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MRI features and texture analysis for the early prediction of therapeutic response to neoadjuvant chemoradiotherapy and tumor recurrence of locally advanced rectal cancer

  • Gastrointestinal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

This study aimed to evaluate the efficiency of imaging features and texture analysis (TA) based on baseline rectal MRI for the early prediction of therapeutic response to neoadjuvant chemoradiotherapy (nCRT) and tumor recurrence in patients with locally advanced rectal cancer (LARC).

Methods

Consecutive patients with LARC who underwent rectal MRI between January 2014 and December 2015 and surgical resection after completing nCRT were retrospectively enrolled. Imaging features were analyzed, and TA parameters were extracted from the tumor volume of interest (VOI) from baseline rectal MRI. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the optimal TA parameter cutoff values to stratify the patients. Logistic and Cox regression analyses were performed to assess the efficacy of each imaging feature and texture parameter in predicting tumor response and disease-free survival.

Results

In total, 78 consecutive patients were enrolled. In the logistic regression, good treatment response was associated with lower tumor location (OR = 13.284, p = 0.012), low Conv_Min (OR = 0.300, p = 0.013) and high Conv_Std (OR = 3.174, p = 0.016), Shape_Sphericity (OR = 3.170, p = 0.015), and Shape_Compacity (OR = 2.779, p = 0.032). In the Cox regression, a greater risk of tumor recurrence was related to higher cT stage (HR = 5.374, p = 0.044), pelvic side wall lymph node positivity (HR = 2.721, p = 0.013), and gray-level run length matrix_long-run low gray-level emphasis (HR = 2.268, p = 0.046).

Conclusions

Imaging features and TA based on baseline rectal MRI could be valuable for predicting the treatment response to nCRT for rectal cancer and tumor recurrence.

Key Points

• Imaging features and texture parameters of T2-weighted MR images of rectal cancer can help to predict treatment response and the risk for tumor recurrence.

• Tumor location as well as conventional and shape indices of texture features can help to predict treatment response for rectal cancer.

• Clinical T stage, positive pelvic side wall lymph nodes, and the high-order texture parameter, GLRLM_LRLGE, can help to predict tumor recurrence for rectal cancer.

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Abbreviations

18FDG-PET:

Fluorine-18 fluorodeoxyglucose positron emission tomography

ADC:

Apparent diffusion coefficient

CI:

Confidence interval

cN:

Clinical N

cT:

Clinical T

DCE:

Dynamic contrast-enhanced

DFS:

Disease-free survival

DWI:

Diffusion-weighted echo-planar imaging

EMVI:

Extramural venous invasion

GLCM:

Gray-level co-occurrence matrix

GLRLM:

Gray-level run length matrix

GLRLM_LRLGE:

Gray-level run length matrix_long-run low gray-level emphasis

GLZLM:

Gray-level zone length matrix

HR:

Hazard ratio

LARC:

Locally advanced rectal cancer

LN:

Lymph node

MRF:

Mesorectal fascia

MRI:

Magnetic resonance imaging

N+:

Lymph node metastasis positive

nCRT:

Neoadjuvant chemoradiotherapy

NGLDM:

Neighborhood gray-level different matrix

OR:

Odds ratio

pCR:

Pathologic complete response

PD:

Progressive disease

ROC:

Receiver operating characteristic

T2WI:

T2-weighted images

TA:

Texture analysis

TRG:

Tumor regression grade

VOI:

Volume of interest

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The authors declare no funding.

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Authors and Affiliations

  1. Department of Radiology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, 93 Jungbu-daero, Paldal-gu, Suwon-si, Gyeonggi-do, 16247, Republic of Korea

    Hayeong Park & Kyung Ah Kim

  2. Department of Pathology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

    Ji-Han Jung

  3. Department of Occupational and Environmental Medicine, College of Medicine, Dankook University, Cheonan, Republic of Korea

    Jeongbae Rhie

  4. Department of Radiology and Medical Research Institute, School of Medicine, Ewha Womans University, Seoul, Republic of Korea

    Sun Young Choi

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  1. Hayeong Park
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Correspondence to Kyung Ah Kim.

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Guarantor

The scientific guarantor of this publication is Kyung Ah Kim.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Jeongbae Rhie kindly provided statistical advice for this manuscript.

Jeongbae Rhie, one of the authors, has significant statistical expertise.

No complex statistical methods were necessary for this paper.

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Written informed consent was not required for this study because of the retrospective nature of the study.

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Institutional Review Board approval was obtained.

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• Retrospective

• Diagnostic or prognostic study

• Performed at one institution

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Park, H., Kim, K.A., Jung, JH. et al. MRI features and texture analysis for the early prediction of therapeutic response to neoadjuvant chemoradiotherapy and tumor recurrence of locally advanced rectal cancer. Eur Radiol 30, 4201–4211 (2020). https://doi.org/10.1007/s00330-020-06835-4

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