The effect of a novel Bayesian penalised likelihood PET reconstruction algorithm on the assessment of malignancy risk in solitary pulmonary nodules according to the British Thoracic Society guidelines

Imaging Follow-Up of Nonsurgical Therapies for Lung Cancer: AJR Expert Panel Narrative Review

Lung cancer continues to be the most common cause of cancer-related death worldwide. In the past decade, with the implementation of lung cancer screening programs and advances in surgical and nonsurgical therapies, the survival of patients with lung cancer has increased, as has the number of imaging studies that these patients undergo. However, most patients with lung cancer do not undergo surgical re-section, because they have comorbid disease or lung cancer in an advanced stage at diagnosis. Nonsurgical therapies have continued to evolve with a growing range of systemic and targeted therapies, and there has been an associated evolution in the imaging findings encountered at follow-up examinations after such therapies (e.g., with respect to posttreatment changes, treatment complications, and recurrent tumor). This AJR Expert Panel Narrative Review describes the current status of nonsurgical therapies for lung cancer and their expected and unexpected imaging manifestations. The goal is to provide guidance to radiologists regarding imaging assessment after such therapies, focusing mainly on non-small cell lung cancer. Covered therapies include systemic therapy (conventional chemotherapy, targeted therapy, and immunotherapy), radiotherapy, and thermal ablation.

The frequency of change in five-point scale score with a Bayesian penalised likelihood PET reconstruction algorithm on interim FDG PET-CT and its potential implications for therapy decisions in Hodgkin's lymphoma

AIM

To assess the effect of a Bayesian penalised likelihood (BPL) reconstruction algorithm on the five-point scale (5-PS) score, response categorisation, and potential implications for therapy decisions after interim 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)-computed tomography (CT) (iPET-CT) to guide treatment in classical Hodgkin's lymphoma (HL).

MATERIALS AND METHODS

The present study included new patients with HL undergoing iPET-CT from 2014-2019 after two cycles of doxorubicin (Adriamycin), bleomycin, vincristine, and dacarbazine (ABVD). Two reporters categorised response using the 5-PS and measured maximum standardised uptake values (SUV_max) of the most avid tumour residuum, mediastinal blood pool, and normal liver with ordered subset expected maximisation (OSEM) and BPL reconstructions.

RESULTS

Eighty-one iPET-CT examinations were reviewed. Compared with OSEM, BPL increased the 5-PS score by a single score in 18/81 (22.2%) patients. The frequency of potential treatment intensification by changing a score of 3-4 was 13.6% (11/81) and represented 25% (11/44) of patients with a score of 3 on OSEM. All 11 patients remained in remission without a change in therapy (mean 63 months) except one who required second-line treatment for refractory disease. Median SUV_max of tumour residuum was significantly higher with BPL compared with OSEM (2.7 versus 2.4, p<<0.0001), whilst liver SUV_max was significantly lower for both reporters (up to 6.6%, p<0.0001).

CONCLUSION

BPL PET reconstruction increased the 5-PS score on iPET-CT in 22% of HL patients and can potentially result in unnecessary treatment escalation in over half of these patients.

EarlyCDT Lung blood test for risk classification of solid pulmonary nodules: systematic review and economic evaluation

BACKGROUND

EarlyCDT Lung (Oncimmune Holdings plc, Nottingham, UK) is a blood test to assess malignancy risk in people with solid pulmonary nodules. It measures the presence of seven lung cancer-associated autoantibodies. Elevated levels of these autoantibodies may indicate malignant disease. The results of the test might be used to modify the risk of malignancy estimated by existing risk calculators, including the Brock and Herder models.

OBJECTIVES

The objectives were to determine the diagnostic accuracy, clinical effectiveness and cost-effectiveness of EarlyCDT Lung; and to develop a conceptual model and identify evidence requirements for a robust cost-effectiveness analysis.

DATA SOURCES

MEDLINE (including Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE), EMBASE, Cochrane Central Register of Controlled Trials, Science Citation Index, EconLit, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment database, NHS Economic Evaluation Database ( NHS EED ) and the international Health Technology Assessment database were searched on 8 March 2021.

REVIEW METHODS

A systematic review was performed of evidence on EarlyCDT Lung, including diagnostic accuracy, clinical effectiveness and cost-effectiveness. Study quality was assessed with the quality assessment of diagnostic accuracy studies-2 tool. Evidence on other components of the pulmonary nodule diagnostic pathway (computerised tomography surveillance, Brock risk, Herder risk, positron emission tomography-computerised tomography and biopsy) was also reviewed. When feasible, bivariate meta-analyses of diagnostic accuracy were performed. Clinical outcomes were synthesised narratively. A simulation study investigated the clinical impact of using EarlyCDT Lung. Additional reviews of cost-effectiveness studies evaluated (1) other diagnostic strategies for lung cancer and (2) screening approaches for lung cancer. A conceptual model was developed.

RESULTS

A total of 47 clinical publications on EarlyCDT Lung were identified, but only five cohorts (695 patients) reported diagnostic accuracy data on patients with pulmonary nodules. All cohorts were small or at high risk of bias. EarlyCDT Lung on its own was found to have poor diagnostic accuracy, with a summary sensitivity of 20.2% (95% confidence interval 10.5% to 35.5%) and specificity of 92.2% (95% confidence interval 86.2% to 95.8%). This sensitivity was substantially lower than that estimated by the manufacturer (41.3%). No evidence on the clinical impact of EarlyCDT Lung was identified. The simulation study suggested that EarlyCDT Lung might potentially have some benefit when considering intermediate risk nodules (10-70% risk) after Herder risk analysis. Two cost-effectiveness studies on EarlyCDT Lung for pulmonary nodules were identified; none was considered suitable to inform the current decision problem. The conceptualisation process identified three core components for a future cost-effectiveness assessment of EarlyCDT Lung: (1) the features of the subpopulations and relevant heterogeneity, (2) the way EarlyCDT Lung test results affect subsequent clinical management decisions and (3) how changes in these decisions can affect outcomes. All reviewed studies linked earlier diagnosis to stage progression and stage shift to final outcomes, but evidence on these components was sparse.

LIMITATIONS

The evidence on EarlyCDT Lung among patients with pulmonary nodules was very limited, preventing meta-analyses and economic analyses.

CONCLUSIONS

The evidence on EarlyCDT Lung among patients with pulmonary nodules is insufficient to draw any firm conclusions as to its diagnostic accuracy or clinical or economic value.

FUTURE WORK

Prospective cohort studies, in which EarlyCDT Lung is used among patients with identified pulmonary nodules, are required to support a future assessment of the clinical and economic value of this test. Studies should investigate the diagnostic accuracy and clinical impact of EarlyCDT Lung in combination with Brock and Herder risk assessments. A well-designed cost-effectiveness study is also required, integrating emerging relevant evidence with the recommendations in this report.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42021242248.

FUNDING

This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 49. See the NIHR Journals Library website for further project information.

A case-control evaluation of pulmonary and extrapulmonary findings of incidental asymptomatic COVID-19 infection on FDG PET-CT

OBJECTIVES

To describe the findings of incidental asymptomatic COVID-19 infection on FDG PET-CT using a case-control design.

METHODS

Incidental pulmonary findings suspicious of asymptomatic COVID-19 infection on FDG PET-CT were classified as a confirmed (positive RT-PCR test) or suspected case (no/negative RT-PCR test). Control cases were identified using a 4:1 control:case ratio. Pulmonary findings were re-categorised by two reporters using the BSTI classification. SUV metrics in ground glass opacification (GGO)/consolidation (where present), background lung, intrathoracic nodes, liver, spleen and bone marrow were measured.

RESULTS

7/9 confirmed and 11/15 suspected cases (COVID-19 group) were re-categorised as BSTI 1 (classic/probable COVID-19) or BSTI 2 (indeterminate COVID-19); 0/96 control cases were categorised as BSTI 1. Agreement between two reporters using the BSTI classification was almost perfect (weighted κ = 0.94). SUVmax GGO/consolidation (5.1 vs 2.2; p < 0.0001) and target-to-background ratio, normalised to liver SUVmean (2.4 vs 1.0; p < 0.0001) were higher in the BSTI 1 & 2 group vs BSTI 3 (non-COVID-19) cases. SUVmax GGO/consolidation discriminated between the BSTI 1 & 2 group vs BSTI 3 (non-COVID-19) cases with high accuracy (AUC = 0.93). SUV metrics were higher (p < 0.05) in the COVID-19 group vs control cases in the lungs, intrathoracic nodes and spleen.

CONCLUSION

Asymptomatic COVID-19 infection on FDG PET-CT is characterised by bilateral areas of FDG avid (intensity > x2 liver SUVmean) GGO/consolidation and can be identified with high interobserver agreement using the BSTI classification. There is generalised background inflammation within the lungs, intrathoracic nodes and spleen.

ADVANCES IN KNOWLEDGE

Incidental asymptomatic COVID-19 infection on FDG PET-CT, characterised by bilateral areas of ground glass opacification and consolidation, can be identified with high reproducibility using the BSTI classification. The intensity of associated FDG uptake (>x2 liver SUVmean) provides high discriminative ability in differentiating such cases from pulmonary findings in a non-COVID-19 pattern. Asymptomatic COVID-19 infection causes a generalised background inflammation within the mid-lower zones of the lungs, hilar and central mediastinal nodal stations, and spleen on FDG PET-CT.

Changes of [18F]FDG-PET/CT quantitative parameters in tumor lesions by the Bayesian penalized-likelihood PET reconstruction algorithm and its influencing factors

Background

To compare the changes in quantitative parameters and the size and degree of ¹⁸F-fluorodeoxyglucose ([¹⁸F]FDG) uptake of malignant tumor lesions between Bayesian penalized-likelihood (BPL) and non-BPL reconstruction algorithms.

Methods

Positron emission tomography/computed tomography images of 86 malignant tumor lesions were reconstructed using the algorithms of ordered subset expectation maximization (OSEM), OSEM + time of flight (TOF), OSEM + TOF + point spread function (PSF), and BPL. [¹⁸F]FDG parameters of maximum standardized uptake value (SUVmax), SUVmean, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and signal-to-background ratio (SBR) of these lesions were measured. Quantitative parameters between the different reconstruction algorithms were compared, and correlations between parameter variation and lesion size or the degree of [¹⁸F]FDG uptake were analyzed.

Results

After BPL reconstruction, SUVmax, SUVmean, and SBR were significantly increased, MTV was significantly decreased. The difference values of %ΔSUVmax, %ΔSUVmean, %ΔSBR, and the absolute value of %ΔMTV between BPL and OSEM + TOF were 40.00%, 38.50%, 33.60%, and 33.20%, respectively, which were significantly higher than those between BPL and OSEM + TOF + PSF. Similar results were observed in the comparison of OSEM and OSEM + TOF + PSF with BPL. The %ΔSUVmax, %ΔSUVmean, and %ΔSBR were all significantly negatively correlated with the size and degree of [¹⁸F]FDG uptake in the lesions, whereas significant positive correlations were observed for %ΔMTV and %ΔTLG.

Conclusion

The BPL reconstruction algorithm significantly increased SUVmax, SUVmean, and SBR and decreased MTV of tumor lesions, especially in small or relatively hypometabolic lesions.

Solitary pulmonary nodule imaging approaches and the role of optical fibre-based technologies

Solitary pulmonary nodules (SPNs) are a clinical challenge, given there is no single clinical sign or radiological feature that definitively identifies a benign from a malignant SPN. The early detection of lung cancer has a huge impact on survival outcome. Consequently, there is great interest in the prompt diagnosis, and treatment of malignant SPNs. Current diagnostic pathways involve endobronchial/transthoracic tissue biopsies or radiological surveillance, which can be associated with suboptimal diagnostic yield, healthcare costs and patient anxiety. Cutting-edge technologies are needed to disrupt and improve, existing care pathways. Optical fibre-based techniques, which can be delivered via the working channel of a bronchoscope or via transthoracic needle, may deliver advanced diagnostic capabilities in patients with SPNs. Optical endomicroscopy, an autofluorescence-based imaging technique, demonstrates abnormal alveolar structure in SPNs in vivo Alternative optical fingerprinting approaches, such as time-resolved fluorescence spectroscopy and fluorescence-lifetime imaging microscopy, have shown promise in discriminating lung cancer from surrounding healthy tissue. Whilst fibre-based Raman spectroscopy has enabled real-time characterisation of SPNs in vivo Fibre-based technologies have the potential to enable in situ characterisation and real-time microscopic imaging of SPNs, which could aid immediate treatment decisions in patients with SPNs. This review discusses advances in current imaging modalities for evaluating SPNs, including computed tomography (CT) and positron emission tomography-CT. It explores the emergence of optical fibre-based technologies, and discusses their potential role in patients with SPNs and suspected lung cancer.

Artificial Intelligence for the Characterization of Pulmonary Nodules, Lung Tumors and Mediastinal Nodes on PET/CT

Lung cancer is the leading cause of cancer related death around the world although early diagnosis remains vital to enabling access to curative treatment options. This article briefly describes the current role of imaging, in particular 2-deoxy-2-[¹⁸F]fluoro-D-glucose (FDG) PET/CT, in lung cancer and specifically the role of artificial intelligence with CT followed by a detailed review of the published studies applying artificial intelligence (ie, machine learning and deep learning), on FDG PET or combined PET/CT images with the purpose of early detection and diagnosis of pulmonary nodules, and characterization of lung tumors and mediastinal lymph nodes. A comprehensive search was performed on Pubmed, Embase, and clinical trial databases. The studies were analyzed with a modified version of the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) and Prediction model Risk Of Bias Assessment Tool (PROBAST) statement. The search resulted in 361 studies; of these 29 were included; all retrospective; none were clinical trials. Twenty-two records evaluated standard machine learning (ML) methods on imaging features (ie, support vector machine), and 7 studies evaluated new ML methods (ie, deep learning) applied directly on PET or PET/CT images. The studies mainly reported positive results regarding the use of ML methods for diagnosing pulmonary nodules, characterizing lung tumors and mediastinal lymph nodes. However, 22 of the 29 studies were lacking a relevant comparator and/or lacking independent testing of the model. Application of ML methods with feature and image input from PET/CT for diagnosing and characterizing lung cancer is a relatively young area of research with great promise. Nevertheless, current published studies are often under-powered and lacking a clinically relevant comparator and/or independent testing.

Multi-observer concordance and accuracy of the British Thoracic Society scale and other visual assessment qualitative criteria for solid pulmonary nodule assessment using FDG PET-CT

AIM

To compare the interobserver reliability and diagnostic accuracy of the British Thoracic Society (BTS) scale and other visual assessment criteria in the context of 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)-computed tomography (CT) evaluation of solid pulmonary nodules (SPNs).

MATERIALS AND METHODS

Fifty patients who underwent FDG PET-CT for assessment of a SPN were identified. Seven reporters with varied experience at four centres graded FDG uptake visually using the British Thoracic Society (BTS) four-point scale. Five reporters also scored SPNs according to three- and five-point visual assessment scales and using semi-quantitative assessment (maximum standardised uptake value [SUV_max]). Interobserver reliability was assessed with the intra-class correlation coefficient (ICC) and weighted Cohen's kappa (κ). Diagnostic performance was evaluated by receiver operator characteristic (ROC) analysis.

RESULTS

Good interobserver reliability was demonstrated with the BTS scale (ICC=0.78, 95% confidence interval [CI]: 0.69-0.85) and five-point scale (ICC=0.78, 95 CI 0.68-0.86), whilst the three-point scale demonstrated moderate reliability (ICC=0.70, 95% CI: 0.59-0.80). Almost perfect agreement was achieved between two consultants (κ=0.85), and substantial agreement between two other consultants (κ=0.78) using the BTS scale. ROC curves for the BTS and five-point scales demonstrated equivalent accuracy (BTS area under the ROC curve [AUC]=0.768; five-point AUC=0.768). SUV_max was no more accurate compared to the BTS scale (SUV_max AUC=0.794; BTS AUC=0.768, p=0.43).

CONCLUSIONS

The BTS scale can be applied reliably by reporters with varied levels of PET-CT reporting experience, across different centres and has a diagnostic performance that is not surpassed by alternative scales.