CT radiomics to predict high-risk intraductal papillary mucinous neoplasms of the pancreas

被引:92
作者
Chakraborty, Jayasree [1 ]
Midya, Abhishek [1 ]
Gazit, Lior [2 ]
Attiyeh, Marc [1 ]
Langdon-Embry, Liana [1 ]
Allen, Peter J. [1 ]
Do, Richard K. G. [3 ]
Simpson, Amber L. [1 ]
机构
[1] Mem Sloan Kettering Canc Ctr, Dept Surg, 1275 York Ave, New York, NY 10065 USA
[2] Mem Sloan Kettering Canc Ctr, Dept Strategy & Innovat, New York, NY 10065 USA
[3] Mem Sloan Kettering Canc Ctr, Dept Radiol, New York, NY 10065 USA
关键词
image processing; intraductal papillary mucinous neoplasms; random forest classifier; risk stratification; texture analysis; INTERNATIONAL CONSENSUS GUIDELINES; CYSTIC NEOPLASMS; MANAGEMENT; IMAGE; DYSPLASIA; PATTERNS; FEATURES;
D O I
10.1002/mp.13159
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose Methods Intraductal papillary mucinous neoplasms (IPMNs) are radiographically visible precursor lesions of pancreatic cancer. Despite standard criteria for assessing risk, only 18% of cysts are malignant at resection. Thus, a large number of patients undergo unnecessary invasive surgery for benign disease. The ability to identify IPMNs with low or high risk of transforming into invasive cancer would optimize patient selection and improve surgical decision-making. The purpose of this study was to investigate quantitative CT imaging features as markers for objective assessment of IPMN risk. This retrospective study analyzed pancreatic cyst and parenchyma regions extracted from CT scans in 103 patients to predict IPMN risk. Patients who underwent resection between 2005 and 2015 with pathologically proven branch duct (BD)-IPMN and a preoperative CT scan were included in the study. Expert pathologists categorized IPMNs as low or high risk following resection as part of routine clinical care. We extracted new radiographically inspired features as well as standard texture features and designed prediction models for the categorization of high- and low-risk IPMNs. Five clinical variables were also combined with imaging features to design prediction models. Results Conclusion Using images from 103 patients and tenfold cross-validation technique, the novel radiographically inspired imaging features achieved an area under the receiver operating characteristic curve (AUC) of 0.77, demonstrating their predictive power. The combination of these features with clinical variables obtained the best performance (AUC = 0.81). The present study demonstrates that features extracted from pretreatment CT images can predict the risk of IPMN. Development of a preoperative model to discriminate between low-risk and high-risk IPMN will improve surgical decision-making.
引用
收藏
页码:5019 / 5029
页数:11
相关论文
共 40 条
  • [1] Ahonen T, 2009, LECT NOTES COMPUT SC, V5575, P61, DOI 10.1007/978-3-642-02230-2_7
  • [2] *AM CANC SOC, 2018, CANC FACTS FIG 2018
  • [3] [Anonymous], 2010, P 2010 INT JOINT C N, DOI DOI 10.1109/IJCNN.2010.5596486
  • [4] [Anonymous], 2020, Radiology
  • [5] Development and Validation of a Multi-institutional Preoperative Nomogram for Predicting Grade of Dysplasia in Intraductal Papillary Mucinous Neoplasms (IPMNs) of the Pancreas: A Report from The Pancreatic Surgery Consortium
    Attiyeh, Marc A.
    Fernandez-del Castillo, Carlos
    Al Efishat, Mohammad
    Eaton, Anne A.
    Gonen, Mithat
    Batts, Ruqayyah
    Pergolini, Ilaria
    Rezaee, Neda
    Lillemoe, Keith D.
    Ferrone, Cristina R.
    Mino-Kenudson, Mari
    Weiss, Matthew J.
    Cameron, John L.
    Hruban, Ralph H.
    D'Angelica, Michael I.
    DeMatteo, Ronald P.
    Kingham, T. Peter
    Jarnagin, William R.
    Wolfgang, Christopher L.
    Allen, Peter J.
    [J]. ANNALS OF SURGERY, 2018, 267 (01) : 157 - 163
  • [6] Beyond imaging: The promise of radiomics
    Avanzo, Michele
    Stancanello, Joseph
    El Naqa, Issam
    [J]. PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2017, 38 : 122 - 139
  • [7] Measures of angular spread and entropy for the detection of architectural distortion in prior mammograms
    Banik, Shantanu
    Rangayyan, Rangaraj M.
    Desautels, J. E. Leo
    [J]. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2013, 8 (01) : 121 - 134
  • [8] Hospital volume and surgical mortality in the United States.
    Birkmeyer, JD
    Siewers, AE
    Finlayson, EVA
    Stukel, TA
    Lucas, FL
    Batista, I
    Welch, HG
    Wennberg, DE
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2002, 346 (15) : 1128 - 1137
  • [9] MAPS: A Quantitative Radiomics Approach for Prostate Cancer Detection
    Cameron, Andrew
    Khalvati, Farzad
    Haider, Masoom A.
    Wong, Alexander
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2016, 63 (06) : 1145 - 1156
  • [10] Imaging patterns of intraductal papillary mucinous neoplasms of the pancreas: An illustrated discussion of the International Consensus Guidelines for the Management of IPMN
    Campbell, Naomi M.
    Katz, Seth S.
    Escalon, Joanna G.
    Do, Richard K.
    [J]. ABDOMINAL IMAGING, 2015, 40 (03): : 663 - 677