Indeterminate lung nodules in cancer patients: pretest probability of malignancy and the role of 18F-FDG PET/CT

Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept

[18F]Fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) are indispensable components in modern medicine. Although PET can provide additional diagnostic value, it is costly and not universally accessible, particularly in low-income countries. To bridge this gap, we have developed a conditional generative adversarial network pipeline that can produce FDG-PET from diagnostic CT scans based on multi-center multi-modal lung cancer datasets (n = 1,478). Synthetic PET images are validated across imaging, biological, and clinical aspects. Radiologists confirm comparable imaging quality and tumor contrast between synthetic and actual PET scans. Radiogenomics analysis further proves that the dysregulated cancer hallmark pathways of synthetic PET are consistent with actual PET. We also demonstrate the clinical values of synthetic PET in improving lung cancer diagnosis, staging, risk prediction, and prognosis. Taken together, this proof-of-concept study testifies to the feasibility of applying deep learning to obtain high-fidelity PET translated from CT.

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.

Current Evidence for Stereotactic Body Radiotherapy in Lung Metastases

Lung metastases are the second most common malignant neoplasms of the lung. It is estimated that 20–54% of cancer patients have lung metastases at some point during their disease course, and at least 50% of cancer-related deaths occur at this stage. Lung metastases are widely accepted to be oligometastatic when five lesions or less occur separately in up to three organs. Stereotactic body radiation therapy (SBRT) is a noninvasive, safe, and effective treatment for metastatic lung disease in carefully selected patients. There is no current consensus on the ideal dose and fractionation for SBRT in lung metastases, and it is the subject of study in ongoing clinical trials, which examines different locations in the lung (central and peripheral). This review discusses current indications, fractionations, challenges, and technical requirements for lung SBRT.

AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients

BACKGROUND

[¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) is a well-established modality in the work-up of patients with suspected or confirmed diagnosis of lung cancer. Recent research efforts have focused on extracting theragnostic and textural information from manually indicated lung lesions. Both semi-automatic and fully automatic use of artificial intelligence (AI) to localise and classify FDG-avid foci has been demonstrated. To fully harness AI's usefulness, we have developed a method which both automatically detects abnormal lung lesions and calculates the total lesion glycolysis (TLG) on FDG PET-CT.

METHODS

One hundred twelve patients (59 females and 53 males) who underwent FDG PET-CT due to suspected or for the management of known lung cancer were studied retrospectively. These patients were divided into a training group (59%; n = 66), a validation group (20.5%; n = 23) and a test group (20.5%; n = 23). A nuclear medicine physician manually segmented abnormal lung lesions with increased FDG-uptake in all PET-CT studies. The AI-based method was trained to segment the lesions based on the manual segmentations. TLG was then calculated from manual and AI-based measurements, respectively and analysed with Bland-Altman plots.

RESULTS

The AI-tool's performance in detecting lesions had a sensitivity of 90%. One small lesion was missed in two patients, respectively, where both had a larger lesion which was correctly detected. The positive and negative predictive values were 88% and 100%, respectively. The correlation between manual and AI TLG measurements was strong (R² = 0.74). Bias was 42 g and 95% limits of agreement ranged from - 736 to 819 g. Agreement was particularly high in smaller lesions.

CONCLUSIONS

The AI-based method is suitable for the detection of lung lesions and automatic calculation of TLG in small- to medium-sized tumours. In a clinical setting, it will have an added value due to its capability to sort out negative examinations resulting in prioritised and focused care on patients with potentially malignant lesions.

Texture analysis of iodine maps and conventional images for k-nearest neighbor classification of benign and metastatic lung nodules

BACKGROUND

The purpose of this study was to analyze if the use of texture analysis on spectral detector CT (SDCT)-derived iodine maps (IM) in addition to conventional images (CI) improves lung nodule differentiation, when being applied to a k-nearest neighbor (KNN) classifier.

METHODS

183 cancer patients who underwent contrast-enhanced, venous phase SDCT of the chest were included: 85 patients with 146 benign lung nodules (BLN) confirmed by either prior/follow-up CT or histopathology and 98 patients with 425 lung metastases (LM) verified by histopathology, 18F-FDG-PET-CT or unequivocal change during treatment. Semi-automatic 3D segmentation of BLN/LM was performed, and volumetric HU attenuation and iodine concentration were acquired. For conventional images and iodine maps, average, standard deviation, entropy, kurtosis, mean of the positive pixels (MPP), skewness, uniformity and uniformity of the positive pixels (UPP) within the volumes of interests were calculated. All acquired parameters were transferred to a KNN classifier.

RESULTS

Differentiation between BLN and LM was most accurate, when using all CI-derived features combined with the most significant IM-derived feature, entropy (Accuracy:0.87; F1/Dice:0.92). However, differentiation accuracy based on the 4 most powerful CI-derived features performed only slightly inferior (Accuracy:0.84; F1/Dice:0.89, p=0.125). Mono-parametric lung nodule differentiation based on either feature alone (i.e. attenuation or iodine concentration) was poor (AUC=0.65, 0.58, respectively).

CONCLUSIONS

First-order texture feature analysis of contrast-enhanced staging SDCT scans of the chest yield accurate differentiation between benign and metastatic lung nodules. In our study cohort, the most powerful iodine map-derived feature slightly, yet insignificantly increased classification accuracy  compared to classification based on conventional image features only.

Factors associated with subcentimeter pulmonary nodule outcomes followed with computed tomography imaging in oncology patients

•

PNs with irregular, lobuled or spiculated margins exhibited faster growth than PNs with regular, smooth margins.

•

Malignancy was significantly associated with male gender, a colorectal cancer diagnosis and advanced stage disease.

•

Oncologic patients should have an individualized CT follow-up strategy, as the rate of malignant pulmonary nodules is higher than in the general population.

Introduction

Technological advancements in computed tomography (CT) have enabled the frequent detection of small pulmonary nodules (PNs), especially in patients with an oncologic history. It is important the malignant versus benign etiology of PNs be determined. The aim of the present study was to evaluate the behavior and clinical/radiological characteristics of subcentimeter PNs detected by CT in oncologic patients.

Methods

An observational, longitudinal, retrospective and single-center study was conducted with a sample of 100 patients with a diagnosis of a primary malignant solid tumor outside of the lungs who developed indeterminate subcentimeter PNs (n = 251) detected on consecutive thoracic CT scans from 2015 to 2017. Follow-up CTs for each patients were examined in each of three periods (0–3 months, 3–6 months, and 6 months to 1 year).

Results

In our study sample, 28 patients (28 %) showed one or more signs suspicious of pulmonary metastasis, including ≥50 % PN growth, nodule growth followed by size reduction in patients undergoing chemotherapy, and the appearance of multiple nodules. The majority (56 %) of the PNs were detected during the 3–6-month follow-up CT scan. PNs with irregular, lobuled, or spiculated margins exhibited faster growth than PNs with regular, smooth margins. Malignancy of PNs was found to be significantly associated with being male, a primary colorectal cancer diagnosis, and advanced stage disease.

Conclusion

Our findings reinforce the necessity of an individualized CT follow-up strategy for patients with an oncologic history, as well as the importance of early nodule screening, with the inter-scan interval being dependent on the primary neoplasm.

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

PURPOSE

British Thoracic Society (BTS) guidelines advocate using FDG PET-CT with the Herder model to estimate malignancy risk in solitary pulmonary nodules (SPNs). Qualitative and semi-quantitative assessment of SPN uptake is based upon analysis of Ordered Subset Expected Maximisation (OSEM) PET images. Our aim was to assess the effect of a Bayesian Penalised Likelihood (BPL) PET reconstruction on the assessment of SPN FDG uptake and estimation of malignancy risk (Herder score).

METHODS

Subjects with SPNs who underwent FDG PET-CT between 2014-2017, with histological confirmation of malignancy or histological/imaging follow-up confirmation of benignity were included. Two blinded readers independently classified SPN uptake on both OSEM and BPL (BTS score; 1 = none; 2 = ≤ mediastinal blood pool (MBP); 3 = >MBP but ≤ 2x liver; 4 = >2x liver), with resultant calculation of the Herder score (%) for both reconstructions.

RESULTS

97 subjects with 75 (77%) malignant SPNs were included. BPL increased the BTS score in 25 (26%) SPNs; 9 SPNs (7 malignant) increased from BTS score 2 to 3, 16 (13 malignant) from BTS score 3 to 4, with a mean Herder score increase of 18 ± 22%. The mean Herder score for all SPNs with BPL was higher than OSEM (73 ± 29 vs 68 ± 32%, p = 0.001). There was no difference in Herder model diagnostic performance between BPL and OSEM, with similar areas under the curve (0.84 vs 0.83, p = 0.39).

CONCLUSION

BPL increases the Herder score in 26% of SPNs compared to OSEM but does not alter the diagnostic performance of the Herder model.

Is 18F-fluorodeoxyglucose positron emission tomography/computed tomography useful to discriminate metachronous lung cancer from metastasis in patients with oncological history?

BACKGROUND

Solitary pulmonary nodules detected during follow-up in patients with previous cancer history have a high probability of malignancy being either a metachronous lung cancer or a metastasis. This distinction represents a crucial issue in the perspective of "personalized medicine," implying different treatments and prognosis. Aim, to evaluate the role of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in distinguishing whether solitary pulmonary nodules are metachronous cancers or metastases and the relationship between the nodule's characteristics and their nature.

METHODS

From a single-institution database, we retrospectively selected all patients with a previous cancer history who performed 18F-FDG PET/CT to evaluate pulmonary nodules detected during follow-up, ranging from 5 mm to 40 mm, and histologically diagnosed as malignant.

RESULTS

Between September 2009 and August 2017, 127 patients (80 males; mean age=70.2±8.5years) with 127 malignant nodules were included: 103/127 (81%) metachronous cancers, 24/127 (19%) metastases. In both groups, PET/CT provided good and equivalent detection rate of malignancy (81% vs. 83%). No differences between metachronous cancers and metastases were found in: patient's age (70.3±8.1 years vs. 69.5±9.7years), gender (males=63.1% vs. 62.5%), interval between previous cancer diagnosis and nodules' detection (median time=4years vs. 4.5years), location (right-lung=55% vs. 54%; upper-lobes=64% vs. 67%; central-site=31% vs. 25%), size (median size=17mm vs. 19.5mm), 18F-FDG standardized uptake value (median SUVmax=5.2 vs. 5.9).

CONCLUSIONS

In oncological patients, despite its high detection rate, 18F-FDG PET/CT, as well as any other clinico-anatomical features, cannot distinguish whether a malignant solitary pulmonary nodule is a metachronous lung cancer or a metastasis, supporting the need of histological differential diagnosis.

The value of 18F-FDG-PET/CT in the diagnosis of solitary pulmonary nodules: A meta-analysis

BACKGROUND

Solitary pulmonary nodules (SPNs) are common imaging findings. Many studies have indicated that F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG-PET/CT) is an accurate test for distinguishing benign and malignant SPNs. The aim of this study was to investigate the value of F-FDG-PET/CT in the diagnosis of malignant SPNs.

METHODS

We systematically searched the PubMed and Embase databases up to March 2017, and published data on sensitivity, specificity, and other measures of diagnostic accuracy of F-FDG-PET/CT in the diagnosis of malignant SPNs were meta-analyzed. Statistical analyses were undertaken using Meta-DiSc 1.4 software and Stata version 12.0. The measures of accuracy of F-FDG-PET/CT in the diagnosis of malignant SPNs were pooled using random-effects models.

RESULTS

A total of 20 publications reporting 21 studies were identified. Pooled results indicated that F-FDG-PET/CT showed a diagnostic sensitivity of 0.89 (95% confidence interval [CI], 0.87-0.91) and a specificity of 0.70 (95% CI, 0.66-0.73). The positive likelihood ratio was 3.33 (95% CI, 2.35-4.71) and the negative likelihood ratio was 0.18 (95% CI, 0.13-0.25). The diagnostic odds ratio was 22.43 (95% CI, 12.55-40.07).

CONCLUSIONS

F-FDG-PET/CT showed insufficient sensitivity and specificity for diagnosing malignant SPNs; it cannot replace the "gold standard" pathology by resection or percutaneous biopsy. Larger studies are required for further evaluation.

Time to Progression of Pancreatic Cancer: Evaluation with Multi-Detector Computed Tomography

PURPOSE

The aim of this study is to evaluate the natural history of untreated pancreatic cancer, with a particular emphasis on the growth rate of primary tumor and development of metastatic disease.

METHODS

One hundred patients with histologically proven pancreatic ductal adenocarcinoma examined with at least two CT scans with no intervening treatment were included. Tumor diameters and volumes were measured in CT scans and tumor growth rates and volume doubling times (VDTs) were calculated. The relationship between initial tumor size, growth rate, and distant metastasis development were investigated.

RESULTS

Included tumors were 1.0-6.2 cm (mean, 2.9 ± 1.3 cm) in diameter and 5.5-1225.9 cm³ (mean, 120.6 ± 158.9 cm³) in volume at the initial CT. Tumor growth rates were -0.4 to 19.9 cm/year (mean, 4.2 ± 3.8 cm/year) in diameter, and 11.1-13,321.5 cm³/year (mean, 727.8 ± 1609.5 cm³/year) in volume corresponding to VDT of 20.0-976.8 days (mean, 132.3 ± 132.1 days). The growth rate was significantly associated with the initial diameter and volume (p < 0.001). The development of distant metastasis was significantly associated with initial diameter (p < 0.05), volume (p = 0.015), and volume growth rate (p = 0.002).

CONCLUSIONS

The growth rate and VDTs of untreated pancreatic cancers varied widely, from less than a month to more than 4 years, positively associated with tumor size. The small tumors tend to grow slowly and have low risk for developing metastasis.

Return of the pulmonary nodule: the radiologist's key role in implementing the 2015 BTS guidelines on the investigation and management of pulmonary nodules

The British Thoracic Society has published new comprehensive guidelines for the management of pulmonary nodules. These guidelines are significantly different from those previously published, as they use two malignancy prediction calculators to better characterize the risk of malignancy. There are recommendations for a higher nodule size threshold for follow-up (≥5 mm or ≥80 mm(3)) and a reduction of the follow-up period to 1 year for solid pulmonary nodules; both of these will reduce the number of follow-up CT scans. PET-CT plays a crucial role in characterization also, with an ordinal scale being recommended for reporting. Radiologists will be the key in implementing these guidelines, and routine use of volumetric image-analysis software will be required to manage patients with pulmonary nodules correctly.

Medical imaging in personalised medicine: a white paper of the research committee of the European Society of Radiology (ESR)

The future of medicine lies in early diagnosis and individually tailored treatments, a concept that has been designated 'personalised medicine' (PM), which aims to deliver the right treatment to the right patient at the right time. Medical imaging has always been personalised and is fundamental to almost all aspects of PM. It is instrumental in solving clinical differential diagnoses. Imaging procedures are tailored to the clinical problem and patient characteristics. Screening for preclinical disease is done with imaging. Stratification based on imaging biomarkers can help identify individuals suited for preventive intervention. Treatment decisions are based on the in vivo visualisation of the location and extent of an abnormality, as well as the loco-regional physiological, biochemical and biological processes using structural and molecular imaging. Image-guided biopsy provides relevant tissue specimens for genetic/molecular characterisation. In addition, radiogenomics relate imaging biomarkers to these genetic and molecular features. Furthermore, imaging is essential to patient-tailored therapy planning, therapy monitoring and follow-up of disease, as well as targeting non-invasive or minimally invasive treatments, especially with the rise of theranostics. Radiologists need to be prepared for this new paradigm as it will mean changes in training, clinical practice and in research. Key Points • Medical imaging is a key component in personalised medicine • Personalised prevention will rely on image-based screening programmes • Anatomical, functional and molecular imaging biomarkers affect decisions on the type and intensity of treatment • Treatment response assessment with imaging will improve personalised treatment • Image-based invasive intervention integrates personalised diagnosis and personalised treatment.