The additional value of 18F-FDG PET/CT imaging in guiding the treatment strategy of non-tuberculous mycobacterial patients.

OBJECTIVES: Non-tuberculous mycobacteria (NTM) infection is an increasing health problem due to delaying an effective treatment. However, there are few data on 18F-FDG PET/CT for evaluating the status of NTM patients. The aim of this study was to investigate the potential value of 18F-FDG PET/CT in guiding the treatment strategy of NTM patients. METHODS: We retrospectively analyzed the cases of 23 NTM patients who underwent 18F-FDG PET/CT. The clinical data, including immune status and severity of NTM pulmonary disease (NTM-PD), were reviewed. The metabolic parameters of 18F-FDG included maximum standardized uptake value (SUVmax), SUVmax of the most FDG-avid lesion (SUVTop), SUVTop/SUVmax of the liver (SURLiver), SUVTop/SUVmax of the blood (SURBlood), metabolic lesion volume (MLV), and total lesion glycolysis (TLG). The optimal cut-off values of these parameters were determined using receiver operating characteristic curves. RESULTS: There were 6 patients (26.09%) with localized pulmonary diseases and 17 patients (73.91%) with disseminated diseases. The NTM lesions had high or moderate 18F-FDG uptake (median SUVTop: 8.2 ± 5.7). As for immune status, the median SUVTop in immunocompromised and immunocompetent patients were 5.2 ± 2.5 and 10.0 ± 6.4, respectively, with a significant difference (P = 0.038). As for extent of lesion involvement, SURLiver and SURBlood in localized pulmonary and disseminated diseases were 1.9 ± 1.1 vs. 3.8 ± 1.6, and 2.7 ± 1.8 vs. 5.5 ± 2.6, respectively, with a significant difference (P = 0.016 and 0.026). Moreover, for disease severity, SUVmax of the lung lesion (SUVI-lung) and SUVmax of the marrow (SUVMarrow) in the severe group were 7.7 ± 4.3 and 4.4 ± 2.7, respectively, significantly higher than those in the non-severe group (4.4 ± 2.0 and 2.4 ± 0.8, respectively) (P = 0.027 and 0.036). The ROC curves showed that SUVTop, SURLiver, SURBlood, SUVI-lung, and SUVMarrow had a high sensitivity and specificity for the identification of immune status, lesion extent, and severity of disease in NTM patients. CONCLUSION: 18F-FDG PET/CT is a useful tool in the diagnosis, evaluation of disease activity, immune status, and extent of lesion involvement in NTM patients, and can contribute to planning the appropriate treatment for NTM.

Habitat Imaging-Based 18F-FDG PET/CT Radiomics for the Preoperative Discrimination of Non-small Cell Lung Cancer and Benign Inflammatory Diseases.

PURPOSE: To propose and evaluate habitat imaging-based 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) radiomics for preoperatively discriminating non-small cell lung cancer (NSCLC) and benign inflammatory diseases (BIDs). METHODS: Three hundred seventeen 18F-FDG PET/CT scans were acquired from patients who underwent aspiration biopsy or surgical resection. All volumes of interest (VOIs) were semiautomatically segmented. Each VOI was separated into variant subregions, namely, habitat imaging, based on our adapted clustering-based habitat generation method. Radiomics features were extracted from these subregions. Three feature selection methods and six classifiers were applied to construct the habitat imaging-based radiomics models for fivefold cross-validation. The radiomics models whose features extracted by conventional habitat-based methods and nonhabitat method were also constructed. For comparison, the performances were evaluated in the validation set in terms of the area under the receiver operating characteristic curve (AUC). Pairwise t-test was applied to test the significant improvement between the adapted habitat-based method and the conventional methods. RESULTS: A total of 1,858 radiomics features were extracted. After feature selection, habitat imaging-based 18F-FDG PET/CT radiomics models were constructed. The AUC of the adapted clustering-based habitat radiomics was 0.7270 ± 0.0147, which showed significantly improved discrimination performance compared to the conventional methods (p <.001). Furthermore, the combination of features extracted by our adaptive habitat imaging-based method and non-habitat method showed the best performance than the other combinations. CONCLUSION: Habitat imaging-based 18F-FDG PET/CT radiomics shows potential as a biomarker for discriminating NSCLC and BIDs, which indicates that the microenvironmental variations in NSCLC and BID can be captured by PET/CT.

A subregion-based positron emission tomography/computed tomography (PET/CT) radiomics model for the classification of non-small cell lung cancer histopathological subtypes.

BACKGROUND: This study classifies lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) using subregion-based radiomics features extracted from positron emission tomography/computed tomography (PET/CT) images. METHODS: In this study, the standard 18F-fluorodeoxyglucose (FDG) PET/CT images of 150 patients with lung ADC and 100 patients with SCC were retrospectively collected from the PET Center of the First Affiliated Hospital, College of Medicine, Zhejiang University. First, the 3D feature vector of each tumor voxel (whose basis is PET value, CT value, and CT local dominant orientation) was extracted. Using K-means individual clustering and population clustering, each tumor was divided into 4 subregions that reflect intratumoral regional heterogeneity. Next, based on each subregion, 385 radiomics features were extracted. Clinical features including age, gender, and smoking history were included. Thus, there were a total of 1,543 features extracted from PET/CT images and clinical reports. Statistical tests were then used to eliminate irrelevant and redundant features, and the recursive feature elimination (RFE) algorithm was used to select the best feature subset to classify SCC and ADC. Finally, 7 types of classifiers were tested to achieve the optimized model for the classification: support vector machine (SVM) with linear kernel, SVM with radial basis function kernel (SVM-RBF), random forest, logistic regression, Gaussian process classifier, linear discriminant analysis, and the AdaBoost classifier. Furthermore, 5-fold cross-validation was applied to obtain the sensitivity, specificity, accuracy, and area under the curve (AUC) for performance evaluation. RESULTS: Our model exhibited the best performance with the subregion radiomics features and SVM-RBF classifier, with a 5-fold cross-validation sensitivity, specificity, accuracy, and AUC of 0.8538, 0.8758, 0.8623, and 0.9155, respectively. The interquartile range feature from subregion 2 of CT and the gender feature from the clinical reports are the 2 optimized features that achieved the highest comprehensive score. CONCLUSIONS: Our proposed model showed that SCC and ADC could be classified successfully using PET/CT images, which could be a promising tool to assist radiologists or medical physicists during diagnosis. The subregion-based method illustrated that non-small cell lung cancer (NSCLC) depicts intratumoral regional heterogeneity on both CT and PET images. By defining these heterogeneities through a subregion-based method, the diagnostic performance was improved. The 3D feature vector (whose basis is PET value, CT value, and CT local dominant orientation) showed superiority in reflecting NSCLC intratumoral regional heterogeneity.

Study of low-dose PET image recovery using supervised learning with CycleGAN.

PET is a popular medical imaging modality for various clinical applications, including diagnosis and image-guided radiation therapy. The low-dose PET (LDPET) at a minimized radiation dosage is highly desirable in clinic since PET imaging involves ionizing radiation, and raises concerns about the risk of radiation exposure. However, the reduced dose of radioactive tracers could impact the image quality and clinical diagnosis. In this paper, a supervised deep learning approach with a generative adversarial network (GAN) and the cycle-consistency loss, Wasserstein distance loss, and an additional supervised learning loss, named as S-CycleGAN, is proposed to establish a non-linear end-to-end mapping model, and used to recover LDPET brain images. The proposed model, and two recently-published deep learning methods (RED-CNN and 3D-cGAN) were applied to 10% and 30% dose of 10 testing datasets, and a series of simulation datasets embedded lesions with different activities, sizes, and shapes. Besides vision comparisons, six measures including the NRMSE, SSIM, PSNR, LPIPS, SUVmax and SUVmean were evaluated for 10 testing datasets and 45 simulated datasets. Our S-CycleGAN approach had comparable SSIM and PSNR, slightly higher noise but a better perception score and preserving image details, much better SUVmean and SUVmax, as compared to RED-CNN and 3D-cGAN. Quantitative and qualitative evaluations indicate the proposed approach is accurate, efficient and robust as compared to other state-of-the-art deep learning methods.

Prognostic value of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography in primary hepatic mucosa-associated lymphoid tissue lymphoma: A case report and review of the literature.

INTRODUCTION: Primary hepatic mucosa-associated lymphoid tissue (MALT) lymphoma is extremely rare and we herein report a case of a patient suffering from primary hepatic MALT lymphoma with concomitant hepatitis B virus infection. DIAGNOSTIC MODALITIES AND OUTCOME: Double masses were found in a 59-year-old Chinese female patient. We reported the laboratory results, computed tomography (CT) and fluorine-18-fluorodeoxyglucose (F-FDG) positron emission tomography (PET)/CT images among other findings. As far as we know, only 9 cases have been reported till now using F-FDG PET/CT imaging. Our patient's lesions were found to conform to standard uptake values of FDG. CONCLUSION: It indicates that hepatic MALT lymphoma can be studied with F-FDG PET/CT like other F-FDG-avid lymphomas. It was also noted that delayed-time-point FDG PET imaging may further improve the detection of the MALT lymphoma in liver. Although the patient in this case refused further treatment, potential management options, including rituximab, which is also discussed in this review.

Evaluation of the factors affecting the maximum standardized uptake value of metastatic lymph nodes in different histological types of non-small cell lung cancer on PET-CT.

BACKGROUND: To evaluate the factors affecting the maximum standardized uptake value (SUVmax) of metastatic lymph nodes in different histological types of non-small cell lung cancer (NSCLC) on integrated positron emission tomography and computed tomography (PET-CT). METHODS: This was a retrospective, single-institution review of 122 patients with pathologically proven NSCLC who had PET-CT scanning at the same center. Lymph node metastases were pathologically confirmed in tissue specimens from surgical patients. Statistical evaluation of PET-CT results was performed on a per-nodal-station basis. RESULTS: The tumor SUVmax of squamous cell carcinoma (SCC) (11.0 ± 4.1) was higher than that of adenocarcinoma (AC) (7.4 ± 4.4) (P < 0.01), however, the SUVmax of the metastatic lymph nodes did not differ between the SCC (4.6 ± 3.1) and AC groups(3.6 ± 2.5) (P = 0.221). The SUVmax of metastatic lymph nodes was positively correlated with lymph node size but not with the primary tumor SUVmax, primary tumor size, tumor location and tumor differentiation. The frequency of a SUVmax of lymph nodes ≥2.5 was 44%, 80%,100% in SCC group and 39%, 59%, 90% in AC group when the short-axis diameter of metastatic lymph node was <10 mm, 10-15 mm, and > 15 mm, respectively. The low sensitivity for metastatic lymph nodes on PET-CT was increased when the SUVmax cut-off for malignancy was considered to be above the normal background compared with that when the SUVmax cut-off was above 2.5. CONCLUSIONS: There was no difference in the SUVmax of metastatic lymph nodes in the SCC and AC groups. The SUVmax of metastatic lymph nodes was positively correlated with metastatic lymph node size. There was a high false negative rate if lymph nodes with a short-axis diameter less than 10 mm and a extremely low false negative rate if lymph nodes with a short-axis diameter higher than 15 mm. Although an increased sensitivity may be achieved by decreasing the SUVmax cut-off, invasive staging may still be required for negative lymph nodes due to the lower sensitivity of PET-CT in both SCC and AC.

(18)F-Fluorodeoxyglucose positron emission tomography/computed tomography in patients with Kikuchi-Fujimoto disease: a nine-case series in China.

This study observed the image characteristics and clinico-imaging relationships of (18)F-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) in the patients with Kikuchi-Fujimoto disease (KFD). Nine consecutive patients with histologically proven KFD who underwent (18)F-FDG PET/CT were recruited. The (18)F-FDG uptakes of bone marrow (BM), spleen and lymph nodes (LNs) were systematically evaluated and maximum standardized uptake values (SUVmax) were measured. The number, locations and size factors of LNs were also assessed. The correlations were calculated between (18)F-FDG uptake and laboratory data and size factors of LNs, and the findings of LNs were compared between subgroups with different clinical features. (18)F-FDG uptakes were positive in the BM (SUVmax, 3.2 ± 1.2), spleen (SUVmax, 2.8 ± 0.7) and 122 affected LNs (SUVmax, 4.2 ± 2.2) for all patients. The affected LNs presented a systemically (region, 4 ± 1), multiple (number, 14 ± 5) and small-sized (long axis diameter, 11.4 ± 2.7 mm; short axis diameter, 8.0 ± 2.1 mm; area, 81.1 ± 44.6 mm(2)) pattern. The SUVmax of BM correlated to neutrophil count, and the SUVmax of affected LNs correlated to size factors and was lower in patients with long imaging interval and positive anti-nuclear antibody (ANA) (P < 0.05). We conclude that (18)F-FDG PET/CT can be characterized by the generalized distribution of relatively small-sized LNs and involvement of BM and spleen with high (18)F-FDG avidity in patients with KFD. The imaging interval, neutrophil count and ANA level should be synthetically considered during imaging evaluation.

Elevated uptake of 18F-FDG in PET/CT imaging of a nocardial pleural nodule.

18-Fluoredeoxyglucose position emission tomography and computed tomography ((18)F-FDG PET/CT) scanning has been widely used in the assessment of malignancy. We report here an increased (18)F-FDG uptake in pleural nodules in the PET/CT scan images of a patient having recurrent fever and chest pain. Further studies with bacterial culture and histopathology of biopsy confirmed the lesions as nocardial infection. To our knowledge, it is the first report of PET /CT findings in pleural multiple irregular nodules with nocardial infection. Our study suggests that a combination of FDG-PET/CT scanning and pathological study may be considered in distinguishing uncommon benign lesions in the lung.