Prediction of occult lymph node metastasis by metabolic parameters in patients with clinically N0 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.

Identification of Metastatic Lymph Nodes Using Indocyanine Green Fluorescence Imaging

Indocyanine green (ICG) has been used to detect several types of tumors; however, its ability to detect metastatic lymph nodes (LNs) remains unclear. Our goal was to determine the feasibility of ICG in detecting metastatic LNs. We established a mouse model and evaluated the potential of ICG. The feasibility of detecting metastatic LNs was also evaluated in patients with lung or esophageal cancer, detected with computed tomography (CT) or positron-emission tomography (PET)/CT, and scheduled to undergo surgical resection. Tumors and metastatic LNs were successfully detected in the mice. In the clinical study, the efficacy of ICG was evaluated in 15 tumors and fifty-four LNs with suspected metastasis or anatomically key regional LNs. All 15 tumors were successfully detected. Among the fifty-four LNs, eleven were pathologically confirmed to have metastasis; all eleven were detected in ICG fluorescence imaging, with five in CT and seven in PET/CT. Furthermore, thirty-four LNs with no signals were pathologically confirmed as nonmetastatic. Intravenous injection of ICG may be a useful tool to detect metastatic LNs and tumors. However, ICG is not a targeting agent, and its relatively low fluorescence makes it difficult to use to detect tumors in vivo. Therefore, further studies are needed to develop contrast agents and devices that produce increased fluorescence signals.

Artificial intelligence-based computer-aided diagnosis system supports diagnosis of lymph node metastasis in esophageal squamous cell carcinoma: A multicenter study

Background

This study aimed to develop an artificial intelligence-based computer-aided diagnosis system (AI-CAD) emulating the diagnostic logic of radiologists for lymph node metastasis (LNM) in esophageal squamous cell carcinoma (ESCC) patients, which contributed to clinical treatment decision-making.

Methods

A total of 689 ESCC patients with PET/CT images were enrolled from three hospitals and divided into a training cohort and two external validation cohorts. 452 CT images from three publicly available datasets were also included for pretraining the model. Anatomic information from CT images was first obtained automatically using a U-Net-based multi-organ segmentation model, and metabolic information from PET images was subsequently extracted using a gradient-based approach. AI-CAD was developed in the training cohort and externally validated in two validation cohorts.

Results

The AI-CAD achieved an accuracy of 0.744 for predicting pathological LNM in the external cohort and a good agreement with a human expert in two external validation cohorts (kappa = 0.674 and 0.587, p < 0.001). With the aid of AI-CAD, the human expert's diagnostic performance for LNM was significantly improved (accuracy [95% confidence interval]: 0.712 [0.669-0.758] vs. 0.833 [0.797-0.865], specificity [95% confidence interval]: 0.697 [0.636-0.753] vs. 0.891 [0.851-0.928]; p < 0.001) among patients underwent lymphadenectomy in the external validation cohorts.

Conclusions

The AI-CAD could aid in preoperative diagnosis of LNM in ESCC patients and thereby support clinical treatment decision-making.

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.

Prediction of cervical metastasis and survival in cN0 oral cavity cancer using tumour 18F-FDG PET/CT functional parameters

PURPOSE

Oral cavity squamous cell carcinoma (OCC) can spread to the neck without apparent lymphadenopathy. Pretreatment detection or prediction of occult metastasis might contribute to proper management of clinically node-negative (cN0) OCC. We examined the role of tumour quantitative 18-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/computed tomography (CT) measurements for predicting OCC occult metastasis and survival.

METHODS

This study included 130 cN0 OCC patients who underwent ¹⁸F-FDG PET/CT scanning and subsequent curative surgery and neck dissection. Maximum, peak, and mean standardized uptake value (SUV_max, SUV_peak, and SUV_mean), metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were measured on pretreatment ¹⁸F-FDG PET/CT. Binary logistic regression was used to identify factors predicting occult cervical metastasis. Univariate and multivariate Cox proportional hazard regression were used to find factors associated with overall survival (OS).

RESULTS

Pathological cervical metastasis (pN +) was found in 29 (22.3%) patients. Age, tumour differentiation, lymphovascular invasion, and T classification were significantly associated with pN + (all P < 0.05). After adjustment for these factors, MTV and TLG independently predicted pN + (P < 0.05). Invasion depth, lymphovascular invasion, T and N classifications, and overall TNM stage were significantly associated with OS. After adjustment for these factors, SUV_max and TLG independently predicted OS (all P < 0.05). Patients with TLG > 9.3 g had a 5.7-fold increased risk of overall mortality.

CONCLUSIONS

Tumour ¹⁸F-FDG PET/CT parameters might predict occult metastasis and survival in cN0 OCC patients.

Tumor SUVs on 18F-FDG PET/CT and Aggressive Pathological Features in Esophageal Squamous Cell Carcinoma

PURPOSE

Considerable discrepancies are observed between clinical staging and pathological staging after surgical resection in patients with esophageal squamous cell carcinoma (ESCC). In this study, we examined the relationships between tumor SUVs on FDG PET/CT and aggressive pathological features in resected ESCC patients.

METHODS

A total of 220 patients with surgically resected clinical stage I-II ESCC without neoadjuvant treatment were retrospectively analyzed. SUVmax of the primary tumor was measured on pretreatment FDG PET/CT. Pathological features included depth of tumor invasion, lymph node metastasis, tumor differentiation, lymphatic vessel tumor embolus, perineural invasion, Ki-67 index, and p53 protein expression. Receiver operating characteristic curve analysis was used to determine an optimal cutoff of SUVmax to predict pathologically advanced disease. Differences in pathological features associated with SUVmax were examined by t test or χ test.

RESULTS

The number of patients upstaged from clinical stage I-II to pathological stage III-IV was 43 (19.5%). Receiver operating characteristic curve analysis showed that the optimal cutoff SUVmax of 4.0 had good performance for predicting locally advanced disease (area under the receiver operating characteristic curve = 0.844, P < 0.001). Higher tumor SUVmax was significantly associated with advanced depth of tumor invasion (deeper than submucosa, P < 0.001), positive lymph node metastasis (P < 0.001), presence of lymphatic vessel tumor embolus (P < 0.001), presence of perineural invasion (P < 0.001), higher Ki-67 index (P = 0.025), and poor tumor differentiation (P = 0.039).

CONCLUSIONS

SUVmax measured on pretreatment FDG PET/CT is significantly associated with aggressive pathological features and may help clinicians identify patients at risk of advanced disease.

Nomogram using F-18 fluorodeoxyglucose positron emission tomography/computed tomography for preoperative prediction of lymph node metastasis in gastric cancer

BACKGROUND

Lymph node (LN) metastasis is an important prognostic factor in patients with gastric cancer (GC). However, the evaluation of LN metastasis status in the preoperative setting is not accurate. Therefore, precise preoperative prediction of LN metastasis status is crucial for optimal treatment in patients with GC.

AIM

To develop a preoperative nomogram for LN metastasis using F-18 fluorodeoxyglucose (F-18 FDG) positron emission tomography/computed tomography (PET/CT) and preoperative laboratory test findings in GC.

METHODS

In this study, the data of 566 GC patients who underwent preoperative F-18 FDG PET/CT and subsequent surgical resection were analyzed. The LN metastasis prediction model was developed in the training cohort and validated in the internal validation cohort. Routine preoperative laboratory tests, including albumin and carbohydrate antigen (CA) 19-9 were performed in all patients. Univariate and multivariable logistic regression was performed to validate the preoperative predictive indicators for LN metastasis.

RESULTS

Of the 566 patients, 232 (41%) had confirmed histopathologic LN metastasis. Univariate logistic regression revealed that the tumor location, blood hemoglobin, serum albumin levels, neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, CA 19-9, maximum standardized uptake value (SUVmax) of the primary tumor (T_SUVmax), and SUVmax of LN (N_SUVmax) were significantly associated with LN metastasis. In multivariate analysis, T_SUVmax (OR = 1.08; 95%CI: 1.02–1.15; P = 0.011) and N_SUVmax (OR = 1.49; 95%CI: 1.19–1.97; P = 0.002) were found to be significant predictive factors for LN metastasis. The LN metastasis prediction model using T_SUVmax, N_SUVmax, serum albumin, and CA 19-9 yielded an area under the curve (AUC) of 0.733 (95%CI: 0.683–0.784, P = 0.025) in the training cohort and AUC of 0.756 (95%CI: 0.678–0.833, P < 0.001) in the test cohort.

CONCLUSION

T_SUVmax and N_SUVmax measured by preoperative F-18 FDG PET/CT are independent predictive factors for LN metastasis in GC.

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

OBJECTIVE

The aim of this study was to investigate the capability of F-FDG PET/computed tomography (CT)-related metabolic parameters to predict lymph node metastasis (LNM) and occult lymph node metastasis (OLNM) in patients with esophageal squamous cell carcinoma (ESCC).

METHODS

Totally 84 patients undergoing curative esophagectomy with lymph node dissection were enrolled in this study. Metabolic tumor volume (MTV) was measured using threshold-based methods with a threshold of 40% maximum standardized uptake value (SUVmax). The derivative of the volume (V)-threshold (T) function (volume difference/threshold difference) was defined as the heterogeneity factor (HF). In addition, SUVmax, SUVmean, total lesion glycolysis (TLG), maximum tumor-to-blood SUV ratio (SURmax), SURmean and several clinicopathologic parameters were analyzed to identify risk factors of LNM and OLNM.

RESULTS

SUVmax, SUVmean, MTV, TLG, SURmax, SURmean and HF were significantly different between LNM (+) and LNM (-). The optimal cut-off values of those parameters were 12.5, 8.34, 15.01, 117.185, 7.885, 4.855 and 0.300, respectively. Logistic regression analysis showed that MTV (OR = 1.127, P = 0.04) and SURmax (OR = 1.446, P = 0.004) were independent predictors of LNM, with sensitivity and specificity were 51.2%, 83.7% vs. 53.7%, 79.1%. In univariate and multivariate analysis, MTV was the sole parameter associated with OLMN (P = 0.024).

CONCLUSION

MTV and SURmax were statistically significant predictors of LNM in patients with ESCC, while MTV was a predictor of OLNM. High SURmax and MTV may indicate that the treatment planning should be tailored, which may improve patient prognosis.

Improved detection of metastatic lymph nodes in oesophageal squamous cell carcinoma by combined interpretation of fluorine-18-fluorodeoxyglucose positron-emission tomography/computed tomography

Background

We sought to evaluate the diagnostic performance of fluorine-18-fluorodeoxyglucose positron-emission tomography/computed tomography (¹⁸F-FDG PET/CT) in the detection of metastatic lymph nodes by combined interpretation of PET/CT images in patients with oesophageal squamous cell carcinoma.

Methods

Two hundred three patients with oesophageal squamous cell carcinoma underwent ¹⁸F-FDG PET/CT before oesophagectomy and lymph node dissection. Maximum standardized uptake value (SUV_max), mean Hounsfield unit (HU), short axis diameter (size), and visual CT attenuation (high, iso-, low) were evaluated on noncontrast CT and PET images following PET/CT scan. In this combined interpretation protocol, the high attenuated lymph nodes were considered benign, even if the SUV_max value was high. The diagnostic accuracy of each method was compared using the postoperative histologic result as a reference standard.

Results

A total of 1099 nodal stations were dissected and 949 nodal stations were proven to demonstrate metastasis. SUV_max and size of the malignant lymph nodes were higher than those of the benign nodes, and visual CT attenuation was significantly different among the two groups (P < 0.001). Using cutoff values of 2.6 for SUV_max and 10.2 mm for size, the combined interpretation of an SUV_max of more than 2.6 with iso- or low CT attenuation [area under the curve (AUC): 0.846, 95% confidence interval (CI): 0.824–0.867] showed significantly better diagnostic performance for detecting malignant lymph nodes than SUV_max only (AUC: 0.791, 95% CI: 0.766–0.815) and size (AUC: 0.693, 95% CI: 0.665–0.720) methods (P < 0.001) in a receiver operating characteristic curve analysis.

Conclusions

The diagnostic accuracy of PET/CT for nodal metastasis in oesophageal squamous cell carcinoma was improved by the combined interpretation of ¹⁸F-FDG uptake and visual CT attenuation pattern.

Diagnostic value of 18F-fluorodeoxyglucose positron-emission tomography/computed tomography for preoperative lymph node metastasis of esophageal cancer: A meta-analysis

OBJECTIVE

We determined the value of F-fluorodeoxyglucose positron-emission tomography/computed tomography (FDG PET/CT) for the assessment of preoperative lymph node metastases in patients with esophageal cancer.

METHODS

We searched electronic database indexes for articles on PET/CT assessment of lymph node status. Information including true positives, false positives, false negatives, and true negatives was obtained. Based on these data, the pooled sensitivity, specificity, diagnostic odds ratio, and likelihood ratio were calculated using bivariate models and receiver operating characteristic curves (ROCs) were drawn.

RESULTS

Patients without neoadjuvant treatment had a pooled sensitivity and specificity (95% confidence interval [CI]) of 0.57 (0.45-0.69) and 0.91 (0.85-0.95), respectively. Patients who received neoadjuvant treatment had a pooled sensitivity and specificity of 0.53 (0.35-0.70) and 0.96 (0.86-0.99), respectively.

CONCLUSIONS

The PET/CT has a high diagnostic specificity but its diagnostic sensitivity is low; thus, its diagnosis findings cannot accurately reflect the lymph node status.

Esophageal cancer N staging study with endoscopic ultrasonography

Esophageal cancer staging is important for the treatment of esophageal cancer. Endoscopic ultrasonography (EUS) is a common diagnostic tool for esophageal cancer prior to surgery. However, EUS is unable to accurately discriminate the N-staging of lymph nodes. In order to distinguish an optimized standard for malignant lymph node diagnosis, the present study compared lymph nodes detected by EUS and surgery. A total of 112 patients were preoperatively examined with EUS and staged according to the 7th Edition of the American Joint Committee on Cancer Staging Manual. The results of EUS were compared with surgical findings. The critical values of long diameter, short diameter and lymph node number detected by EUS were >7.5, >5.5 mm and >2, respectively; indexes, including long diameter >7.5 mm, short diameter >5.5 mm, round, low echo, edge smooth, near lesion and detected lymph node number (>2) and T3/4 staging, met significance in the EUS group compared with the surgical group (P<0.05). Furthermore, the area under curve (AUC) value of the EUS (0.801) was superior to the conventional, surgical method (0.779). Although EUS improved the diagnostic accuracy of esophageal N staging, it was not able to satisfactorily distinguish between N2 and N3 staging. Advancements in EUS may enhance its detection ability, further improving the diagnostic accuracy of lymph node metastasis.

PET/Computed Tomography Scanning and Precision Medicine: Esophageal Cancer

Esophageal cancer commonly has a poor prognosis, which requires an accurate diagnosis and early treatment to improve outcome. Other modalities for staging, such as endoscopic ultrasound imaging and computed tomography (CT) scans, have a role in diagnosis and staging. However, PET with fluorine-18 fluoro-2-deoxy-d-glucose/CT (FDG PET/CT) scanning allows for improved detection of distant metastatic disease and can help to prevent unnecessary interventions that would increase morbidity. FDG PET/CT scanning is valuable in the neoadjuvant chemotherapy assessment and predicting survival outcomes subsequent to surgery. FDG PET/CT scanning detects recurrent disease and metastases in follow-up.

Predictive Value of 18F-FDG PET/CT for Axillary Lymph Node Metastasis in Invasive Ductal Breast Cancer

BACKGROUND

This study assessed whether primary tumor maximum standardized uptake value (pSUV_max) measured by ¹⁸F-fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) could improve the prediction of axillary lymph node (ALN) metastasis in invasive ductal breast cancer (IDC).

METHODS

In this study, 128 IDC patients who underwent pretreatment ¹⁸F-FDG PET/CT and surgical resection of primary tumor with sentinel lymph node biopsy, ALN dissection, or both were analyzed. All the patients were classified as five molecular subtypes. The optimal cutoff values of pSUVmax for all the patients and each molecular subtype for the prediction of ALN metastasis were determined using receiver operating characteristic (ROC) analysis. Furthermore, the prognostic accuracy of ALN metastasis was assessed using c-statistics.

RESULTS

The findings showed ALN metastasis in 52 patients (40.6%). The ¹⁸F-FDG PET/CT procedure had a sensitivity of 48.1% and a specificity of 94.7% for ALN metastasis. In the ROC analysis of pSUVmax for ALN metastasis, the optimal cutoff value was 3.9 for all the patients, 2.8 for the luminal A subtype, 3.3 for the luminal B (human epidermal growth factor receptor 2 [HER2]-negative) subtype, 5.3 for the luminal B (HER2-positive) subtype, 12.7 for the HER2-positive subtype, and 11.5 for the triple-negative subtype. A predictive ALN metastasis model using nodal ¹⁸F-FDG uptake finding gave a c-statistic of 0.714, and a model combination of nodal ¹⁸F-FDG uptake finding with pSUV_max of all the patients gave a c-statistic of 0.736 (P = 0.3926). However, the combination of nodal the ¹⁸F-FDG uptake finding with the pSUV_max of each molecular subtype gave a c-statistic of 0.791 (P = 0.0047).

CONCLUSIONS

Combining the pSUV_max of each molecular subtype with the nodal ¹⁸F-FDG uptake finding can improve the prediction of ALN metastasis in IDC.

Restaging oesophageal cancer after neoadjuvant therapy with (18)F-FDG PET-CT: identifying interval metastases and predicting incurable disease at surgery

OBJECTIVES

It is unknown whether restaging oesophageal cancer after neoadjuvant therapy with positron emission tomography-computed tomography (PET-CT) is more sensitive than contrast-enhanced CT for disease progression. We aimed to determine this and stratify risk.

METHODS

This was a retrospective study of patients staged before neoadjuvant chemotherapy (NAC) by (18)F-FDG PET-CT and restaged with CT or PET-CT in a single centre (2006-2014).

RESULTS

Three hundred and eighty-three patients were restaged (103 CT, 280 PET-CT). Incurable disease was detected by CT in 3 (2.91 %) and PET-CT in 17 (6.07 %). Despite restaging unsuspected incurable disease was encountered at surgery in 34/336 patients (10.1 %). PET-CT was more sensitive than CT (p = 0.005, McNemar's test). A new classification of FDG-avid nodal stage (mN) before NAC (plus tumour FDG-avid length) predicted subsequent progression, independent of conventional nodal stage. The presence of FDG-avid nodes after NAC and an impassable tumour stratified risk of incurable disease at surgery into high (75.0 %; both risk factors), medium (22.4 %; either), and low risk (3.87 %; neither) groups (p < 0.001). Decision theory supported restaging PET-CT.

CONCLUSIONS

PET-CT is more sensitive than CT for detecting interval progression; however, it is insufficient in at least higher risk patients. mN stage and response (mNR) plus primary tumour characteristics can stratify this risk simply.

KEY POINTS

• Restaging (18) F-FDG-PET-CT after neoadjuvant chemotherapy identifies metastases in 6 % of patients • Restaging (18) F-FDG-PET-CT is more sensitive than CT for detecting interval progression • Despite this, at surgery 10 % of patients had unsuspected incurable disease • New concepts (FDG-avid nodal stage and response) plus tumour impassability stratify risk • Higher risk (if not all) patients may benefit from additional restaging modalities.