Patients
A total of 129 metastatic lymph nodes from 77 patients with postoperative ESCC were investigated in the current retrospective study. The study was approved by the ethics committee of Taixing People’s Hospital, Jiangsu, China. Prior written informed consent was obtained from each of the study participants. The salvage CRT or radiotherapy (RT) was administered to the ESCC patients with lymph node recurrence post-surgery from January 2015 through December 2016 at the Department of Radiotherapy of Taixing People’s Hospital in Jiangsu Province, China. We followed the following inclusion criteria for the selection of participants:
(a) Patients received curative esophagectomy and pathologically confirmed SCC; not received radiotherapy treatment either prior or postoperatively;
(b) The lymph node recurrences located within the bilateral supraclavicular region and mediastinum; the diagnostic approaches for lymph metastasis included physical examinations, B-mode ultrasound, computed tomography (CT) of the supraclavicular and thoracic region, positron emission tomography (PET)-CT and histological confirmation through biopsy;
(c) No clear contraindications to radiotherapy and chemotherapy, and no distant metastases such as heart, brain, lung, and bone; and
(d) Detailed follow-up information of patients within three years available.
Overall, 85 consecutive patients were enrolled, after exclusion, 77 were considered. The exclusion criteria were as follows:
(a) The information of follow-up was poor (n = 5);
(b) The radiotherapy treatment was administered after esophagectomy (n = 2);
(c) The pathology was not SCC (n = 1).
According to the 7th edition of American Joint Committee on Cancer (AJCC) staging, 129 lymph nodes of 77 patients were included in the study, of which 47 patients had a single lymph node metastasis, and 30 patients reported two or more lymph node metastases. The patients were randomly assigned to the training cohort and validation cohort in a ratio of about 10:3. In the training cohort, models were built and then were validated in the validation cohort. The clinic characteristics of patients in both cohorts are presented in Table 1.
Table 1
Characteristics of patients in training and validation cohorts
Characteristics
|
Training cohort
|
Validation cohort
|
P
|
Summary
|
Number of patients
|
59
|
18
|
|
77
|
Number of LN
|
102
|
27
|
|
129
|
Gender
|
|
|
|
|
Female
|
9
|
5
|
0.295
|
14
|
Male
|
50
|
13
|
63
|
Age (Median (range))
|
64 (46–79)
|
64 (50–74)
|
0.433
|
64 (46–79)
|
Number of LN per patient
|
|
|
|
|
Single
|
36
|
11
|
0.778
|
47
|
≥ 2
|
23
|
7
|
30
|
T stage
|
|
|
|
|
T1 + 2
|
26
|
11
|
0.159
|
37
|
T3 + 4
|
33
|
7
|
40
|
N involved
|
|
|
|
|
N་
|
29
|
8
|
0.792
|
37
|
N-
|
30
|
10
|
40
|
Median LN recurrence time
(month (range))
|
11 (1–72)
|
18 (5–60)
|
0.138*
|
11 (1–72)
|
POCT
|
|
|
|
|
YES
|
24
|
7
|
0.559
|
31
|
NO
|
35
|
11
|
46
|
CRT for LN
|
|
|
|
|
YES
|
40
|
9
|
0.262
|
49
|
NO
|
19
|
9
|
28
|
Median radiation dose (Gy (range))
|
60 (50–64)
|
60 (50–64)
|
0.194
|
60 (50–64)
|
Treatment response
|
|
|
|
|
response (CR + PR)
|
75
|
18
|
0.148
|
93
|
nonresponse (SD + PD)
|
27
|
9
|
36
|
Median control time of LN (month (95%CI))
|
13.0 (11.5–14.4)
|
12.0 (9.3–14.7)
|
0.109*
|
13.0 (11.9–14.0)
|
Note:
χ2 test and Fisher’s exact test for categorized variables; two-sample t-test for continues variables
* log-rank test
Abbreviations: LN, lymph node; +, metastasis positive; - metastasis negative, CRT: Concurrent chemoradiotherapy
POCT: Postoperative adjuvant chemotherapy
|
Chemo-radiotherapy (CRT)
All patients received three-dimensional conformal radiation therapy (3DCRT). The gross tumor volume (GTV) was defined as recurrent lymph nodes identified by CT scans or PET/CT. The clinical target volume (CTV) was defined as GTV with a 0.5 cm to 1.5 cm expansion range. The planning tumor volume (PTV) was ascertained by adding 0.5 cm radially to the CTV. A total dose of 50–64 (median, 60) Gy was delivered in 2 Gy per fraction five days a week. Also, twenty-eight patients received radiation therapy alone; forty-nine patients received CRT of TP (paclitaxel, 135 mg/m2 on day 1 and cisplatin, 25 mg/m2 on days 1–3, 28 days per cycle). According to toxicity levels, the dose adjustment was implemented in the second chemotherapy cycle in ten patients.
Treatment evaluation and follow-up
One month after the completion of the treatment, the therapeutic response was assessed using CT image with contrast, according to the Response Evaluation Criteria in Solid Tumors 1.1 (RECIST1.1) [19]. Patients with complete response (CR) or partial response (PR) were considered responders, while those with stable disease (SD) or progressive disease (PD) were classified as non-responders. The patients were followed at 1-or 3-month intervals by a history and physical examination, ultrasonography, and computed tomography after the completion of therapy. Local-regional failure time was calculated from the end of the first chemoradiotherapy or radiotherapy to the time of the second recurrence.
Image acquisitions and tumor segmentation
All patients underwent contrast-enhanced CT of the chest performed using a 64-channel multi-detector CT scanner (LightSpeed VCT, GE Medical Systems, Milwaukee, WI, USA) in our hospital between January 2015 and December 2016. The acquisition parameters were as follows: 120 kV; 160 mAs; 0.4 s or 0.5 s rotation time; detector collimation, 64 × 0.625 mm or 64 × 1.25 mm; the field of view, 350 mm × 350 mm; and matrix, 512 × 512. The contrast-enhanced CT was performed after a 25-second delay following intravenous administration of 85 mL of iodinated contrast material (Iohexol injection; Yangtze River Pharmaceutical Group, Jiangsu, China) at a rate of 3.0 mL/s with a pump injector. All the CT images were reconstructed with a standard kernel. These CT images were retrieved from the picture archiving and communication system (PACS).
Regarding the radiotherapy plan in the treatment planning system and AJCC 7th edition staging, two radiation oncologists with > 5 years of experience in interpreting esophageal carcinoma radiology outlined the metastatic lymph nodes in the clavicle, and mediastinal lymphatic drainage area performed manual segmentation of the metastatic lymph nodes on each patient’s CT images. 3D-slicer (https://www.slicer.org/), an open-source and free software platform for biomedical research [20], was employed for this task. These regions-of-interest (ROIs) were used in subsequent feature extraction for further analysis.
Radiomics feature extraction
Pyradiomics (http://pyradiomics.readthedocs.io/), an extension in 3D-slicer (version 4.8.1), is an open-source Python package for the extraction of radiomics features from CT imaging [21]. There were 106 features: 13 shape-based, 18 first-order, 24 Gray Level Co-occurrence Matrix (GLCM), 16 Gray Level Size Zone Matrix (GLSZM), 5 Neighboring gray-tone difference matrix (NGTDM), 14 Gray-level dependence matrix (GLDM) and 16 Gray Level Run Length Matrix (GLRLM) features (see Additional file 1: Supplementary Table S1). The ROIs were manually delineated slice-by-slice by two expert radiologists (Readers 1 and 2, with clinical experience of 10 and 8 years, respectively, in esophageal cancer radiotherapy). Reader 1 delineated the ROI again a month later. Reader 2 manually sketched the ROIs only once. The inter-class correlation coefficient (ICC) was used to determine the agreement in feature values between the observers. In our study, radiomic features with ICC greater than 0.75 were extracted, and reader 1 delineated some ROIs for the first time for further study.
Statistical analysis
All statistical analyses were performed on R software (version 3.5.3, http://www.r-project.org/). The difference in the categorical variables between the two groups was assessed with the two-sample t-test, chi-square test, or Fisher’s exact test as appropriate. The Kaplan-Meier method and log-rank test were used to estimate disease-free survival (DFS). Multivariate analyses were performed using the Cox proportional-hazards model. The least absolute shrinkage and selection operator (LASSO) with logistic regression was applied to identify optimal predictors in the training cohort by the “glmnet” package. The “ggplot2” and “pROC” packages were employed to draw ROC curves and evaluate the model performance by the AUC. The “survival” and “survminer” packages were used for survival analysis and to draw survival cures. A two-sided p-value of < 0.05 was considered statistically significant.