Abstract
Background
Advanced low rectal cancer has a non-negligible risk of lateral pelvic lymph node (LPLN) metastasis (LPLNM) and lateral local recurrence (LR) after neoadjuvant (chemo)radiotherapy and total mesorectal excision. LPLN dissection (LPLND) reduces LR but increases postoperative complications and sexual/urinary dysfunction.
Objective
The aim of this study was to develop a new radiomics-based prediction model for LPLNM in patients with rectal cancer.
Methods
A total of 247 patients with rectal cancer and enlarged LPLNs treated by (chemo)radiotherapy and LPLND were enrolled in this retrospective, multicenter study. LPLN radiomic features were extracted from pretreatment portal venous-phase computed tomography images. A radiomics score of LPLN was constructed based on the least absolute shrinkage and selection operator regression in a primary cohort of 175 patients. Model performance was assessed in terms of discrimination, calibration, and decision curve analysis, and was externally validated in 72 patients.
Results
The radiomics score showed significantly better discrimination compared with pretreatment short-axis diameter measurements in both the primary (area under the curve [AUC] 0.91 vs. 0.83, p = 0.0015) and validation (AUC 0.90 vs. 0.80, p = 0.0298) cohorts. Decision curve analysis also indicated the superiority of the radiomics score. In a subanalysis of patients with a short-axis diameter ≥ 7 mm, the radiomics nomogram, incorporating the radiomics score and LPLN shrinkage to ≤ 4 mm, had better discrimination compared with a model incorporating only LPLN shrinkage in both cohorts.
Conclusions
Radiomics-based prediction modeling provides individualized risk estimation of LPLNM in rectal cancer patients treated with (chemo)radiotherapy, and outperforms measurements of pretreatment LPLN diameter.
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References
Kapiteijn E, Marijnen CA, Nagtegaal ID, et al. Preoperative radiotherapy combined with total mesorectal excision for resectable rectal cancer. N Engl J Med. 2001;345:638–46.
Sauer R, Becker H, Hohenberger W, et al. Preoperative versus postoperative chemoradiotherapy for rectal cancer. N Engl J Med. 2004;351:1731–40.
Bosset JF, Collette L, Calais G, et al. Chemotherapy with preoperative radiotherapy in rectal cancer. N Engl J Med. 2006;355:1114–23.
Akiyoshi T, Watanabe T, Miyata S, Kotake K, Muto T, Sugihara K. Results of a Japanese nationwide multi-institutional study on lateral pelvic lymph node metastasis in low rectal cancer: is it regional or distant disease? Ann Surg. 2012;255:1129–34.
Hashiguchi Y, Muro K, Saito Y, et al. Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2019 for the treatment of colorectal cancer. Int J Clin Oncol. 2020;25:1–42.
Georgiou P, Tan E, Gouvas N, et al. Extended lymphadenectomy versus conventional surgery for rectal cancer: a meta-analysis. Lancet Oncol. 2009;10:1053–62.
Benson AB, Venook AP, Al-Hawary MM, et al. Rectal cancer, version 2.2018, NCCN clinical practice guidelines in oncology. J Natl Compr Cancer Netw. 2018;16:874–901.
Ogura A, Konishi T, Cunningham C, et al. Neoadjuvant (chemo)radiotherapy with total mesorectal excision only is not sufficient to prevent lateral local recurrence in enlarged nodes: results of the multicenter lateral node study of patients with low cT3/4 rectal cancer. J Clin Oncol. 2019;37:33–43.
Akiyoshi T, Ueno M, Matsueda K, et al. Selective lateral pelvic lymph node dissection in patients with advanced low rectal cancer treated with preoperative chemoradiotherapy based on pretreatment imaging. Ann Surg Oncol. 2014;21:189–96.
Akiyoshi T, Toda S, Tominaga T, et al. Prognostic impact of residual lateral lymph node metastasis after neoadjuvant (chemo)radiotherapy in patients with advanced low rectal cancer. BJS Open. 2019;3:822–9.
Kim HJ, Choi GS, Park JS, et al. Optimal treatment strategies for clinically suspicious lateral pelvic lymph node metastasis in rectal cancer. Oncotarget. 2017;8:100724–33.
Ishihara S, Kawai K, Tanaka T, et al. Oncological outcomes of lateral pelvic lymph node metastasis in rectal cancer treated with preoperative chemoradiotherapy. Dis Colon Rectum. 2017;60:469–76.
Malakorn S, Yang Y, Bednarski BK, et al. Who should get lateral pelvic lymph node dissection after neoadjuvant chemoradiation? Dis Colon Rectum. 2019;62:1158–66.
Aerts HJ, Velazquez ER, Leijenaar RT, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014;5:4006.
Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data. Radiology. 2016;278:563–77.
Huang YQ, Liang CH, He L, et al. Development and validation of a radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer. J Clin Oncol. 2016;34:2157–64.
Liu Z, Zhang XY, Shi YJ, et al. Radiomics analysis for evaluation of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Clin Cancer Res. 2017;23:7253–62.
Horvat N, Veeraraghavan H, Khan M, et al. MR imaging of rectal cancer: radiomics analysis to assess treatment response after neoadjuvant therapy. Radiology. 2018;287:833–43.
Akiyoshi T, Matsueda K, Hiratsuka M, et al. Indications for lateral pelvic lymph node dissection based on magnetic resonance imaging before and after preoperative chemoradiotherapy in patients with advanced low-rectal cancer. Ann Surg Oncol. 2015;22 Suppl 3:S614–20.
Fedorov A, Beichel R, Kalpathy-Cramer J, et al. 3D Slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging. 2012;30:1323–41.
Griethuysen JJM, Fedorov A, Parmar C, et al. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77:e104–7.
Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15:155–63.
Tibshirani R. The lasso method for variable selection in the Cox model. Stat Med. 1997;16:385–95.
Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Mak. 2006;26:565–74.
Ogura A, Konishi T, Beets GL, et al. Lateral nodal features on restaging magnetic resonance imaging associated with lateral local recurrence in low rectal cancer after neoadjuvant chemoradiotherapy or radiotherapy. JAMA Surg. 2019;154(9):e192172.
Kim TG, Park W, Choi DH, et al. Factors associated with lateral pelvic recurrence after curative resection following neoadjuvant chemoradiotherapy in rectal cancer patients. Int J Colorectal Dis. 2014;29:193–200.
Brown G, Richards CJ, Bourne MW, et al. Morphologic predictors of lymph node status in rectal cancer with use of high-spatial-resolution MR imaging with histopathologic comparison. Radiology. 2003;227:371–7.
Cong M, Feng H, Ren JL, et al. Development of a predictive radiomics model for lymph node metastases in pre-surgical CT-based stage IA non-small cell lung cancer. Lung Cancer. 2020;139:73–9.
Ji GW, Zhang YD, Zhang H, et al. Biliary tract cancer at CT: a radiomics-based model to predict lymph node metastasis and survival outcomes. Radiology. 2019;290:90–8.
Tan X, Ma Z, Yan L, Ye W, Liu Z, Liang C. Radiomics nomogram outperforms size criteria in discriminating lymph node metastasis in resectable esophageal squamous cell carcinoma. Eur Radiol. 2019;29:392–400.
Zhu H, Zhang X, Li X, Shi Y, Zhu H, Sun Y. Prediction of pathological nodal stage of locally advanced rectal cancer by collective features of multiple lymph nodes in magnetic resonance images before and after neoadjuvant chemoradiotherapy. Chin J Cancer Res. 2019;31:984–92.
Cercek A, Roxburgh CSD, Strombom P, et al. Adoption of total neoadjuvant therapy for locally advanced rectal cancer. JAMA Oncol. 2018;4:e180071.
Konishi T, Shinozaki E, Murofushi K, et al. Phase II trial of neoadjuvant chemotherapy, chemoradiotherapy, and laparoscopic surgery with selective lateral node dissection for poor-risk low rectal cancer. Ann Surg Oncol. 2019;26:2507–13.
Maas M, Nelemans PJ, Valentini V, et al. Long-term outcome in patients with a pathological complete response after chemoradiation for rectal cancer: a pooled analysis of individual patient data. Lancet Oncol. 2010;11:835–44.
van Timmeren JE, Leijenaar RTH, van Elmpt W, et al. Test-retest data for radiomics feature stability analysis: generalizable or study-specific? Tomography. 2016;2:361–5.
Varghese BA, Hwang D, Cen SY, et al. Reliability of CT-based texture features: phantom study. J Appl Clin Med Phys. 2019;20:155–63.
Bagher-Ebadian H, Siddiqui F, Liu C, Movsas B, Chetty IJ. On the impact of smoothing and noise on robustness of CT and CBCT radiomics features for patients with head and neck cancers. Med Phys. 2017;44:1755–70.
Yang F, Dogan N, Stoyanova R, Ford JC. Evaluation of radiomic texture feature error due to MRI acquisition and reconstruction: a simulation study utilizing ground truth. Phys Med. 2018;50:26–36.
Fiset S, Welch ML, Weiss J, et al. Repeatability and reproducibility of MRI-based radiomic features in cervical cancer. Radiother Oncol. 2019;135:107–14.
Funding
This study was supported in part by a Japanese Foundation for Research and Promotion of Endoscopy Grant, and JSPS KAKENHI Grant Number 20K09022.
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Conception and design: Takashi Akiyoshi. Acquisition of data: All authors. Analysis and interpretation of data: Ryota Nakanishi, Takashi Akiyoshi, Shigeo Toda, Senzo Taguchi, Yu Murakami, and Koji Oba. Manuscript writing: All authors. Final approval of the manuscript: All authors.
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Ryota Nakanishi, Takashi Akiyoshi, Shigeo Toda, Yu Murakami, Senzo Taguchi, Koji Oba, Yutaka Hanaoka, Toshiya Nagasaki, Tomohiro Yamaguchi, Tsuyoshi Konishi, Shuichiro Matoba, Masashi Ueno, Yosuke Fukunaga, and Hiroya Kuroyanagi declare they have no conflicts of interest.
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Nakanishi, R., Akiyoshi, T., Toda, S. et al. Radiomics Approach Outperforms Diameter Criteria for Predicting Pathological Lateral Lymph Node Metastasis After Neoadjuvant (Chemo)Radiotherapy in Advanced Low Rectal Cancer. Ann Surg Oncol 27, 4273–4283 (2020). https://doi.org/10.1245/s10434-020-08974-w
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DOI: https://doi.org/10.1245/s10434-020-08974-w