Abdominal Radiology

, Volume 43, Issue 11, pp 2903–2912 | Cite as

Role of MRI and added value of diffusion-weighted and gadolinium-enhanced MRI for the diagnosis of local recurrence from rectal cancer

  • Valeria MolinelliEmail author
  • Maria Gloria Angeretti
  • Ejona Duka
  • Nicola Tarallo
  • Elena Bracchi
  • Raffaele Novario
  • Carlo Fugazzola



To evaluate whether the addition of gadolinium-enhanced MRI and diffusion-weighted imaging (DWI) improves T2 sequence performance for the diagnosis of local recurrence (LR) from rectal cancer and to assess which approach is better at formulating this diagnosis among readers with different experience.


Forty-three patients with suspected LR underwent pelvic MRI with T2 weighted (T2) sequences, gadolinium fat-suppressed T1 weighted sequences (post-contrast T1), and DWI sequences. Three readers (expert: G, intermediate: E, resident: V) scored the likelihood of LR on T2, T2 + post-contrast T1, T2 + DWI, and T2 + post-contrast T1 + DWI.


In total, 18/43 patients had LR; on T2 images, the expert reader achieved an area under the ROC curve (AUC) of 0.916, sensitivity of 88.9%, and specificity of 76%; the intermediate reader achieved values of 0.890, 88.9%, and 48%, respectively, and the resident achieved values of 0.852, 88.9%, and 48%, respectively. DWI significantly improved the AUC value for the expert radiologist by up to 0.999 (p = 0.04), while post-contrast T1 significantly improved the AUC for the resident by up to 0.950 (p = 0.04). For the intermediate reader, both the T2 + DWI AUC and T2 + post-contrast T1 AUC were better than the T2 AUC (0.976 and 0.980, respectively), but with no statistically significant difference. No statistically significant difference was achieved by any of the three readers by comparing either the T2 + DWI AUCs to the T2 + post-contrast T1 AUCs or the AUCs of the two pairs of sequences to those of the combined three sequences.

Furthermore, using the T2 sequences alone, all of the readers achieved a fair number of “equivocal” cases: they decreased with the addition of either DWI or post-contrast T1 sequences and, for the two less experienced readers, they decreased even more with the three combined sequences.


Both DWI and T1 post-contrast MRI increased diagnostic performance for LR diagnosis compared to T2; however, no significant difference was observed by comparing the two different pairs of sequences with the three combined sequences.


Magnetic resonance Oncologic imaging Machine learning Rectal cancer local recurrence Diffusion weighted images 


Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

The authors declare that the research, with consideration of the retrospective nature of the work, complied with local regulations for work with human subject data.


  1. 1.
    Weinstein S, Osei-Bonsu S, Aslam R, Yee J (2013) Multidetector CT of the postoperative colon: review of normal appearances and common complications. RadioGraphics 33:515–532CrossRefGoogle Scholar
  2. 2.
    Colosio A, Forne P, Soyer P, et al. (2013) Local colorectal cancer recurrence: pelvic MRI evaluation. Abdom Imaging 38:72–81CrossRefGoogle Scholar
  3. 3.
    Abulafi AM, William NS (1994) The local recurrence of colorectal cancer: the problem, mechanisms, management and adjuvant therapy. Br J Surg 81:7–19CrossRefGoogle Scholar
  4. 4.
    Cai Y, Li Z, Gu X, et al. (2014) Prognostic factors associated with locally recurrent rectal cancer following primary surgery (review). Oncol Lett 7:10–16CrossRefGoogle Scholar
  5. 5.
    Hoffel C, Marcus C, Arrivè L, et al. (2009) Imagerie post-opératoire de chirurgie colorectale. J Radiol 90:954–968CrossRefGoogle Scholar
  6. 6.
    Tan PL, Chan CLH, Moore NR (2005) Radiological appearances in the pelvis following rectal cancer surgery. Clin Radiol 60:846–855CrossRefGoogle Scholar
  7. 7.
    Nural SM, Danaci M, Soyucoket A, et al. (2013) Efficiency of apparent diffusion coefficients in differentiation of colorectal tumor recurrences and post therapeutical soft-tissue changes. Eur J Radiol 82:1702–1709CrossRefGoogle Scholar
  8. 8.
    Nishie A, Stolpen AH, Obuchi M, et al. (2008) Evaluation of locally recurrent pelvic malignancy: performance of T2- and diffusion-weighted MRI with image fusion. J Magn Reson Imaging 28:705–713CrossRefGoogle Scholar
  9. 9.
    Torricelli P, Pecchi A, Luppi G, Romagnoli R (2003) Gadolinium-enhanced MRI with dynamic evaluation in diagnosing the local recurrence of rectal cancer. Abdom Imaging 28:19–27CrossRefGoogle Scholar
  10. 10.
    Blomqvist L, Fransson P, Hindmarsh T (1998) The pelvis after surgery and radio-chemotherapy for rectal cancer studied with Gd-DTPA-enhanced fast dynamic MR imaging. Eur Radiol 8:781–787CrossRefGoogle Scholar
  11. 11.
    Sinha R, Rajiah P, Ramachandran I, et al. (2013) Diffusion-weighted MR imaging of the gastrointestinal tract: technique, indications, and imaging findings. RadioGraphics 33:655–676CrossRefGoogle Scholar
  12. 12.
    Lambregts DMJ, Cappendijk VC, Maas M, et al. (2011) Value of MRI and diffusion-weighted MRI for the diagnosis of locally recurrent rectal cancer. Eur Radiol 21:1250–1258CrossRefGoogle Scholar
  13. 13.
    Grosu S, Schäfer AO, Baumann T, et al. (2016) Differentiating locally recurrent rectal cancer from scar tissue: value of diffusion-weighted MRI. Eur J Radiol 85(7):1265–1270CrossRefGoogle Scholar
  14. 14.
    Colosio A, Soyer P, Rousset P, et al. (2014) Value of diffusion-weighted and gadolinium-enhanced MRI for the diagnosis of pelvic recurrence from colorectal cancer. J Magn Reson Imaging 40:306–313CrossRefGoogle Scholar
  15. 15.
    Hoeffel C, Arrivé L, Mourra M, et al. (2006) Anatomic and pathologic findings at external phased-array pelvic MR imaging after surgery for anorectal disease. RadioGraphics 26:1391–1407CrossRefGoogle Scholar
  16. 16.
    DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44(3):837–845CrossRefGoogle Scholar
  17. 17.
    Müller-Schimpfle M, Brix G, Layer G, et al. (1993) Recurrent rectal cancer: diagnosis with dynamic MR imaging. Radiology 189(3):881–889CrossRefGoogle Scholar
  18. 18.
    Kuang F, Ren J, Zhong Q, et al. (2013) The value of apparent diffusion coefficient in the assessment of cervical cancer. Eur Radiol 23(4):1050–1058CrossRefGoogle Scholar
  19. 19.
    Roy C, Foudi F, Charton J, et al. (2013) Comparative sensitivities of functional MRI sequences in detection of local recurrence of prostate carcinoma after radical prostatectomy or external-beam radiotherapy. AJR 200(4):W361–W368CrossRefGoogle Scholar
  20. 20.
    Lambregts DMJ, Vandecaveye V, Barbaro B, et al. (2011) Diffusion-weighted MRI for selection of complete responders after chemoradiation for locally advanced rectal cancer: a multicenter study. Ann Surg Oncol 18:2224–2231CrossRefGoogle Scholar
  21. 21.
    Park MJ, Kim SH, Lee SJ, et al. (2011) Locally advanced rectal cancer: added value of diffusion-weighted MR imaging for predicting tumor clearance of the mesorectal fascia after neoadjuvant chemotherapy and radiation therapy. Radiology 260(3):771–780CrossRefGoogle Scholar
  22. 22.
    Lambregts DMJ, Lahaye MJ, Heijnen LA, et al. (2016) MRI and diffusion-weighted MRI to diagnose a local tumour regrowth during long-term follow-up of rectal cancer patients treated with organ preservation after chemoradiotherapy. Eur Radiol 26:2118–2125CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of RadiologyUniversity HospitalVareseItaly
  2. 2.Department of Medical PhysicsUniversity HospitalVareseItaly

Personalised recommendations