Eur J Radiol, 2025, 183: 111937 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/39864243/. DOI: 10.1016/j.ejrad.2025.111937.
[15]
SHI J J, LIN J, ZHOU X B, et al. Comparison of reduced and full field of view in diffusion-weighted MRI on image quality: a meta-analysis[J]. J Magn Reson Imaging, 2025, 61(2): 690-701. DOI: 10.1002/jmri.29487.
[16]
ZHANG H N, ZENG J W, WANG C, et al. The comparison of the application value of reduced field of view image reconstruction using image-space sampling function and full field of view single-shot echo-planar imaging DWI in rectal cancer[J]. Chin Comput Med Imaging, 2024, 30(3): 338-342. DOI: 10.19627/j.cnki.cn31-1700/th.2024.03.008.
[17]
WU B J, LIU Y, ZHANG Y W, et al. The value of high-resolution small field-of-view diffusion-weighted MRI technique in the detection of rectal cancer[J]. Int J Med Radiol, 2023, 46(6): 634-638, 658. DOI: 10.19300/j.2023.L20577.
[18]
WANG M Y, YU Y, YAN L F, et al. Application value of FOCUS diffusion weighted imaging in the diagnosis of microprolactinomas[J]. Chin J Magn Reson Imaging, 2022, 13(11): 60-65. DOI: 10.12015/issn.1674-8034.2022.11.011.
[19]
WANG Z Y, WANG C, DING T, et al. Application value of reduced field of view image reconstruction using image-space sampling function DWI sequence in rectal cancer T staging[J]. Radiol Pract, 2024, 39(3): 383-387. DOI: 10.13609/j.cnki.1000-0313.2024.03.014.
[20]
ZHANG J H, LIU R Q, HAO D, et al. ResNet-Vision Transformer based MRI-endoscopy fusion model for predicting treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicenter study[J]. Chin Med J, 2025, 138(21): 2793-2803. DOI: 10.1097/CM9.0000000000003391.
[21]
FENG S T, HUANG M Q, DONG Z, et al. MRI T2-weighted imaging and fat-suppressed T2-weighted imaging image fusion technology improves image discriminability for the evaluation of anal fistulas[J]. Korean J Radiol, 2019, 20(3): 429-437. DOI: 10.3348/kjr.2018.0260.
[22]
ZHENG Z Y, LIU Y, FENG L X, et al. Multimodal MRI image fusion for early automatic staging of endometrial cancer[J/OL]. Sensors (Basel), 2025, 25(9): 2932 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/40363369/. DOI: 10.3390/s25092932.
[23]
AMIN M B, GREENE F L, EDGE S B, et al. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging[J]. CA Cancer J Clin, 2017, 67(2): 93-99. DOI: 10.3322/caac.21388.
[24]
ZHAO Y, LIU W. Application of HR-T2WI combined with DWI in evaluating extramural vascular invasion of rectal cancer[J]. Chin Comput Med Imaging, 2022, 28(5): 505-509. DOI: 10.3969/j.issn.1006-5741.2022.05.012.
[25]
MAKSIM R, BUCZYŃSKA A, SIDORKIEWICZ I, et al. Imaging and metabolic diagnostic methods in the stage assessment of rectal cancer[J/OL]. Cancers, 2024, 16(14): 2553 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/39061192/. DOI: 10.3390/cancers16142553.
[26]
WANG Z, GE Y X, HE F, et al. High resolution T2WI combined with synthetic double inversion recovery images for T staging of rectal cancer[J]. Chin J Med Imaging Technol, 2022, 38(9): 1350-1355. DOI: 10.13929/j.issn.1003-3289.2022.09.016.
[27]
HORVAT N, CARLOS TAVARES ROCHA C, CLEMENTE OLIVEIRA B, et al. MRI of rectal cancer: tumor staging, imaging techniques, and management[J]. RadioGraphics, 2019, 39(2): 367-387. DOI: 10.1148/rg.2019180114.
[28]
WANG Z, DAI Z Z, ZHOU X Y, et al. Synthetic double inversion recovery imaging for rectal cancer T staging evaluation: imaging quality and added value to T2-weighted imaging[J/OL]. Insights Imaging, 2024, 15(1): 256 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/39446274/. DOI: 10.1186/s13244-024-01796-4.
[29]
HOU M, ZHOU L, SUN J H. Deep-learning-based 3D super-resolution MRI radiomics model: superior predictive performance in preoperative T-staging of rectal cancer[J]. Eur Radiol, 2023, 33(1): 1-10. DOI: 10.1007/s00330-022-08952-8.
[30]
SALMERÓN-RUIZ A, LUENGO GÓMEZ D, MEDINA BENÍTEZ A, et al. Primary staging of rectal cancer on MRI: an updated pictorial review with focus on common pitfalls and current controversies[J/OL]. Eur J Radiol, 2024, 175: 111417 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/38484688/. DOI: 10.1016/j.ejrad.2024.111417.
[31]
AO W Q, ZHANG X, YAO X Z, et al. Preoperative prediction of extramural venous invasion in rectal cancer by dynamic contrast-enhanced and diffusion weighted MRI: a preliminary study[J/OL]. BMC Med Imaging, 2022, 22(1): 78 [2026-02-12]. https://pubmed.ncbi.nlm.nih.gov/35484509/. DOI: 10.1186/s12880-022-00810-9.
[32]
WAN H Y, FANG X M, SHEN W, et al. The application value of MRI high-definition diffusion weighted imaging combined with T1WI dynamic contrast enhancement in preoperative T-stage of rectal cancer[J]. J Pract Radiol, 2024, 40(6): 926-930. DOI: 10.3969/j.issn.1002-1671.2024.06.015.
[33]
LI W Q, ZHANG G W, ZHANG J S. Advances in DWI models for treatment response assessment in rectal cancer[J]. Chin J Magn Reson Imaging, 2025, 16(10): 196-201. DOI: 10.12015/issn.1674-8034.2025.10.031.
[34]
INOUE A, TANABE M, IHARA K, et al. Evaluation of diffusion-weighted magnetic resonance imaging of the rectal cancers: comparison between modified reduced field-of-view single-shot echo-planar imaging with tilted two-dimensional radiofrequency excitation pulses and conventional full field-of-view readout-segmented echo-planar imaging[J]. La Radiol Med, 2023, 128(10): 1192-1198. DOI: 10.1007/s11547-023-01699-2.
[35]
MU R Q, LV J W, MA C Y, et al. Diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging parameters and serum tumor markers in rectal carcinoma prognosis[J]. World J Gastrointest Oncol, 2024, 16(5): 1796-1807. DOI: 10.4251/wjgo.v16.i5.1796.
[36]
WEI Y R, WANG H J, CHEN Z W, et al. Deep learning-based multiparametric MRI model for preoperative T-stage in rectal cancer[J]. J Magn Reson Imaging, 2024, 59(3): 1083-1092. DOI: 10.1002/jmri.28856.

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