Prediction of lymph node metastasis by PET/CT metabolic parameters in patients with esophageal squamous cell carcinoma

Development and Validation of PET/CT-Based Nomogram for Preoperative Prediction of Lymph Node Status in Esophageal Squamous Cell Carcinoma

PURPOSE

This study was conducted to predict the lymph node status and survival of esophageal squamous cell carcinoma before treatment by PET-CT-related parameters.

METHODS

From January 2013 to July 2018, patients with pathologically diagnosed ESCC at our hospital were retrospectively enrolled. Completed esophagectomy and two- or three-field lymph node dissections were conducted. Those with neoadjuvant therapy were excluded. The first 65% of patients in each year were regarded as the training set and the last 35% as the test set. Nomogram was constructed by the "rms" package. Five-year, overall survival was analyzed based on the best cutoff value of risk score determined by the "survivalROC" package.

RESULTS

Ultimately, 311 patients were included with 209 in the training set and 102 in the test set. The positive rate of the lymph node in the training set was 36.8% and that in the test set was 32.4%. The C-index of the training set was 0.763 and the test set was 0.766. The decision curve analysis showed that it was superior to the previous methods based on lymph node uptake or long/short axis diameter or axial ratio. Risk score > 0.20 was significantly associated with 5-year, overall survival (p = 0.0015) in all patients.

CONCLUSIONS

The nomogram constructed from PET-CT parameters including primary tumor metabolic length and thickness can accurately predict the risk of lymph node metastasis in ESCC. The risk score calculated by our model accurately predicts the patient's 5-year overall survival.

Prediction of Individual Lymph Node Metastatic Status in Esophageal Squamous Cell Carcinoma Using Routine Computed Tomography Imaging: Comparison of Size-Based Measurements and Radiomics-Based Models

BACKGROUND

Lymph node status is vital for prognosis and treatment decisions for esophageal squamous cell carcinoma (ESCC). This study aimed to construct and evaluate an optimal radiomics-based method for a more accurate evaluation of individual regional lymph node status in ESCC and to compare it with traditional size-based measurements.

METHODS

The study consecutively collected 3225 regional lymph nodes from 530 ESCC patients receiving upfront surgery from January 2011 to October 2015. Computed tomography (CT) scans for individual lymph nodes were analyzed. The study evaluated the predictive performance of machine-learning models trained on features extracted from two-dimensional (2D) and three-dimensional (3D) radiomics by different contouring methods. Robust and important radiomics features were selected, and classification models were further established and validated.

RESULTS

The lymph node metastasis rate was 13.2% (427/3225). The average short-axis diameter was 6.4 mm for benign lymph nodes and 7.9 mm for metastatic lymph nodes. The division of lymph node stations into five regions according to anatomic lymph node drainage (cervical, upper mediastinal, middle mediastinal, lower mediastinal, and abdominal regions) improved the predictive performance. The 2D radiomics method showed optimal diagnostic results, with more efficient segmentation of nodal lesions. In the test set, this optimal model achieved an area under the receiver operating characteristic curve of 0.841-0.891, an accuracy of 84.2-94.7%, a sensitivity of 65.7-83.3%, and a specificity of 84.4-96.7%.

CONCLUSIONS

The 2D radiomics-based models noninvasively predicted the metastatic status of an individual lymph node in ESCC and outperformed the conventional size-based measurement. The 2D radiomics-based model could be incorporated into the current clinical workflow to enable better decision-making for treatment strategies.

Volumetric Evaluation of Staging 18F-FDG PET/CT Images in Patients with Esophageal Cancer

Objectives:

The aim of this study was to evaluate the metastatic potential of primary tumor and survival in esophageal cancer (EC) patients by using metabolic tumor volume (MTV) and total lesion glycolysis (TLG) from the staging ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) images. Another aim is to determine a tumor volume-based cut-off value to predict long-term survival.

Methods:

Medical records of EC patients were retrospectively evaluated. Sixty-two patients with staging ¹⁸F-FDG PET/CT and at least five years of follow-up were included in the study. The region of interest to the primary tumor and all metastatic sites was created and MTV and TLG values of the primary tumor (MTVp, TLGp) and total tumor volume (MTVt and TLGt) values were obtained. The relationship between the obtained MTV and TLG values and short-time (one-year) and long time (five-year) survival was investigated.

Results:

Significant factors on survival were determined as lymph node or distant metastasis (p=0.024, 0.008, respectively) at the staging PET/CT. A significant relationship between volumetric parameters of the primary tumor and total tumor burden (MTVp, TLGp, MTVwb and TLGwb) between survivors and non-survivors for one-year and five-year was detected. In receiver operating characteristics analysis, the most significant volumetric parameter was MTVwb, with area under curve 0.771 in estimated five-year survival. The best cut-off value was detected as 36.1 mL with 78% sensitivity and 75% specificity for MTVwb in determining long-term survivors.

Conclusion:

Tumor burden in ¹⁸F-FDG PET/CT images at the time of staging of patients with EC will contribute to the prediction of long-term survivors.

Development and validation of a nomogram model for the prediction of 4L lymph node metastasis in thoracic esophageal squamous cell carcinoma

Objectives

The left tracheobronchial (4L) lymph nodes (LNs) are considered as regional LNs for esophageal squamous cell carcinoma (ESCC), but there is a controversy about routine prophylactic 4L LN dissection for all resectable ESCCs. This study aimed to develop a nomogram for preoperative prediction of station 4L lymph node metastases (LNMs).

Methods

A total of 522 EC patients in the training cohort and 370 in the external validation cohort were included. The prognostic impact of station 4L LNM was evaluated, and multivariable logistic regression analyses were performed to identify independent risk factors of station 4L LNM. A nomogram model was developed based on multivariable logistic regression analysis. Model performance was evaluated in both cohorts in terms of calibration, discrimination, and clinical usefulness.

Results

The incidence of station 4L LNM was 7.9% (41/522) in the training cohort. Patients with station 4L LNM exhibited a poorer 5-year overall survival rate than those without (43.2% vs. 71.6%, p < 0.001). In multivariate logistic regression analyses, six variables were confirmed as independent 4L LNM risk factors: sex (p = 0.039), depth of invasion (p = 0.002), tumor differentiation (p = 0.016), short axis of the largest 4L LNs (p = 0.001), 4L conglomeration (p = 0.006), and 4L necrosis (p = 0.002). A nomogram model, containing six independent risk factors, demonstrated a good performance, with the area under the curve (AUC) of 0.921 (95% CI: 0.878–0.964) in the training cohort and 0.892 (95% CI: 0.830–0.954) in the validation cohort. The calibration curve showed a good agreement on the presence of station 4L LNM between the risk estimation according to the model and histopathologic results on surgical specimens. The Hosmer–Lemeshow test demonstrated a non-significant statistic (p = 0.691 and 0.897) in the training and validation cohorts, which indicated no departure from the perfect fit. Decision curve analysis indicated that the model had better diagnostic power for 4L LNM than the traditional LN size criteria.

Conclusions

This model integrated the available clinical and radiological risk factors, facilitating in the precise prediction of 4L LNM in patients with ESCC and aiding in personalized therapeutic decision-making regarding the need for routine prophylactic 4L lymphadenectomy.

PET/CT for Predicting Occult Lymph Node Metastasis in Gastric Cancer

A portion of gastric cancer patients with negative lymph node metastasis at an early stage eventually die from tumor recurrence or advanced metastasis. Occult lymph node metastasis (OLNM] is a potential risk factor for the recurrence and metastasis in these patients, and it is highly important for clinical prognosis. Positron emission tomography (PET)/computed tomography (CT) is used to assess lymph node metastasis in gastric cancer due to its advantages in anatomical and functional imaging and non-invasive nature. Among the major metabolic parameters of PET, the maximum standardized uptake value (SUVmax) is commonly used for examining lymph node status. However, SUVmax is susceptible to interference by a variety of factors. In recent years, the exploration of new PET metabolic parameters, new PET imaging agents and radiomics, has become an active research topic. This paper aims to explore the feasibility and predict the effectiveness of using PET/CT to detect OLNM. The current landscape and future trends of primary metabolic parameters and new imaging agents of PET are reviewed. For gastric cancer patients, the possibility to detect OLNM non-invasively will help guide surgeons to choose the appropriate lymph node dissection area, thereby reducing unnecessary dissections and providing more reasonable, personalized and comprehensive treatments.

Modified method to improve the diagnostic efficiency of 18F-FDG PET/CT in regional lymph node metastasis of esophageal squamous cell carcinoma

Background

Regional lymph node (LN) metastasis is a significant factor influencing the treatment choice of esophageal squamous cell carcinoma (ESCC). The performance PET/CT as an imaging evaluation method for regional LNs in ESCC, is unsatisfactory due to the lack of logical criterion. We explored how a modified criterion improved the diagnostic value of ¹⁸F-FDG PET/CT in regional LN metastasis.

Methods

The data from 111 patients with ESCC were analyzed retrospectively. All patients underwent preoperative PET/CT examination, resection of the cancer, and regional LN dissection. The PET/CT images were interpreted by two experienced diagnosticians. LNs were allocated to five subregions. Each LN was diagnosed by two diagnostic criteria of PET/CT (traditional criterion and the modified criterion) one by one across the same field, and the accuracy of PET/CT was determined using the histopathologic results as the reference standard.

Results

A total of 4,847 LNs were dissected, of which 147 were confirmed as metastases by postoperative pathology. A total of 656 LNs were screened by ¹⁸F-FDG PET/CT imaging. The determination of all 656 LNs by PET/CT was compared with the pathological results. The diagnostic accuracy of the modified and traditional criteria for the five subregions (paraesophageal, neck, upper mediastinal, middle-lower mediastinal and ventral subregions) was: 74.60% vs. 61.90%, 86.44% vs. 81.36%, 90.26% vs. 70.78%, 96.19% vs. 75.09%, and 87.91% vs. 85.71%, respectively.

Conclusions

The modified diagnostic criterion had better diagnostic efficiency because it combined PET and CT imaging data.

Characterization of 18F-fluorodeoxyglucose metabolic spatial distribution improves the differential diagnosis of indeterminate pulmonary nodules and masses with high fluorodeoxyglucose uptake

Background

The aim of this study was to investigate the value of visual assessment of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) metabolic spatial distribution (V-FMSD) in the diagnosis of indeterminate pulmonary nodules and masses with high ¹⁸F-FDG uptake.

Methods

A total of 301 patients with indeterminate pulmonary nodules or masses who underwent ¹⁸F-FDG positron emission tomography/computed tomography (PET/CT) imaging were retrospectively studied. The characteristics of ¹⁸F-FDG metabolic spatial distribution (FMSD) in the proximal and distal regions of the lesions were visually analyzed using a 5-point scoring system. The sensitivity, specificity, accuracy, and area under receiver operating characteristic curve (AUC) were compared between V-FMSD and conventional PET/CT methods for the diagnosis of hypermetabolic indeterminate pulmonary nodules and masses.

Results

The V-FMSD results showed that 180 (92.8%) malignant lesions had a score of ≥3 and 78 (72.9%) benign lesions had a score of ≤2. This indicated that the FMSD in the proximal region of malignant lesions was significantly higher than that of the distal region, and the FMSD in the proximal region of benign lesions was significantly lower than that of the distal region. V-FMSD had a specificity of 72.9%, which was markedly higher than those of the maximum standard uptake value (SUV_max; 0%, P<0.001) and the retention index (RI; 26.2%, P<0.001). The AUC of V-FMSD was 0.886, which was significantly larger than those of the SUV_max (0.626, P<0.001), RI (0.670, P<0.001), and PET/CT (0.788, P<0.05).

Conclusions

Our study found that pulmonary benign and malignant lesions have distinct FMSD characteristics. V-FMSD can therefore be used as a novel auxiliary marker to improve the diagnostic accuracy of hypermetabolic indeterminate pulmonary nodules and masses.

Prognostic value of 18F-FDG PET /CT metabolic parameters in patients with locally advanced pancreatic Cancer treated with stereotactic body radiation therapy

Background

¹⁸F-FDG PET/CT metabolic parameters have been applied as prognostic factors in multi-malignancies. However, the role in locally advanced pancreatic cancer (LAPC) was not confirmed. In this study, we investigated the prognostic value of ¹⁸F-FDG PET/CT metabolic parameters in LAPC patients treated with stereotactic body radiation therapy (SBRT).

Methods

Seventy three LAPC patients who received SBRT therapy and pre-treatment ¹⁸F-FDG PET/CT imaging from January 2012 to January 2016 were included in this retrospective study. The study aim was to evaluate the relationship between metabolic parameters with clinical factors, and the value of metabolic parameters in the prognosis of LAPC. The median of parameters was set as the cut-off value for statistical analysis. Univariate survival analysis was performed by the Kaplan Meier method and log-rank test, and multivariate analysis was carried out by a Cox proportional hazards model.

Results

Patients with lymph node metastasis or longer tumor diameters were associated with higher TLG (P < 0.05). Univariate analysis showed MTV, TLG, radiotherapy dose and chemotherapy were significantly associated with disease progression-free survival (PFS) and overall survival (OS) (P < 0.05). Lymph node metastasis and tumor longest diameter were associated with OS. Multivariate analysis demonstrated TLG, radiotherapy dose, and chemotherapy were independent factors of PFS and OS (HR: 2.307, 0.591, 0.572 and 2.145, 0.480, 0.471, P < 0.05).

Conclusions

TLG was found to be the independent prognostic factor of OS and PFS. Among clinical factors, radiotherapy dose and chemotherapy were independent prognostic factors of OS and PFS.