[Density and SUV ratios from PET/CT in the detection of mediastinal lymph node metastasis in non-small cell lung cancer]

[Research Progress in Imaging-based Diagnosis of Benign and Malignant Enlarged Lymph Nodes in Non-small Cell Lung Cancer]

Non-small cell lung cancer (NSCLC) can be detected with enlarged lymph nodes on imaging, but their benignity and malignancy are difficult to determine directly, making it difficult to stage the tumor and design radiotherapy target volumes. The clinical diagnosis of malignant lymph nodes is often based on the short diameter of lymph nodes ≥1 cm or the maximum standard uptake value ≥2.5, but the sensitivity and specificity of these criteria are too low to meet the clinical needs. In recent years, many advances have been made in diagnosing benign and malignant lymph nodes using other imaging parameters, and with the development of radiomics, deep learning and other technologies, models of mining the image information of enlarged lymph node regions further improve the diagnostic accuracy. The purpose of this paper is to review recent advances in imaging-based diagnosis of benign and malignant enlarged lymph nodes in NSCLC for more accurate and noninvasive assessment of lymph node status in clinical practice.
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Diagnostic value of NSE factor combined with ultrasound hemodynamic indexes in cervical lymph node metastasis of lung cancer

Value of neuron-specific enolase (NSE) factor combined with ultrasound hemodynamic parameters in the diagnosis of cervical lymph node metastasis of lung cancer was explored. The clinical data of 85 patients with lung cancer, admitted to Qingdao Municipal Hospital (Group) from January 2015 to December 2016, were retrospectively analyzed. According to the results of pathological examination, 47 patients with cervical lymph node metastasis were enrolled in the metastatic group and 38 patients without lymph node metastasis were enrolled in the non-metastatic group. The expression level of NSE in serum and the hemodynamic indicators of blood flow resistance index (RI) and pulsatility index (PI) were compared between the two groups. ROC curve analysis was used to analyze the diagnostic efficacy of NSE, RI, PI, and their combination in lymph node metastasis of lung cancer. The NSE, RI and PI indexes in the metastatic group were significantly higher than those in the non-metastatic group (P<0.05). The sensitivity and specificity of NSE in the diagnosis of cervical lymph node metastasis of lung cancer were 73.68 and 72.34%, respectively; the sensitivity and specificity of RI were 78.95 and 80.85%, respectively; the sensitivity and specificity of PI were 81.58 and 68.09%, respectively. Also, the sensitivity and specificity of NSE combined with RI were 89.47 and 61.70%, respectively, and the diagnostic AUC was 0.881. The sensitivity and specificity of NSE combined with PI were 92.11 and 74.47%, respectively, and the diagnostic AUC was 0.905. NSE, RI, and PI have certain diagnostic value for cervical lymph node metastasis of lung cancer, however, the combined diagnosis is more valuable, and can be used as the auxiliary diagnosis of cervical lymph node metastasis of lung cancer.

Discrimination of mediastinal metastatic lymph nodes in NSCLC based on radiomic features in different phases of CT imaging

BACKGROUND

We aimed to develop radiomic models based on different phases of computed tomography (CT) imaging and to investigate the efficacy of models for diagnosing mediastinal metastatic lymph nodes (LNs) in non-small cell lung cancer (NSCLC).

METHODS

Eighty-six NSCLC patients were enrolled in this study, and we selected 231 mediastinal LNs confirmed by pathology results as the subjects which were divided into training (n = 163) and validation cohorts (n = 68). The regions of interest (ROIs) were delineated on CT scans in the plain phase, arterial phase and venous phase, respectively. Radiomic features were extracted from the CT images in each phase. A least absolute shrinkage and selection operator (LASSO) algorithm was used to select features, and multivariate logistic regression analysis was used to build models. We constructed six models (orders 1-6) based on the radiomic features of the single- and dual-phase CT images. The performance of the radiomic model was evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV).

RESULTS

A total of 846 features were extracted from each ROI, and 10, 9, 5, 2, 2, and 9 features were chosen to develop models 1-6, respectively. All of the models showed excellent discrimination, with AUCs greater than 0.8. The plain CT radiomic model, model 1, yielded the highest AUC, specificity, accuracy and PPV, which were 0.926 and 0.925; 0.860 and 0.769; 0.871 and 0.882; and 0.906 and 0.870 in the training and validation sets, respectively. When the plain and venous phase CT radiomic features were combined with the arterial phase CT images, the sensitivity increased from 0.879 and 0.919 to 0.949 and 0979 and the NPV increased from 0.821 and 0.789 to 0.878 and 0.900 in the training group, respectively.

CONCLUSIONS

All of the CT radiomic models based on different phases all showed high accuracy and precision for the diagnosis of LN metastasis (LNM) in NSCLC patients. When combined with arterial phase CT, the sensitivity and NPV of the model was be further improved.

Impact of Computer-Aided CT and PET Analysis on Non-invasive T Staging in Patients with Lung Cancer and Atelectasis

PURPOSE

Tumor delineation within an atelectasis in lung cancer patients is not always accurate. When T staging is done by integrated 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG)-positron emission tomography (PET)/X-ray computer tomography (CT), tumors of neuroendocrine differentiation and slowly growing tumors can present with reduced FDG uptake, thus aggravating an exact T staging. In order to further exhaust information derived from [¹⁸F]FDG-PET/CT, we evaluated the impact of CT density and maximum standardized uptake value (SUVmax) for the classification of different tumor subtypes within a surrounding atelectasis, as well as possible cutoff values for the differentiation between the primary tumor and atelectatic lung tissue.

PROCEDURES

Seventy-two patients with histologically proven lung cancer and adjacent atelectasis were investigated. Non-contrast-enhanced [¹⁸F]FDG-PET/CT was performed within 2 weeks before surgery/biopsy. Boundaries of the primary within the atelectasis were determined visually on the basis of [¹⁸F]FDG uptake; CT density was quantified manually within each primary and each atelectasis.

RESULTS

CT density of the primary (36.4 Hounsfield units (HU) ± 6.2) was significantly higher compared to that of atelectatic lung (24.3 HU ± 8.3; p < 0.01), irrespective of the histological subtype. The discrimination between different malignant tumors using density analysis failed. SUVmax was increased in squamous cell carcinomas compared to adenocarcinomas. Irrespective of the malignant subtype, a possible cutoff value of 24 HU may help to exclude the presence of a primary in lesions below 24 HU, whereas a density above a threshold of 40 HU can help to exclude atelectatic lung.

CONCLUSION

Density measurements in patients with lung cancer and surrounding atelectasis may help to delineate the primary tumor, irrespective of the specific lung cancer subtype. This could improve T staging and radiation treatment planning (RTP) without additional application of a contrast agent in CT, or an additional magnetic resonance imaging (MRI), even in cases of lung tumors of neuroendocrine differentiation or in slowly growing tumors with less avidity to [¹⁸F]FDG.

Role of CT Density in PET/CT-Based Assessment of Lymphoma

PURPOSE

In patients with Hodgkin (HL) and non-Hodgkin lymphoma (NHL), primary staging, as well as intermediate and late response assessment, is often performed by integrated 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron emission tomography/X-ray computed tomography (PET/CT). The purpose of this analysis was to evaluate if findings in patients with histopathologically proven HL or NHL might correlate with semi-automated density measurements of target lesions (TLs) in the CT component of the integrated PET/CT examination.

PROCEDURES

After approval by the institutional review board, 176 lymph nodes (LN) in 90 PET/CT examinations of 90 patients were retrospectively analyzed (HL, 108 TLs out of 55 patients; NHL, 68 TLs out of 35 patients). PET/CT was performed for reasons of primary staging, response evaluation as interim PET, or as final examination after therapy, according to the clinical schedule. Analyses of TLs were performed on the basis of tracer uptake (SUV) 60 min after tracer injection and volumetric CT histogram analysis in non-contrast-enhanced CT.

RESULTS

All patients were diagnosed with HL or NHL in a pretreatment biopsy. Prior to therapy induction, staging of all patients was performed using contrast-enhanced CT of the neck to the pelvis, or by [¹⁸F]FDG PET/CT. Of the 176 TLs, 119 were classified as malignant, and 57 were benign. Malignant TLs had significantly higher CT density values compared to benign (p < 0.01).

CONCLUSION

Density measurements of TLs in patients with HL and NHL correlate with the dignity of TLs and might therefore serve as a complementary surrogate parameter for the differentiation between malignant and benign TLs. A possible density threshold in clinical routine might be a 20-Hounsfield units (HU) cutoff value to rule out benignancy in TLs that are above the 20-HU threshold.

Radiomic Analysis using Density Threshold for FDG-PET/CT-Based N-Staging in Lung Cancer Patients

PURPOSE

Mediastinal nodal (N)-staging done by integrated 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) positron emission tomography/x-ray computed tomography (PET/CT) in lung cancer patients is not always accurate. In order to reduce the need for invasive staging procedures, additional surrogate parameters for the detection of malignant lymph node infiltration would be helpful. The purpose of this study was to evaluate if radiomic semi-automated density profiling in mediastinal lymph nodes can improve preclinical N-staging, irrespective of the specific lung cancer entity.

PROCEDURES

This retrospective study was approved by the institutional review board. Two hundred forty-eight histologically proven lymph nodes in 122 lung cancer patients were investigated. In malignantly infiltrated lymph nodes, the specific lung cancer entity was histologically classified; benign lymph nodes were histologically classified as benign. Non-contrast enhanced [¹⁸F]FDG-PET/CT was performed before surgery/biopsy. Lymph node analyses were performed on the basis of FDG uptake and volumetric CT histogram analysis for metric lymph node sampling.

RESULTS

Of the 248 lymph nodes, 118 were benign, 130 malignant. Malignant lymph nodes had a significantly higher median CT density (32.4 Hounsfield units (HU) (min 5.4/max 77.5 HU)) compared to benign lymph nodes (9.3 HU (min -49.5/max 60.4 HU, p < 0.05), irrespective of the histological subtype. The discrimination between different malignant tumour subtypes by means of volumetric density analysis failed. Irrespective of the malignant subtype, a possible cutoff value of 20 HU may help differentiate between benign and malignant lymph nodes.

CONCLUSION

Density measurements in unclear mediastinal and hilar lymph nodes with equivocal FDG uptake in PET might serve as a possible surrogate parameter for N-staging in lung cancer patients, irrespective of the specific lung cancer subtype. This could also help to find possible high yield targets in cases where invasive lymph node staging is necessary.