Managing Incidental Lung Nodules in Patients With a History of Oncologic Disease: A Survey of Thoracic Radiologists

Comparison of Ultrashort TE Lung MRI and HRCT Lungs for Detection of Pulmonary Nodules in Oncology Patients

Purpose The purpose of this study is to evaluate the detection rate of pulmonary nodules in ultrashort echo time (UTE) lung magnetic resonance imaging (MRI) and to compare it with computed tomography (CT) in oncology patients.

Materials and Methods All individuals undergoing radiotherapy/chemotherapy/regular follow-up or visiting the oncology department and referred to radiology department for nodule detection, during the period of 1 year, were subjected to UTE lung MRI using the sequence Flash 3d_spiralvibe coronal 1.25 mm iso and high-resolution CT lungs and the images were analyzed.

Results Among the total number of nodules detected in both lungs of all patients, nodules detected by CT were 241, and nodules detected by MRI were 212. The nodule detection rate by MRI was 87.96%. The detection rate of nodules for size equal to or more than 5 mm was nearly 100%. For nodules less than 5 mm, and equal to or more than 4 mm, MRI showed a comparable detection rate of 75%, while for nodules less than 4 mm, the detection rate was only 25%.

Conclusion Our study results indicate that lung MRI had a near-complete detection rate for nodules equal to or more than 5 mm in size. Hence, in oncology patients who are undergoing regular follow-up of the lung nodules, lung MRI using UTE can replace low-dose CT, which in turn reduces the radiation dose to the patient.

Impact of Bayesian penalized likelihood reconstruction on quantitative and qualitative aspects for pulmonary nodule detection in digital 2-[18F]FDG-PET/CT

To evaluate the impact of block sequential regularized expectation maximization (BSREM) reconstruction on quantitative and qualitative aspects of 2-[¹⁸F]FDG-avid pulmonary nodules compared to conventional ordered subset expectation maximization (OSEM) reconstruction method. Ninety-one patients with 144 2-[¹⁸F]FDG-avid pulmonary nodules (all ≤ 20 mm) undergoing PET/CT for oncological (re-)staging were retrospectively included. Quantitative parameters in BSREM and OSEM (including point spread function modelling) were measured, including maximum standardized uptake value (SUV_max). Nodule conspicuity in BSREM and OSEM images was evaluated by two readers. Wilcoxon matched pairs signed-rank test was used to compare quantitative and qualitative parameters in BSREM and OSEM. Pulmonary nodule SUV_max was significantly higher in BSREM images compared to OSEM images [BSREM 5.4 (1.2–20.7), OSEM 3.6 (0.7–17.4); p = 0.0001]. In a size-based analysis, the relative increase in SUV_max was more pronounced in smaller nodules (≤ 7 mm) as compared to larger nodules (8–10 mm, or > 10 mm). Lesion conspicuity was higher in BSREM than in OSEM (p < 0.0001). BSREM reconstruction results in a significant increase in SUV_max and a significantly improved conspicuity of small 2-[¹⁸F]FDG-avid pulmonary nodules compared to OSEM reconstruction. Digital 2-[¹⁸F]FDG-PET/CT reading may be enhanced with BSREM as small lesion conspicuity is improved.

Management of Pulmonary Nodules in Oncologic Patients: AJR Expert Panel Narrative Review

Cancer survivors are at higher risk than the general population for development of a new primary malignancy, most commonly lung cancer. Current lung cancer screening guidelines recommend low-dose chest CT for high-risk individuals, including patients with a history of cancer and a qualifying smoking history. However, major lung cancer screening trials have inconsistently included cancer survivors, and few studies have assessed management of lung nodules in this population. This narrative review highlights relevant literature and provides expert opinion for management of pulmonary nodules detected incidentally or by screening in oncologic patients. In patients with previously treated lung cancer, a new nodule most likely represents distant metastasis from the initial lung cancer or a second primary lung cancer; CT features such as nodule size and composition should guide decisions regarding biopsy, PET/CT, and CT surveillance. In patients with extrapulmonary cancers, nodule management requires individualized risk assessment; smoking is associated with increased odds of primary lung cancer, whereas specific primary cancer types are associated with increased odds of pulmonary metastasis. Nonneoplastic causes, such as infection, medication toxicity, and postradiation or postsurgical change, should also be considered. Future prospective studies are warranted to provide evidence-based data to assist clinical decision-making in this context.

Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT: impact of image reconstructions on diagnostic performance

OBJECTIVES

To evaluate the diagnostic performance of a deep learning algorithm for automated detection of small ¹⁸F-FDG-avid pulmonary nodules in PET scans, and to assess whether novel block sequential regularized expectation maximization (BSREM) reconstruction affects detection accuracy as compared to ordered subset expectation maximization (OSEM) reconstruction.

METHODS

Fifty-seven patients with 92 ¹⁸F-FDG-avid pulmonary nodules (all ≤ 2 cm) undergoing PET/CT for oncological (re-)staging were retrospectively included and a total of 8824 PET images of the lungs were extracted using OSEM and BSREM reconstruction. Per-slice and per-nodule sensitivity of a deep learning algorithm was assessed, with an expert readout by a radiologist/nuclear medicine physician serving as standard of reference. Receiver-operator characteristic (ROC) curve of OSEM and BSREM were assessed and the areas under the ROC curve (AUC) were compared. A maximum standardized uptake value (SUV_max)-based sensitivity analysis and a size-based sensitivity analysis with subgroups defined by nodule size was performed.

RESULTS

The AUC of the deep learning algorithm for nodule detection using OSEM reconstruction was 0.796 (CI 95%; 0.772-0.869), and 0.848 (CI 95%; 0.828-0.869) using BSREM reconstruction. The AUC was significantly higher for BSREM compared to OSEM (p = 0.001). On a per-slice analysis, sensitivity and specificity were 66.7% and 79.0% for OSEM, and 69.2% and 84.5% for BSREM. On a per-nodule analysis, the overall sensitivity of OSEM was 81.5% compared to 87.0% for BSREM.

CONCLUSIONS

Our results suggest that machine learning algorithms may aid detection of small ¹⁸F-FDG-avid pulmonary nodules in clinical PET/CT. AI performed significantly better on images with BSREM than OSEM.

KEY POINTS

• The diagnostic value of deep learning for detecting small lung nodules (≤ 2 cm) in PET images using BSREM and OSEM reconstruction was assessed. • BSREM yields higher SUV_maxof small pulmonary nodules as compared to OSEM reconstruction. • The use of BSREM translates into a higher detectability of small pulmonary nodules in PET images as assessed with artificial intelligence.

Prevalence and Clinical Relevance of Extracardiac Findings in Cardiovascular Magnetic Resonance Imaging

PURPOSE

To assess the prevalence of extracardiac findings (ECF) during cardiovascular magnetic resonance (CMR) examinations and their downstream effect on clinical management.

MATERIALS AND METHODS

We retrospectively identified 500 consecutive patients. Trans-axial balanced steady-state free precession nongated images acquired from the upper thorax to the upper abdomen were evaluated independently by 2 radiologists. ECF were classified as nonsignificant (benign, with no need for further investigation), significant (mandatory to be reported/monitored), and major (clinically remarkable pathology, mandatory to be reported/investigated/treated). Fifteen-month clinical follow-up information was collected through hospital records.

RESULTS

Of 500 patients, 108 (21.6%) showed a total of 153 ECF: 59 (11.8% of the entire study population; 38.5% of all ECF) nonsignificant, 76 (15.2%; 49.7%) significant, and 18 (3.6%; 11.8%) major ECF. The most frequent ECF were pleural effusion, hepatic cyst, renal cyst, and ascending aorta dilatation. Of 94 significant and major ECF, 46 were previously unknown and more common in older patients. Newly diagnosed major ECF (n=11, 2.2% of the entire study population, and 7.2% of all ECF)-including 5 tumors (1% of study population)-were confirmed by downstream evaluations and required specific treatment. Patients with major ECF were significantly older than patients without with major ECF. Newly diagnosed clinically significant and major ECF prompted downstream diagnostic tests in 44% and 100% of cases, respectively.

CONCLUSIONS

The detection of significant and major ECF is common during CMR reporting. The knowledge and the correct identification of most frequent ECF enable earlier diagnoses and faster treatment initiation of unknown extracardiac pathologies in patients referred to CMR imaging.

The clinical significance of indeterminate pulmonary nodules in melanoma patients at baseline and during follow-up chest CT

Objective

This study aims to determine an appropriate timeline to monitor indeterminate pulmonary nodules (IPN) in melanoma patients to confirm metastatic origin.

Materials and Methods

588 clinically non-metastatic melanoma patients underwent curative intent surgery during 3 years. Patients with baseline chest CT and at least one follow-up (FU) CT were retrospectively analyzed to assess for IPN. Patients with definitely benign nodules, metastases and non-melanoma malignancies were excluded. Change in volume from first to FU CT, initial diameter (D1) and volume (V1), distance from pleura, peripheral and perifissural location, density and clinical stage were evaluated. Nodules were volumetrically measured on CTs and were considered metastases if they increased in size between two CTs or if increase was accompanied by multiple new nodules or extrapulmonary metastases.

Results

148 patients were included. Two out of 243 baseline IPN detected in 70 patients, increased significantly in volume in 3 and 5 months and were proven metastases. During FU, 86% of 40 interval IPN detected in 28 patients, were proven metastases. Interval nodule (p < 0.0001, HR:243,CI:[57.32,1033.74]), 3-month volume change (OR:1.023,CI:[1.014,1.033]), V1 (OR:1.006,CI:[1.003,1.009]), D1 (OR:1.424,CI:[1.23,1.648]), distance from pleura (OR:1.03,CI:[1.003,1.059]), and combined stage IIC + III (OR:11.29,CI:[1.514,84.174]), were associated with increased risk for metastasis. 43%, 72% and 94% of patients with IPN were confirmed with metastases in the first FU CT at 3, 6 and 12 months respectively.

Conclusion

Baseline IPN are most likely benign, while interval IPN are high risk for metastasis. Absence of volume increase of IPN within 6 months excluded metastasis in most patients.

Primary lung cancer in patients with previous malignancies: a nationwide study

Overall survival of patients with cancer continues to increase and so they receive more frequent CT imaging, making oncological patients a growing population that effectively receives lung cancer screening in the course of daily practice. However, it is currently uncertain how early lung cancer detection in this subgroup of patients should be optimally managed. We describe the relationship between primary lung cancer and prior malignancies in a nationwide cohort, in an attempt to identify possible areas of improvement in nodule management. We found that a substantial number of subjects with lung cancer suffered from a prior malignancy; however, with the exception of otorhinolaryngeal malignancies, they did not show a high absolute risk for lung cancer. Future research should provide more data on how to handle this subgroup of patients in clinical and screening setting.

Management of incidental lung nodules <8 mm in diameter

Due to the increase of incidentally detected pulmonary nodules and the information obtained from several screening programs, updated guidelines with new recommendations for the management of small pulmonary nodules have been proposed. These international guidelines coincide in proposing periodic follow-up for small nodules, less than 8 mm of diameter. Fleischner and British Thoracic Society guidelines are the most recent and popular guidelines for incidental pulmonary nodules management. They have specific recommendations according to nodule characteristics (density and size) and cancer risk of the patient. Both guidelines separate recommendations for solid and subsolid nodules. Predictive risk models have been developed to improve the nodule management. In certain cases follow up may not be the best option. We discuss the scenarios and options to achieve a histologic diagnosis of these tiny pulmonary nodules.