Dual-time-point positron emission tomography findings of benign mediastinal fluorine-18-fluorodeoxyglucose uptake in tuberculosis-endemic region

FDG-PET-CT as an early detection method for tuberculosis: a systematic review and meta-analysis

Tuberculosis (TB) causes major public health problems worldwide. Fighting TB requires sustained efforts in health prevention, diagnosis and treatment. Previous literature has shown that conventional diagnostic methods like X-ray and sputum microscopy often miss early or extrapulmonary TB due to their limited sensitivity. Blood tests, while useful, lack the anatomical detail needed for precise localization of TB lesions. A possible step forward in the fight against TB could be the use of Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and Computed Tomography (CT). This meta-analysis discusses the current literature, including the methods, results and implications of using FDG-PET-CT in the early diagnosis of TB. Analysis of the studies showed that the sensitivity of FDG-PET-CT as a potential method for early detection of TB was 82.6%.

Using neighborhood gray tone difference matrix texture features on dual time point PET/CT images to differentiate malignant from benign FDG-avid solitary pulmonary nodules

OBJECTIVE

Lung cancer usually presents as a solitary pulmonary nodule (SPN) on diagnostic imaging during the early stages of the disease. Since the early diagnosis of lung cancer is very important for treatment, the accurate diagnosis of SPNs has much importance. The aim of this study was to evaluate the discriminant power of dual time point imaging (DTPI) PET/CT in the differentiation of malignant and benign FDG-avid solitary pulmonary nodules by using neighborhood gray-tone difference matrix (NGTDM) texture features.

METHODS

Retrospective analysis was carried out on 116 patients with SPNs (35 benign and 81 malignant) who had DTPI ¹⁸F-FDG PET/CT between January 2005 and May 2015. Both PET and CT images were acquired at 1 h and 3 h after injection. The SUV_max and NGTDM texture features (coarseness, contrast, and busyness) of each nodule were calculated on dual time point images. Patients were randomly divided into training and validation datasets. Receiver operating characteristic (ROC) curve analysis was performed on all texture features in the training dataset to calculate the optimal threshold for differentiating malignant SPNs from benign SPNs. For all the lesions in the testing dataset, two visual interpretation scores were determined by two nuclear medicine physicians based on the PET/CT images with and without reference to the texture features.

RESULTS

In the training dataset, the AUCs of delayed busyness, delayed coarseness, early busyness, and early SUV_max were 0.87, 0.85, 0.75 and 0.75, respectively. In the validation dataset, the AUCs of visual interpretations with and without texture features were 0.89 and 0.80, respectively.

CONCLUSION

Compared to SUV_max or visual interpretation, NGTDM texture features derived from DTPI PET/CT images can be used as good predictors of SPN malignancy. Improvement in discriminating benign from malignant nodules using SUVmax and visual interpretation can be achieved by adding busyness extracted from delayed PET/CT images.

Diagnostic classification of solitary pulmonary nodules using dual time 18F-FDG PET/CT image texture features in granuloma-endemic regions

Lung cancer, the most commonly diagnosed cancer worldwide, usually presents as solid pulmonary nodules (SPNs) on early diagnostic images. Classification of malignant disease at this early timepoint is critical for improving the success of surgical resection and increasing 5-year survival rates. ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/CT has demonstrated value for SPNs diagnosis with high sensitivity to detect malignant SPNs, but lower specificity in diagnosing malignant SPNs in populations with endemic infectious lung disease. This study aimed to determine whether quantitative heterogeneity derived from various texture features on dual time FDG PET/CT images (DTPI) can differentiate between malignant and benign SPNs in patients from granuloma-endemic regions. Machine learning methods were employed to find optimal discrimination between malignant and benign nodules. Machine learning models trained by texture features on DTPI images achieved significant improvements over standard clinical metrics and visual interpretation for discriminating benign from malignant SPNs, especially by texture features on delayed FDG PET/CT images.

PET/CT imaging of Mycobacterium tuberculosis infection

Tuberculosis has a high morbidity and mortality worldwide. Mycobacterium tuberculosis (Mtb) has a complex pathophysiology; it is an aerobic bacillus capable of surviving in anaerobic conditions in a latent state for a very long time before reactivation to active disease. In the latent tuberculosis infection, the individual has no clinical evidence of active disease, but exhibits a hypersensitive response to proteins of Mtb. Only some 5–10 % of latently infected individuals appear to have reactivation of tuberculosis at any one time point after infection, and neither imaging nor immune tests have been shown to predict tuberculosis reactivation reliably. The complex pathology of the organism provides multiple molecular targets for imaging the infection and targeting therapy. Positron emission tomography (PET) integrated with computer tomography (CT) provides a unique opportunity to noninvasively image the whole body for diagnosing, staging and assessing therapy response in many infectious and inflammatory diseases. PET/CT is a powerful noninvasive tool that can rapidly provide three-dimensional views of disease deep within the body and conduct longitudinal assessment over time in one particular patient. Some PET tracers, such as ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG), have been found to be useful in various infectious diseases for detection, assessing disease activity, staging and monitoring response to therapy. This tracer has also been used for imaging tuberculosis. ¹⁸F-FDG PET relies on the glucose uptake of inflammatory cells as a result of the respiratory burst that occurs with infection. Other PET tracers have also been used to image different aspects of the pathology or microbiology of Mtb. The synthesis of the complex cell membrane of the bacilli for example can be imaged with ¹¹C-choline or ¹⁸F-fluoroethylcholine PET/CT while the uptake of amino acids during cell growth can be imaged by 3′-deoxy-3′-[¹⁸F]fluoro-l-thymidine. PET/CT provides a noninvasive and sensitive method of assessing histopathological information on different aspects of tuberculosis and is already playing a role in the management of tuberculosis. As our understanding of the pathophysiology of tuberculosis increases, the role of PET/CT in the management of this disease would become more important. In this review, we highlight the various tracers that have been used in tuberculosis and explain the underlying mechanisms for their use.