ACR Appropriateness Criteria Non-invasive Clinical Staging of Bronchogenic Carcinoma

[18F]F-FAPI-42 PET dynamic imaging characteristics and multiparametric quantification of lung cancer: an exploratory study using uEXPLORER PET/CT

PURPOSE

To explore the dynamic and parametric characteristics of [18F]F-FAPI-42 PET/CT in lung cancers.

METHODS

Nineteen participants with newly diagnosed lung cancer underwent 60-min dynamic [18F]F-FAPI-42 PET/CT. Time-activity curves (TAC) were generated for tumors and normal organs, with kinetic parameters (K1, K2, K3, K4, Ki) calculated. A new parameter, the K ratio (K1 + K3)/(K2 + K4), was introduced to measure net uptake efficiency.

RESULTS

In primary tumor (PT), [18F]F-FAPI-42 uptake showed a gradual increase followed by a plateau, contrasting with organs like the thyroid and pancreas, which showed rapid uptake and continuous washout. Compared to non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) lesions reached the plateau earlier (11 min vs. 14 min) but had a lower uptake. During the plateau phase, [18F]F-FAPI-42 demonstrated slight washout in SCLC, whereas its uptake increased slightly in NSCLC. Lymph node and distant metastases exhibited similar TAC profiles to primary tumors. Kinetic modeling revealed that an irreversible two-compartment model (irre-2TCM) best represented the pharmacokinetics of [18F]F-FAPI-42 in lung cancer, whereas re-2TCM was better suited for the pancreas and thyroid. Lower K1, K2, K3 and K4 were observed in PT compared to those in the pancreas and thyroid (P < 0.05), however, the K ratio in PT was found to be 2-3 times higher. SCLC had lower Ki and SUVmean than NSCLC (P < 0.05). Kinetic parameter differences were also observed between PT and metastatic lesions. Larger metastatic lymph nodes exhibited higher K1, Ki, and K ratio than smaller ones.

CONCLUSION

Lung cancers exhibit distinct [18F]F-FAPI-42 dynamic and kinetic characteristics compared to the thyroid gland and pancreas. Differences were also observed between SCLC and NSCLC, primary and metastatic lesions, as well as larger versus smaller lesions. These findings provide valuable insights into the in vivo pharmacokinetics of [18F]F-FAPI-42, potentially improving the diagnosis of lung cancer.

TRIAL REGISTRATION

ChiCTR2100045757. Registered April 24, 2021 retrospectively registered, http//www.chictr.org.cn.

Utility of FDG PET-CT in CT Stage IA non-small cell lung cancer: The New Zealand Te Whatu Ora Northern region experience

INTRODUCTION

Our objective was to investigate the utility of fluorodeoxyglucose positron emission tomography-computed tomography (FDG PET-CT) in assessing CT Stage 1A non-small cell lung cancer (NSCLC) in patients under consideration for curative treatment. Performing FDG PET-CT in these patients may lead to unnecessary delays in treatment if it can be shown to provide no added value.

METHODS

We retrospectively reviewed 735 lesions in 653 patients from the New Zealand Te Whatu Ora Northern region lung cancer database with suspected or pathologically proven Stage 1A NSCLC on CT scan who also underwent FDG PET-CT imaging. We determined how often FDG PET-CT findings upstaged patients and then compared to pathological staging where available.

RESULTS

FDG PET-CT provided an overall upstaging rate of 9.7%. Category-specific rates were 0% in Tis, 0.9% in T1mi, 7.4% in T1a, 10% in T1b and 12% in T1c groups. The percentage of lesions upstaged on FDG PET-CT that remained Stage 1A was 100% in T1mi, 100% in T1a, 47.1% in T1b and 40.7% in T1c groups. The P value was statistically significant at 0.004, indicating upstaging beyond Stage 1A was dependent on T category.

CONCLUSION

Our data suggests that FDG PET-CT is indicated for T1b and T1c lesions but is of limited utility in Tis, T1mi and T1a lesions. Adopting a more targeted approach and omitting FDG PET-CT in patients with Tis, T1mi, and T1a lesions may benefit all patients with lung cancer by improving accessibility and treatment timelines.

Lung CT stabilization with high-frequency non-invasive ventilation (HF-NIV) and breath-hold (BH) in lung nodule assessment by PET/CT

PURPOSE

To evaluate the effect of lung stabilization using high-frequency non-invasive ventilation (HF-NIV) and breath-hold (BH) techniques on lung nodule detection and texture assessment in PET/CT compared to a free-breathing (FB) standard lung CT acquisition in PET/CT.

MATERIALS AND METHODS

Six patients aged 65 ± 7 years, addressed for initial assessment of at least one suspicious lung nodule with 18F-FDG PET/CT, underwent three consecutive lung PET/CT acquisitions with FB, HF-NIV and BH. Lung nodules were assessed on all three CT acquisitions of the PET/CT and characterized for any size, volume and solid/sub-solid nature.

RESULTS

BH detected a significantly higher number of nodules (n = 422) compared to HF-NIV (n = 368) and FB (n = 191) (p < 0.001). The mean nodule size (mm) was 2.4 ± 2.1, 2.6 ± 1.9 and 3.2 ± 2.4 in BH, HF-NIV and FB, respectively, for long axis and 1.5 ± 1.3, 1.6 ± 1.2 and 2.1 ± 1.7 in BH, HF-NIV and FB, respectively, for short axis. Long- and short-axis diameters were significantly different between BH and FB (p < 0.001) and between HF-NIV and FB (p < 0.001 and p = 0.008), but not between BH and HF-NIV. A trend for higher volume was shown in FB compared to BH (p = 0.055) and HF-NIV (p = 0.068) without significant difference between BH and HF-NIV (p = 1). We found a significant difference in detectability of sub-solid nodules between the three acquisitions, with BH showing a higher number of sub-solid nodules (n = 128) compared to HF-NIV (n = 72) and FB (n = 44) (p = 0.002).

CONCLUSION

We observed a higher detection rate of pulmonary nodules on CT under BH or HF-NIV conditions applied to PET/CT than with FB. BH and HF-NIV demonstrated comparable texture assessment and performed better than FB in assessing size and volume. BH showed a better performance for detecting sub-solid nodules compared to HF-NIV and FB. The addition of BH or HF-NIV to PET/CT can help improve the detection and texture characterization of lung nodules by CT, therefore improving the accuracy of oncological lung disease assessment. The ease of use of BH and its added value should prompt its use in routine practice.

Automatic Lung Cancer Segmentation in [18F]FDG PET/CT Using a Two-Stage Deep Learning Approach

Purpose

Since accurate lung cancer segmentation is required to determine the functional volume of a tumor in [18F]FDG PET/CT, we propose a two-stage U-Net architecture to enhance the performance of lung cancer segmentation using [18F]FDG PET/CT.

Methods

The whole-body [18F]FDG PET/CT scan data of 887 patients with lung cancer were retrospectively used for network training and evaluation. The ground-truth tumor volume of interest was drawn using the LifeX software. The dataset was randomly partitioned into training, validation, and test sets. Among the 887 PET/CT and VOI datasets, 730 were used to train the proposed models, 81 were used as the validation set, and the remaining 76 were used to evaluate the model. In Stage 1, the global U-net receives 3D PET/CT volume as input and extracts the preliminary tumor area, generating a 3D binary volume as output. In Stage 2, the regional U-net receives eight consecutive PET/CT slices around the slice selected by the Global U-net in Stage 1 and generates a 2D binary image as the output.

Results

The proposed two-stage U-Net architecture outperformed the conventional one-stage 3D U-Net in primary lung cancer segmentation. The two-stage U-Net model successfully predicted the detailed margin of the tumors, which was determined by manually drawing spherical VOIs and applying an adaptive threshold. Quantitative analysis using the Dice similarity coefficient confirmed the advantages of the two-stage U-Net.

Conclusion

The proposed method will be useful for reducing the time and effort required for accurate lung cancer segmentation in [18F]FDG PET/CT.

Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis

Artificial Intelligence (AI) is a branch of computer science that includes research in robotics, language recognition, image recognition, natural language processing, and expert systems. AI is poised to change medical practice, and oncology is not an exception to this trend. As the matter of fact, lung cancer has the highest morbidity and mortality worldwide. The leading cause is the complexity of associating early pulmonary nodules with neoplastic changes and numerous factors leading to strenuous treatment choice and poor prognosis. AI can effectively enhance the diagnostic efficiency of lung cancer while providing optimal treatment and evaluating prognosis, thereby reducing mortality. This review seeks to provide an overview of AI relevant to all the fields of lung cancer. We define the core concepts of AI and cover the basics of the functioning of natural language processing, image recognition, human-computer interaction and machine learning. We also discuss the most recent breakthroughs in AI technologies and their clinical application regarding diagnosis, treatment, and prognosis in lung cancer. Finally, we highlight the future challenges of AI in lung cancer and its impact on medical practice.

A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease management

Radiomics analysis quantifies the interpolation of multiple and invisible molecular features present in diagnostic and therapeutic images. Implementation of 18-fluorine-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) radiomics captures various disorders in non-invasive and high-throughput manner. ¹⁸F-FDG PET/CT accurately identifies the metabolic and anatomical changes during cancer progression. Therefore, the application of ¹⁸F-FDG PET/CT in the field of oncology is well established. Clinical application of ¹⁸F-FDG PET/CT radiomics in lung infection and inflammation is also an emerging field. Combination of bioinformatics approaches or textual analysis allows radiomics to extract additional information to predict cell biology at the micro-level. However, radiomics texture analysis is affected by several factors associated with image acquisition and processing. At present, researchers are working on mitigating these interrupters and developing standardised workflow for texture biomarker establishment. This review article focuses on the application of ¹⁸F-FDG PET/CT in detecting lung diseases specifically on cancer, infection and inflammation. An overview of different approaches and challenges encountered on standardisation of ¹⁸F-FDG PET/CT technique has also been highlighted. The review article provides insights about radiomics standardisation and application of ¹⁸F-FDG PET/CT in lung disease management.

Thoracic positron emission tomography: 18F-fluorodeoxyglucose and beyond

Ongoing technologic and therapeutic advancements in medicine are now testing the limits of conventional anatomic imaging techniques. The ability to image physiology, rather than simply anatomy, is critical in the management of multiple disease processes, especially in oncology. Nuclear medicine has assumed a leading role in detecting, diagnosing, staging and assessing treatment response of various pathologic entities, and appears well positioned to do so into the future. When combined with computed tomography (CT) or magnetic resonance imaging (MRI), positron emission tomography (PET) has become the sine quo non technique of evaluating most solid tumors especially in the thorax. PET/CT serves as a key imaging modality in the initial evaluation of pulmonary nodules, often obviating the need for more invasive testing. PET/CT is essential to staging and restaging in bronchogenic carcinoma and offers key physiologic information with regard to treatment response. A more recent development, PET/MRI, shows promise in several specific lung cancer applications as well. Additional recent advancements in the field have allowed PET to expand beyond imaging with ¹⁸F-flurodeoxyglucose (FDG) alone, now with the ability to specifically image certain types of cell surface receptors. In the thorax this predominantly includes ⁶⁸Ga-DOTATATE which targets the somatostatin receptors abundantly expressed in neuroendocrine tumors, including bronchial carcinoid. This receptor targeted imaging technique permits targeting these tumors with therapeutic analogues such as ¹⁷⁷Lu labeled DOTATATE. Overall, the proper utilization of PET in the thorax has the ability to directly impact and improve patient care.

Recent and Current Advances in FDG-PET Imaging within the Field of Clinical Oncology in NSCLC: A Review of the Literature

Lung cancer is the leading cause of cancer-related deaths around the world, the most common type of which is non-small-cell lung cancer (NSCLC). Computed tomography (CT) is required for patients with NSCLC, but often involves diagnostic issues and large intra- and interobserver variability. The anatomic data obtained using CT can be supplemented by the metabolic data obtained using fluorodeoxyglucose F 18 (FDG) positron emission tomography (PET); therefore, the use of FDG-PET/CT for staging NSCLC is recommended, as it provides more accuracy than either modality alone. Furthermore, FDG-PET/magnetic resonance imaging (MRI) provides useful information on metabolic activity and tumor cellularity, and has become increasingly popular. A number of studies have described FDG-PET/MRI as having a high diagnostic performance in NSCLC staging. Therefore, multidimensional functional imaging using FDG-PET/MRI is promising for evaluating the activity of the intratumoral environment. Radiomics is the quantitative extraction of imaging features from medical scans. The chief advantages of FDG-PET/CT radiomics are the ability to capture information beyond the capabilities of the human eye, non-invasiveness, the (virtually) real-time response, and full-field analysis of the lesion. This review summarizes the recent advances in FDG-PET imaging within the field of clinical oncology in NSCLC, with a focus on surgery and prognostication, and investigates the site-specific strengths and limitations of FDG-PET/CT. Overall, the goal of treatment for NSCLC is to provide the best opportunity for long-term survival; therefore, FDG-PET/CT is expected to play an increasingly important role in deciding the appropriate treatment for such patients.

Utility of FDG PET/CT for Preoperative Staging of Non-Small Cell Lung Cancers Manifesting as Subsolid Nodules With a Solid Portion of 3 cm or Smaller

OBJECTIVE. The objective of our study was to investigate the utility of FDG PET/CT for the preoperative staging of subsolid non-small cell lung cancers (NSCLCs) with a solid portion size of 3 cm or smaller. MATERIALS AND METHODS. We retrospectively enrolled 855 patients with pathologically proven NSCLCs manifesting as subsolid nodules with a solid portion of 3 cm or smaller on CT. We then compared the diagnostic performances of FDG PET/CT and chest CT for detecting lymph node (LN), intrathoracic, or distant metastases in patients who underwent preoperative chest CT and FDG PET/CT. After propensity score matching, we compared the diagnostic performance of FDG PET/CT in the group who underwent both chest CT and FDG PET/CT with that of chest CT in patients who did not undergo FDG PET/CT. RESULTS. There were LN metastases in 25 of 765 patients (3.3%) who underwent surgical LN dissection or biopsy and intrathoracic or distant metastasis in two of 855 patients (0.2%). For LN staging, FDG PET/CT showed a sensitivity of 44.0%, specificity of 81.5%, positive predictive value of 9.6%, negative predictive value of 97.0%, and accuracy of 79.9%, which were lower than those of chest CT for accuracy (p < 0.0001). FDG PET/CT could not accurately detect any intrathoracic or distant metastasis. After propensity score matching, the diagnostic accuracy for LN staging of FDG PET/CT in the group who underwent both CT and FDG PET/CT was lower than that of chest CT in the group who did not undergo FDG PET/CT (p = 0.002), and the diagnostic accuracy for intrathoracic and distant metastases was not different (p > 0.999). CONCLUSION. FDG PET/CT has limited utility in preoperatively detecting LN or distant metastasis in patients with subsolid NSCLCs with a solid portion size of 3 cm or smaller.

Role of FDG PET/CT in the Eighth Edition of TNM Staging of Non-Small Cell Lung Cancer

Lung cancer is the leading cause of cancer-related mortality in the United States, and accurate staging plays a vital role in determining prognosis and treatment. The recently revised eighth edition of the TNM staging system for lung cancer defines new T and M descriptors and updates stage groupings on the basis of substantial differences in survival. There are new T descriptors that are based on the findings at histopathologic examination, and T descriptors are reassigned on the basis of tumor size and extent. No changes were made to the N descriptors in the eighth edition of the TNM staging of lung cancer, because the four N categories that are based on the location of the diseased nodes can be used to consistently predict prognosis. The eighth edition includes a new M1b descriptor for patients with a single extrathoracic metastatic lesion in a single organ (M1b), because they have better survival and different treatment options, compared with those with multiple extrathoracic lesions (M1c). Examination with fluorine 18 fluorodeoxyglucose (FDG) PET/CT is the standard of care and is an integral part of the clinical staging of patients with lung cancer. To provide the treating physicians with accurate staging information, radiologists and nuclear medicine physicians should be aware of the updated classification system and should be cognizant of the site-specific strengths and limitations of FDG PET/CT. In this article, the eighth edition of the TNM staging system is reviewed, as well as the role of FDG PET/CT in the staging of non-small cell lung carcinoma. ^©RSNA, 2018.

Imaging for the Pretreatment Staging of Small cell Lung Cancer: A Systematic Review

BACKGROUND

Small cell lung cancer (SCLC) is an aggressive form of lung cancer. Accurate staging is essential to select the optimal treatment plan to maximize survival. No consensus exists on standard imaging modalities for pretreatment staging of SCLC.

MATERIALS AND METHODS

We conducted a systematic review of the literature on imaging modalities in the pretreatment staging of SCLC. A systematic search of multiple databases identified relevant studies published from 2000 through June 2015. Outcomes of interest included test concordance, staging accuracy (sensitivity and specificity), choice of treatment, timeliness of treatment, and patient outcomes.

RESULTS

The search identified 2880 citations; 7 studies met inclusion criteria, n = 408 patients. Six of the seven studies were deemed to have moderate risk of bias, and one was deemed to have high risk of bias. One of the studies reported test concordance, three studies reported comparative accuracy of testing strategies, and four studies reported the accuracy of a single imaging modality. Analysis from these studies revealed that fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) is more sensitive than multidetector CT for detecting osseous metastases, more sensitive than bone scintigraphy for detecting osseous metastases, and more sensitive for detecting any distant metastases.

CONCLUSIONS

Evidence is sparse on the use of imaging in the pretreatment staging of SCLC. There is a lack of evidence on patient-oriented outcomes and a lack of evidence on whether comparative accuracy or effectiveness is associated with patient factors. We found low-strength evidence suggesting that FDG-PET/CT is more sensitive than CT and bone scintigraphy for detecting osseous metastases.