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Article Open Access

Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images

  • Authors:
    • Shinya Kato
    • Norikatsu Miyoshi
    • Shiki Fujino
    • Soichiro Minami
    • Ayumi Nagae
    • Rie Hayashi
    • Yuki Sekido
    • Tsuyoshi Hata
    • Atsushi Hamabe
    • Takayuki Ogino
    • Mitsuyoshi Tei
    • Yoshinori Kagawa
    • Hidekazu Takahashi
    • Mamoru Uemura
    • Hirofumi Yamamoto
    • Yuichiro Doki
    • Hidetoshi Eguchi
  • View Affiliations / Copyright

    Affiliations: Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Osaka 565‑0871, Japan, Department of Innovative Oncology Research and Regenerative Medicine, Osaka International Cancer Institute, Osaka 541‑8567, Japan, Department of Surgery, Osaka Rosai Hospital, Sakai, Osaka 591‑8025, Japan, Department of Gastroenterological Surgery, Osaka General Medical Center, Osaka 558‑8588, Japan
    Copyright: © Kato et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 474
    |
    Published online on: September 20, 2023
       https://doi.org/10.3892/ol.2023.14062
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Abstract

In current clinical practice, several treatment methods, including neoadjuvant therapy, are being developed to improve overall survival or local recurrence rates for locally advanced rectal cancer. The response to neoadjuvant therapy is usually evaluated using imaging data collected before and after preoperative treatment or postsurgical pathological diagnosis. However, there is a need to accurately predict the response to preoperative treatment before treatment is administered. The present study used a deep learning network to examine colonoscopy images and construct a model to predict the response of rectal cancer to neoadjuvant chemotherapy. A total of 53 patients who underwent preoperative chemotherapy followed by radical resection for advanced rectal cancer at the Osaka University Hospital between January 2011 and August 2019 were retrospectively analyzed. A convolutional neural network model was constructed using 403 images from 43 patients as the learning set. The diagnostic accuracy of the deep learning model was evaluated using 84 images from 10 patients as the validation set. The model demonstrated a sensitivity, specificity, accuracy, positive predictive value and area under the curve of 77.6% (38/49), 62.9% (22/33), 71.4% (60/84), 74.5% (38/51) and 0.713, respectively, in predicting a poor response to neoadjuvant therapy. Overall, deep learning of colonoscopy images may contribute to an accurate prediction of the response of rectal cancer to neoadjuvant chemotherapy.
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Figure 3

View References

1 

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A and Bray F: Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 71:209–249. 2021. View Article : Google Scholar : PubMed/NCBI

2 

Fong Y, Cohen AM, Fortner JG, Enker WE, Turnbull AD, Coit DG, Marrero AM, Prasad M, Blumgart LH and Brennan MF: Liver resection for colorectal metastases. J Clin Oncol. 15:938–946. 1997. View Article : Google Scholar : PubMed/NCBI

3 

Rajput A and Bullard Dunn K: Surgical management of rectal cancer. Semin Oncol. 34:241–249. 2007. View Article : Google Scholar : PubMed/NCBI

4 

Weiser MR, Landmann RG, Wong WD, Shia J, Guillem JG, Temple LK, Minsky BD, Cohen AM and Paty PB: Surgical salvage of recurrent rectal cancer after transanal excision. Dis Colon Rectum. 48:1169–1175. 2005. View Article : Google Scholar : PubMed/NCBI

5 

Wiig JN, Larsen SG and Giercksky KE: Operative treatment of locally recurrent rectal cancer. Recent Results Cancer Res. 165:136–147. 2005. View Article : Google Scholar : PubMed/NCBI

6 

Schrag D, Weiser MR, Goodman KA, Gonen M, Hollywood E, Cercek A, Reidy-Lagunes DL, Gollub MJ, Shia J, Guillem JG, et al: Neoadjuvant chemotherapy without routine use of radiation therapy for patients with locally advanced rectal cancer: A pilot trial. J Clin Oncol. 32:513–518. 2014. View Article : Google Scholar : PubMed/NCBI

7 

Glynne-Jones R, Hava N, Goh V, Bosompem S, Bridgewater J, Chau I, Gaya A, Wasan H, Moran B, Melcher L, et al: Bevacizumab and Combination Chemotherapy in rectal cancer Until Surgery (BACCHUS): A phase II, multicentre, open-label, randomised study of neoadjuvant chemotherapy alone in patients with high-risk cancer of the rectum. BMC Cancer. 15:7642015. View Article : Google Scholar : PubMed/NCBI

8 

Kamiya T, Uehara K, Nakayama G, Ishigure K, Kobayashi S, Hiramatsu K, Nakayama H, Yamashita K, Sakamoto E, Tojima Y, et al: Early results of multicenter phase II trial of perioperative oxaliplatin and capecitabine without radiotherapy for high-risk rectal cancer: CORONA I study. Eur J Surg Oncol. 42:829–835. 2016. View Article : Google Scholar : PubMed/NCBI

9 

Folkesson J, Birgisson H, Pahlman L, Cedermark B, Glimelius B and Gunnarsson U: Swedish Rectal Cancer Trial: Long lasting benefits from radiotherapy on survival and local recurrence rate. J Clin Oncol. 23:5644–5650. 2005. View Article : Google Scholar : PubMed/NCBI

10 

Peeters KC, Marijnen CA, Nagtegaal ID, Kranenbarg EK, Putter H, Wiggers T, Rutten H, Pahlman L, Glimelius B, Leer JW, et al: The TME trial after a median follow-up of 6 years: Increased local control but no survival benefit in irradiated patients with resectable rectal carcinoma. Ann Surg. 246:693–701. 2007. View Article : Google Scholar : PubMed/NCBI

11 

Sauer R, Liersch T, Merkel S, Fietkau R, Hohenberger W, Hess C, Becker H, Raab HR, Villanueva MT, Witzigmann H, et al: Preoperative versus postoperative chemoradiotherapy for locally advanced rectal cancer: Results of the German CAO/ARO/AIO-94 randomized phase III trial after a median follow-up of 11 years. J Clin Oncol. 30:1926–1933. 2012. View Article : Google Scholar : PubMed/NCBI

12 

Ciseł B, Pietrzak L, Michalski W, Wyrwicz L, Rutkowski A, Kosakowska E, Cencelewicz A, Spałek M, Polkowski W, Jankiewicz M, et al: Long-course preoperative chemoradiation versus 5x5 Gy and consolidation chemotherapy for clinical T4 and fixed clinical T3 rectal cancer: Long-term results of the randomized Polish II study. Ann Oncol. 30:1298–1303. 2019. View Article : Google Scholar : PubMed/NCBI

13 

Bahadoer RR, Dijkstra EA, van Etten B, Marijnen CAM, Putter H, Kranenbarg EM, Roodvoets AGH, Nagtegaal ID, Beets-Tan RGH, Blomqvist LK, et al: Short-course radiotherapy followed by chemotherapy before total mesorectal excision (TME) versus preoperative chemoradiotherapy, TME, and optional adjuvant chemotherapy in locally advanced rectal cancer (RAPIDO): A randomised, open-label, phase 3 trial. Lancet Oncol. 22:29–42. 2021. View Article : Google Scholar : PubMed/NCBI

14 

Jin J, Tang Y, Hu C, Jiang LM, Jiang J, Li N, Liu WY, Chen SL, Li S, Lu NN, et al: Multicenter, randomized, Phase III trial of short-term radiotherapy plus chemotherapy versus long-term chemoradiotherapy in locally advanced rectal cancer (STELLAR). J Clin Oncol. 40:1681–1692. 2022. View Article : Google Scholar : PubMed/NCBI

15 

Patel UB, Taylor F, Blomqvist L, George C, Evans H, Tekkis P, Quirke P, Sebag-Montefiore D, Moran B, Heald R, et al: Magnetic resonance imaging-detected tumor response for locally advanced rectal cancer predicts survival outcomes: MERCURY experience. J Clin Oncol. 29:3753–3760. 2011. View Article : Google Scholar : PubMed/NCBI

16 

Fokas E, Liersch T, Fietkau R, Hohenberger W, Beissbarth T, Hess C, Becker H, Ghadimi M, Mrak K, Merkel S, et al: Tumor regression grading after preoperative chemoradiotherapy for locally advanced rectal carcinoma revisited: Updated results of the CAO/ARO/AIO-94 trial. J Clin Oncol. 32:1554–1562. 2014. View Article : Google Scholar : PubMed/NCBI

17 

Ghadimi BM, Grade M, Difilippantonio MJ, Varma S, Simon R, Montagna C, Füzesi L, Langer C, Becker H, Liersch T, et al: Effectiveness of gene expression profiling for response prediction of rectal adenocarcinomas to preoperative chemoradiotherapy. J Clin Oncol. 23:1826–1838. 2005. View Article : Google Scholar : PubMed/NCBI

18 

Cercek A, Dos Santos Fernandes G, Roxburgh CS, Ganesh K, Ng S, Sanchez-Vega F, Yaeger R, Segal NH, Reidy-Lagunes DL, Varghese AM, et al: Mismatch repair-deficient rectal cancer and resistance to neoadjuvant chemotherapy. Clin Cancer Res. 26:3271–3279. 2020. View Article : Google Scholar : PubMed/NCBI

19 

Lynch ML and Brand MI: Preoperative evaluation and oncologic principles of colon cancer surgery. Clin Colon Rectal Surg. 18:163–173. 2005. View Article : Google Scholar : PubMed/NCBI

20 

Arteaga-González I, Martín-Malagón A, Fernández EM, Arranz-Durán J, Parra-Blanco A, Nicolas-Perez D, Quintero-Carrión E, Luis HD and Carrillo-Pallares A: The use of preoperative endoscopic tattooing in laparoscopic colorectal cancer surgery for endoscopically advanced tumors: A prospective comparative clinical study. World J Surg. 30:605–611. 2006. View Article : Google Scholar : PubMed/NCBI

21 

LeCun Y, Bengio Y and Hinton G: Deep learning. Nature. 521:436–444. 2015. View Article : Google Scholar : PubMed/NCBI

22 

Duch W, Swaminathan K and Meller J: Artificial intelligence approaches for rational drug design and discovery. Curr Pharm Des. 13:1497–1508. 2007. View Article : Google Scholar : PubMed/NCBI

23 

Ehteshami Bejnordi B, Veta M, Johannes van Diest P, van Ginneken B, Karssemeijer N, Litjens G, van der Laak J, Hermsen M, Manson QF, Balkenhol M, et al: Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer. JAMA. 318:2199–2210. 2017. View Article : Google Scholar : PubMed/NCBI

24 

Khosravi P, Kazemi E, Imielinski M, Elemento O and Hajirasouliha I: Deep Convolutional neural networks enable discrimination of heterogeneous digital pathology images. EBioMedicine. 27:317–328. 2018. View Article : Google Scholar : PubMed/NCBI

25 

Bhinder B, Gilvary C, Madhukar NS and Elemento O: Artificial intelligence in cancer research and precision medicine. Cancer Discov. 11:900–915. 2021. View Article : Google Scholar : PubMed/NCBI

26 

TNM Classifcation of Maligant Tumours, Eighth Edition. Wiley Blackwell; Hoboken: 2016

27 

Yukimoto R, Uemura M, Tsuboyama T, Sekido Y, Hata T, Ogino T, Miyoshi N, Takahashi H, Kida A, Furuyashiki M, et al: Efficacy of PET/CT in diagnosis of regional lymph node metastases in patients with colorectal cancer: Retrospective cohort study. BJS Open. 6:2022. View Article : Google Scholar : PubMed/NCBI

28 

Japanese Classification of Colorectal, Appendiceal and Anal Carcinoma: The 3d English Edition [Secondary Publication]. J Anus Rectum Colon. 3:175–195. 2019. View Article : Google Scholar : PubMed/NCBI

29 

Benson AB, Venook AP, Al-Hawary MM, Azad N, Chen YJ, Ciombor KK, Cohen S, Cooper HS, Deming D, Garrido-Laguna I, et al: Rectal cancer, version 2.2022, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 20:1139–1167. 2022. View Article : Google Scholar : PubMed/NCBI

30 

Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, Dancey J, Arbuck S, Gwyther S, Mooney M, et al: New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur J Cancer. 45:228–247. 2009. View Article : Google Scholar : PubMed/NCBI

31 

Krizhevsky AS and Hinton GEI: Imagenet classification with deep convolutional neural networks. Adv Neural Inf Process Syst. 25:1097–1105. 2012.PubMed/NCBI

32 

Minami S, Saso K, Miyoshi N, Fujino S, Kato S, Sekido Y, Hata T, Ogino T, Takahashi H, Uemura M, et al: Diagnosis of depth of submucosal invasion in colorectal cancer with AI using deep learning. Cancers (Basel). 14:53612022. View Article : Google Scholar : PubMed/NCBI

33 

Yamashita R, Long J, Longacre T, Peng L, Berry G, Martin B, Higgins J, Rubin DL and Shen J: Deep learning model for the prediction of microsatellite instability in colorectal cancer: A diagnostic study. Lancet Oncol. 22:132–141. 2021. View Article : Google Scholar : PubMed/NCBI

34 

Jiao Y, Li J, Qian C and Fei S: Deep learning-based tumor microenvironment analysis in colon adenocarcinoma histopathological whole-slide images. Comput Methods Programs Biomed. 204:1060472021. View Article : Google Scholar : PubMed/NCBI

35 

Gupta R, Srivastava D, Sahu M, Tiwari S, Ambasta RK and Kumar P: Artificial intelligence to deep learning: Machine intelligence approach for drug discovery. Mol Divers. 25:1315–1360. 2021. View Article : Google Scholar : PubMed/NCBI

36 

Liu X, Zhang D, Liu Z, Li Z, Xie P, Sun K, Wei W, Dai W, Tang Z, Ding Y, et al: Deep learning radiomics-based prediction of distant metastasis in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy: A multicentre study. EBioMedicine. 69:1034422021. View Article : Google Scholar : PubMed/NCBI

37 

Feng L, Liu Z, Li C, Li Z, Lou X, Shao L, Wang Y, Huang Y, Chen H, Pang X, et al: Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: A multicentre observational study. Lancet Digit Health. 4:e8–e17. 2022. View Article : Google Scholar : PubMed/NCBI

38 

Miyoshi N: AI application for surgery. J Jpn Soc Precis Eng. 88:9–11. 2022. View Article : Google Scholar

39 

Lu L, Dercle L, Zhao B and Schwartz LH: Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging. Nat Commun. 12:66542021. View Article : Google Scholar : PubMed/NCBI

40 

Horvat N, Veeraraghavan H, Khan M, Blazic I, Zheng J, Capanu M, Sala E, Garcia-Aguilar J, Gollub MJ and Petkovska I: MR Imaging of rectal cancer: Radiomics analysis to assess treatment response after neoadjuvant therapy. Radiology. 287:833–843. 2018. View Article : Google Scholar : PubMed/NCBI

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Copy and paste a formatted citation
Spandidos Publications style
Kato S, Miyoshi N, Fujino S, Minami S, Nagae A, Hayashi R, Sekido Y, Hata T, Hamabe A, Ogino T, Ogino T, et al: Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images. Oncol Lett 26: 474, 2023.
APA
Kato, S., Miyoshi, N., Fujino, S., Minami, S., Nagae, A., Hayashi, R. ... Eguchi, H. (2023). Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images. Oncology Letters, 26, 474. https://doi.org/10.3892/ol.2023.14062
MLA
Kato, S., Miyoshi, N., Fujino, S., Minami, S., Nagae, A., Hayashi, R., Sekido, Y., Hata, T., Hamabe, A., Ogino, T., Tei, M., Kagawa, Y., Takahashi, H., Uemura, M., Yamamoto, H., Doki, Y., Eguchi, H."Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images". Oncology Letters 26.5 (2023): 474.
Chicago
Kato, S., Miyoshi, N., Fujino, S., Minami, S., Nagae, A., Hayashi, R., Sekido, Y., Hata, T., Hamabe, A., Ogino, T., Tei, M., Kagawa, Y., Takahashi, H., Uemura, M., Yamamoto, H., Doki, Y., Eguchi, H."Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images". Oncology Letters 26, no. 5 (2023): 474. https://doi.org/10.3892/ol.2023.14062
Copy and paste a formatted citation
x
Spandidos Publications style
Kato S, Miyoshi N, Fujino S, Minami S, Nagae A, Hayashi R, Sekido Y, Hata T, Hamabe A, Ogino T, Ogino T, et al: Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images. Oncol Lett 26: 474, 2023.
APA
Kato, S., Miyoshi, N., Fujino, S., Minami, S., Nagae, A., Hayashi, R. ... Eguchi, H. (2023). Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images. Oncology Letters, 26, 474. https://doi.org/10.3892/ol.2023.14062
MLA
Kato, S., Miyoshi, N., Fujino, S., Minami, S., Nagae, A., Hayashi, R., Sekido, Y., Hata, T., Hamabe, A., Ogino, T., Tei, M., Kagawa, Y., Takahashi, H., Uemura, M., Yamamoto, H., Doki, Y., Eguchi, H."Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images". Oncology Letters 26.5 (2023): 474.
Chicago
Kato, S., Miyoshi, N., Fujino, S., Minami, S., Nagae, A., Hayashi, R., Sekido, Y., Hata, T., Hamabe, A., Ogino, T., Tei, M., Kagawa, Y., Takahashi, H., Uemura, M., Yamamoto, H., Doki, Y., Eguchi, H."Treatment response prediction of neoadjuvant chemotherapy for rectal cancer by deep learning of colonoscopy images". Oncology Letters 26, no. 5 (2023): 474. https://doi.org/10.3892/ol.2023.14062
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