Nonsolid Nodules Research Articles

MS 24.01 Natural History of GGO-Containing Tumors

The natural history of GGO-containing tumors, i.e., subsolid nodules (SSNs), is a major concern not only in CT lung cancer screening, but in daily clinical practice. SSNs are classified into pure ground-glass nodules (GGNs) and part-solid GGNs on the basis of their consistency. SSNs are classified according to their status as transient or persistent. Articles in the literature related to the natural history or long-term follow-up results of SSNs are summarized in Table. In the largest CT lung cancer screening cohort reported to date, nonsolid nodules (synonymous with pure GGNs) and part-solid nodules were detected in 4.2% (2392 of 57,496) and 5.0% (2892 of 57,496), respectively, of the participants at baseline (Table).

Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network

We present a computer-aided diagnosis system (CADx) for the automatic categorization of solid, part-solid and non-solid nodules in pulmonary computerized tomography images using a Convolutional Neural Network (CNN). Provided with only a two-dimensional region of interest (ROI) surrounding each nodule, our CNN automatically reasons from image context to discover informative computational features. As a result, no image segmentation processing is needed for further analysis of nodule attenuation, allowing our system to avoid potential errors caused by inaccurate image processing. We implemented two computerized texture analysis schemes, classification and regression, to automatically categorize solid, part-solid and non-solid nodules in CT scans, with hierarchical features in each case learned directly by the CNN model. To show the effectiveness of our CNN-based CADx, an established method based on histogram analysis (HIST) was implemented for comparison. The experimental results show significant performance improvement by the CNN model over HIST in both classification and regression tasks, yielding nodule classification and rating performance concordant with those of practicing radiologists. Adoption of CNN-based CADx systems may reduce the inter-observer variation among screening radiologists and provide a quantitative reference for further nodule analysis.

A multi-view deep convolutional neural networks for lung nodule segmentation.

We present a multi-view convolutional neural networks (MV-CNN) for lung nodule segmentation. The MV-CNN specialized in capturing a diverse set of nodule-sensitive features from axial, coronal and sagittal views in CT images simultaneously. The proposed network architecture consists of three CNN branches, where each branch includes seven stacked layers and takes multi-scale nodule patches as input. The three CNN branches are then integrated with a fully connected layer to predict whether the patch center voxel belongs to the nodule. The proposed method has been evaluated on 893 nodules from the public LIDC-IDRI dataset, where ground-truth annotations and CT imaging data were provided. We showed that MV-CNN demonstrated encouraging performance for segmenting various type of nodules including juxta-pleural, cavitary, and non-solid nodules, achieving an average dice similarity coefficient (DSC) of 77.67% and average surface distance (ASD) of 0.24, outperforming conventional image segmentation approaches.

The effect of radiation dose reduction on computer-aided detection (CAD) performance in a low-dose lung cancer screening population.

Lung cancer screening with low-dose CT has recently been approved for reimbursement, heralding the arrival of such screening services worldwide. Computer-aided detection (CAD) tools offer the potential to assist radiologists in detecting nodules in these screening exams. In lung screening, as in all CT exams, there is interest in further reducing radiation dose. However, the effects of continued dose reduction on CAD performance are not fully understood. In this work, we investigated the effect of reducing radiation dose on CAD lung nodule detection performance in a screening population. The raw projection data files were collected from 481 patients who underwent low-dose screening CT exams at our institution as part of the National Lung Screening Trial (NLST). All scans were performed on a multidetector scanner (Sensation 64, Siemens Healthcare, Forchheim Germany) according to the NLST protocol, which called for a fixed tube current scan of 25 effective mAs for standard-sized patients and 40 effective mAs for larger patients. The raw projection data were input to a reduced-dose simulation software to create simulated reduced-dose scans corresponding to 50% and 25% of the original protocols. All raw data files were reconstructed at the scanner with 1 mm slice thickness and B50 kernel. The lungs were segmented semi-automatically, and all images and segmentations were input to an in-house CAD algorithm trained on higher dose scans (75-300 mAs). CAD findings were compared to a reference standard generated by an experienced reader. Nodule- and patient-level sensitivities were calculated along with false positives per scan, all of which were evaluated in terms of the relative change with respect to dose. Nodules were subdivided based on size and solidity into categories analogous to the LungRADS assessment categories, and sub-analyses were performed. From the 481 patients in this study, 82 had at least one nodule (prevalence of 17%) and 399 did not (83%). A total of 118 nodules were identified. Twenty-seven nodules (23%) corresponded to LungRADS category 4 based on size and composition, while 18 (15%) corresponded to LungRADS category 3 and 73 (61%) corresponded to LungRADS category 2. For solid nodules ≥8 mm, patient-level median sensitivities were 100% at all three dose levels, and mean sensitivities were 72%, 63%, and 63% at original, 50%, and 25% dose, respectively. Overall mean patient-level sensitivities for nodules ranging from 3 to 45 mm were 38%, 37%, and 38% at original, 50%, and 25% dose due to the prevalence of smaller nodules and nonsolid nodules in our reference standard. The mean false-positive rates were 3, 5, and 13 per case. CAD sensitivity decreased very slightly for larger nodules as dose was reduced, indicating that reducing the dose to 50% of original levels may be investigated further for use in CT screening. However, the effect of dose was small relative to the effect of the nodule size and solidity characteristics. The number of false positives per scan increased substantially at 25% dose, illustrating the importance of tuning CAD algorithms to very challenging, high-noise screening exams.

Lung Cancers Manifesting as Part-Solid Nodules in the National Lung Screening Trial.

The objective of our study was to determine how often death occurred from lung cancers that manifested as part-solid nodules in the National Lung Screening Trial (NLST). NLST radiologists classified nodules as solid, ground-glass, or mixed. All lung cancers classified as mixed nodules by NLST radiologists were reviewed by four experienced radiologists and reclassified as solid, nonsolid, or part-solid nodules. When possible, volume doubling times (VDTs) were calculated separately for the entire nodule and for the solid component of the nodule. Of 88 screening-diagnosed lung cancer cases identified by the NLST radiologists as mixed nodules, study radiologists confirmed that 19 were part-solid nodules. All the part-solid nodules were present at baseline (time 0), and none of the patients with a part-solid nodule had lymph node enlargement at CT before diagnosis or metastases at resection. Multilobar stage IV (T4N0M1) bronchioloalveolar carcinoma was diagnosed in one patient 25.0 months after study randomization, and the patient died 67.9 months after randomization. All 18 patients with a solitary or dominant part-solid nodule underwent surgery, and none died of lung cancer. From randomization, the average time to diagnosis was 18.6 months and the average time of follow-up was 79.2 months. On the last CT examination performed before diagnosis, the average size of the solid component of the part-solid nodules was 9.2 mm (SD, 4.9); the solid component was larger than 10 mm in five patients. The median VDT based on the entire nodule was 476 days, and the median VDT based on the solid component alone was 240 days. None of the patients with lung cancer manifesting as a solitary or dominant part-solid nodule had lymph node enlargement or metastases at pathology, and none died of lung cancer within the follow-up time of the NLST.

MA01.05 Predictive Performances of NELSON Screening Program Based on Clinical, Metrological and Population Statistics

The balance of benefits and harms of screening programs depends on multiple factors such as the scenario of patient selection, the triage algorithm and the imaging methods. Because of the multifactorial nature of the outcome of screening programs, it is important to evaluate the performance of its components. We modeled the triage algorithm of the NELSON program for lung cancer screening in different scenarios in order to assess the robustness of the chosen approach. We are looking to develop a model that allows for testing the imaging protocol performance using various high-risk screening populations. Our Objective is to work out a simulator adaptive to multiple screening scenarios. In a first step, we tested a simulation of the NELSON triage algorithm by using published statistics as input data: the distribution of nodule size, the precision of nodule volume measurements and the distribution of nodules growth. We modeled the baseline round of NELSON triage algorithm. We simulated 10,000,000 ground truth (GT) data where the axial diameter of nodules followed a chi2 (df=1) distribution between 3 mm and 20 mm. For each of the GT nodule, we modeled also a chi2 (df=1) distribution of volume doubling time between 90 and 1000 days. We included into the model a Gaussian distribution of the time between visits (average: 105 days, standard deviation: 5 days). We modeled volume measurement of the nodules by adding a Gaussian random error as documented by the Quantitative Imaging Biomarker Alliance (QIBA) screening profile. We performed a by-nodule comparison between nodule classification by the triage algorithm and the corresponding GT in the first round. At each step of the triage algorithm, we evaluated Sensitivity (Se), Specificity (Sp), Positive Predictive Value (PPV) and Negative Predictive Value (NPV). Sensitivity of the triage algorithm for classifying nodules into size categories was for 96,6% for NODCAT2, 86.9% for NODCAT3 and 90.7% for NODCAT4. Classification of GROWCAT C yielded Se=66.2% / Sp=21.2%. We found an overall performance of the NELSON triage algorithm of Se/Sp 94.0%/80.3%.PPV was 11.3%, and NPV was 99.8% Mathematical modeling gives valuable insights into the performance of different components of triage algorithms in lung cancer screening. We found a markedly different test performance for size versus growth assessment of the NELSON triage algorithm. Future work will extent the model to non-solid nodules and multiple rounds of screening. Moreover, it may have the potential to optimize triage algorithms in the design of screening programs.

The Vancouver Lung Cancer Risk Prediction Model: Assessment by Using a Subset of the National Lung Screening Trial Cohort.

Purpose To assess the likelihood of malignancy among a subset of nodules in the National Lung Screening Trial (NLST) by using a risk calculator based on nodule and patient characteristics. Materials and Methods All authors received approval for use of NLST data. An institutional review board exemption and a waiver for informed consent were granted to the author with an academic appointment. Nodule characteristics and patient attributes with regard to benign and malignant nodules in the NLST were applied to a nodule risk calculator from a group in Vancouver, Canada. Patient populations and their nodule characteristics were compared between the NLST and Vancouver cohorts. Multiple thresholds were tested to distinguish benign nodules from malignant nodules. An optimized threshold value was used to determine positive and negative predictive values, and a full logistic regression model was applied to the NLST data set. Results Sufficient data were available for 4431 nodules (4315 benign nodules and 116 malignant nodules) from the NLST data set. The NLST and Vancouver data sets differed in that the former included fewer nodules per study, fewer nonsolid nodules, and more nodule spiculation and emphysema. A composite risk score threshold of 10% was determined to be optimal, demonstrating sensitivity, specificity, positive predictive value, and negative predictive value of 85.3%, 93.9%, 27.4%, and 99.6%, respectively. The receiver operating characteristic curve for the full regression model applied to the NLST database demonstrated an area under the receiver operating characteristic curve of 0.963 (95% confidence interval: 0.945, 0.974). Conclusion Application of an NLST data subset to the Vancouver risk calculator yielded a high discriminant value, which supports the use of a risk calculator method as a valuable approach to distinguish between benign and malignant nodules. © RSNA, 2016 Online supplemental material is available for this article.

CT Screening for Lung Cancer: Part-Solid Nodules in Baseline and Annual Repeat Rounds.

The purpose of this study was to assess the frequencies of identifying participants with part-solid nodules, of diagnostic pursuit, of diagnoses of lung cancer, and long-term lung cancer survival in baseline and annual repeat rounds of CT screening in the International Early Lung Cancer Action Project. Screenings were performed under a common protocol. Participants with solid, nonsolid, and part-solid nodules and the diagnoses of lung cancer were documented. Part-solid nodules were identified in 2892 of 57,496 (5.0%) baseline screening studies; 567 (19.6%) of these nodules resolved or decreased in size. Diagnostic pursuit led to the diagnosis of adenocarcinoma in 79 cases, all clinical stage I. At resection, one nodule (12-mm solid component) had a single N2 metastasis. A new part-solid nodule was identified in 541 of 64,677 (0.8%) annual repeat screenings; 377 (69.7%) of these nodules resolved or decreased in size. In eight cases among the 541, the diagnosis of adenocarcinoma manifesting as a part solid nodule was made; on retrospective review the nodule originally had been a nonsolid nodule. In another 20 cases, the cancer originally had manifested as a nonsolid nodule but had progressed to become part-solid at annual repeat screening before any diagnosis was pursued. These 28 annual repeat cases of lung cancer were all pathologic stage IA. Of the 107 cases of lung cancer (79 baseline cases and 28 annual repeat cases), 106 were surgically resected, and one baseline case was followed up with imaging for 4 years. The lung cancer survival rate was 100% with a median follow-up period from diagnosis of 89 months (interquartile range, 52-134 months). Lung cancers manifesting as part-solid nodules at repeat screening studies all started as nonsolid nodules. Among 107 cases of adenocarcinoma manifesting as a part-solid nodule, a single lymph node metastasis was found in a single case (solid component, 12 mm).

Lung Cancer Deaths in the National Lung Screening Trial Attributed to Nonsolid Nodules.

Purpose To validate the recommendation of performing annual follow-up of nonsolid nodules (NSNs) identified by computed tomographic (CT) screening for lung cancer, all cases of lung cancer manifesting as NSN in the National Lung Screening Trial (NLST) were reviewed. Materials and Methods Institutional review board and informed consent were waived for this study. The NLST database was searched to identify all participants with at least one NSN on CT scan with lung cancer as the cause of death (COD) documented by the NLST endpoint verification process. Among the 26 722 participants, 2534 (9.4%) had one or more NSNs, and lung cancer as the COD occurred for 48 participants. On review, 21 of the 48 patients had no NSN in the cancerous lobe, which left 27 patients whose CT scans were reviewed by four radiologists: Group A (n = 12) were cases of lung cancer as the COD because of adenocarcinoma, and group B (n = 15) were cases of lung cancer as the COD because of other cell types. Frequency of lung cancer as the COD because of NSN and the time from randomization to diagnosis within these groups was determined. Results Six of the 12 patients in group A had no NSN in the cancerous lobe whereas the remaining six patients had a dominant solid or part-solid nodule in the lobe that rapidly grew in four patients, was multifocal in one patient, and had a growing NSN in one patient in whom diagnosis was delayed for over 3 years. Five of the 15 patients in group B had no NSN, and for the remaining 10 patients, lung cancer as the COD was not because of NSN. Conclusion It seems unlikely that patients with lung cancer as the COD occurred with solitary or dominant NSN as long as annual follow-up was performed. This lends further support that lung cancers that manifest as NSNs have an indolent course and can be managed with annual follow-up. © RSNA, 2016.

Malignant Melanoma Metastasis in the Form of Nonsolid Nodules: Diagnosis by Percutaneous Lung Biopsy

Malignant Melanoma Metastasis in the Form of Nonsolid Nodules: Diagnosis by Percutaneous Lung Biopsy

Chemoprevention studies within lung cancer screening programmes.

While aggressive tobacco control and help to stop smoking are essential weapons in the fight against lung cancer, screening with low-dose computed tomography (LDCT) in high-risk populations and chemoprevention may also contribute to reducing lung cancer deaths. Persons undergoing LDCT screening are an ideal population to be tested for agents potentially able to prevent the development of lung cancer by the regression of precancerous lesions, which are routinely monitored as part of the screening process. Peripheral subsolid nodules appear as particularly suitable targets, since many are adenocarcinoma precursors.A study on inhaled budesonide (a potential chemopreventive drug) for 1 year found that the mean size of non-solid lung nodules was significantly reduced over 5 years of follow-up, compared to inhaled placebo, in a population of high-risk individuals with indeterminate lung nodules not requiring immediate specific investigation for lung cancer and detected as part of a lung cancer screening program with LDCT.A new randomised placebo-controlled phase-II trial to test the ability of aspirin to induce the regression of non-solid and partially solid nodules detected by LDCT screening has been started. The effect of aspirin on a miRNA signature able to predict the presence of both cancer and precancerous lesions in high-risk asymptomatic individuals is also being monitored in the trial. This signature was previously shown to predict the presence of both lung cancer and non-solid lung nodules in asymptomatic individuals.

Lung and pleura

Lung Pulmonary nodules are commonly observed in patients with cancer as well as in patients with no known malignancy particularly in heavy smokers. Most of these nodules are small (less than 8 mm). Even in cancer patients a large proportion of these small nodules are benign [1]. The likelihood of malignancy depends on individual aspects (cancer type, grading, staging, molecular markers etc.), nodule size and risk factors [1]. For example, in a heavy smoker with lung cancer and one additional nodule larger than 8 mm the nodule is more likely to represent a second primary than a solitary metastasis. In a non-smoker with advanced high-grade soft-tissue sarcoma a solitary nodule is more likely to represent a metastasis. In all cancer patients a significant proportion of pulmonary nodules represent benign lesions such as pulmonary lymph nodes or granulomas [2,3]. Non-solid nodules (ground glass opacities) are more likely to represent lung cancer (adenocarcinoma) than solid nodules [4,5]. However, they may represent benign lesions such as focal fibrosis or haemorrhage. Furthermore, some (haemorrhagic) metastases may present as non-solid nodules [6]. Consolidation or diffuse ground glass usually represents benign disease such as pneumonia. However, in adenocarcinoma with predominantly lepidic growth consolidation or diffuse ground glass may be due to cancer spread in the lung.

Metástasis de melanoma maligno en forma de nódulos no sólidos: diagnóstico mediante biopsia pulmonar percutánea

Metástasis de melanoma maligno en forma de nódulos no sólidos: diagnóstico mediante biopsia pulmonar percutánea

CT Screening for Lung Cancer: Nonsolid Nodules in Baseline and Annual Repeat Rounds.

To address the frequency of identifying nonsolid nodules, diagnosing lung cancer manifesting as such nodules, and the long-term outcome after treatment in a prospective cohort, the International Early Lung Cancer Action Program. A total of 57,496 participants underwent baseline and subsequent annual repeat computed tomographic (CT) screenings according to an institutional review board, HIPAA-compliant protocol. Informed consent was obtained. The frequency of participants with nonsolid nodules, the course of the nodule at follow-up, and the resulting diagnoses of lung cancer, treatment, and outcome are given separately for baseline and annual repeat rounds of screening. The χ(2) statistic was used to compare percentages. A nonsolid nodule was identified in 2392 (4.2%) of 57,496 baseline screenings, and pathologic pursuit led to the diagnosis of 73 cases of adenocarcinoma. A new nonsolid nodule was identified in 485 (0.7%) of 64,677 annual repeat screenings, and 11 had a diagnosis of stage I adenocarcinoma; none were in nodules 15 mm or larger in diameter. Nonsolid nodules resolved or decreased more frequently in annual repeat than in baseline rounds (322 [66%] of 485 vs 628 [26%] of 2392, P < .0001). Treatment of the cases of lung cancer was with lobectomy in 55, bilobectomy in two, sublobar resection in 26, and radiation therapy in one. Median time to treatment was 19 months (interquartile range [IQR], 6-41 months). A solid component had developed in 22 cases prior to treatment (median transition time from nonsolid to part-solid, 25 months). The lung cancer-survival rate was 100% with median follow-up since diagnosis of 78 months (IQR, 45-122 months). Nonsolid nodules of any size can be safely followed with CT at 12-month intervals to assess transition to part-solid. Surgery was 100% curative in all cases, regardless of the time to treatment.

A Segmentation Framework of Pulmonary Nodules in Lung CT Images.

Accurate segmentation of pulmonary nodules is a prerequisite for acceptable performance of computer-aided detection (CAD) system designed for diagnosis of lung cancer from lung CT images. Accurate segmentation helps to improve the quality of machine level features which could improve the performance of the CAD system. The well-circumscribed solid nodules can be segmented using thresholding, but segmentation becomes difficult for part-solid, non-solid, and solid nodules attached with pleura or vessels. We proposed a segmentation framework for all types of pulmonary nodules based on internal texture (solid/part-solid and non-solid) and external attachment (juxta-pleural and juxta-vascular). In the proposed framework, first pulmonary nodules are categorized into solid/part-solid and non-solid category by analyzing intensity distribution in the core of the nodule. Two separate segmentation methods are developed for solid/part-solid and non-solid nodules, respectively. After determining the category of nodule, the particular algorithm is set to remove attached pleural surface and vessels from the nodule body. The result of segmentation is evaluated in terms of four contour-based metrics and six region-based metrics for 891 pulmonary nodules from Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI) public database. The experimental result shows that the proposed segmentation framework is reliable for segmentation of various types of pulmonary nodules with improved accuracy compared to existing segmentation methods.

Long-term effects of inhaled budesonide on screening-detected lung nodules

A previously carried out randomized phase IIb, placebo-controlled trial of 1 year of inhaled budesonide, which was nested in a lung cancer screening study, showed that non-solid and partially solid lung nodules detected by low-dose computed tomography (LDCT), and not immediately suspicious for lung cancer, tended to regress. Because some of these nodules may be slow-growing adenocarcinoma precursors, we evaluated long-term outcomes (after stopping the 1-year intervention) by annual LDCT. We analyzed the evolution of target and non-target trial nodules detected by LDCT in the budesonide and placebo arms up to 5 years after randomization. The numbers and characteristics of lung cancers diagnosed during follow-up were also analyzed. The mean maximum diameter of non-solid nodules reduced significantly (from 5.03 mm at baseline to 2.61 mm after 5 years) in the budesonide arm; there was no significant size change in the placebo arm. The mean diameter of partially solid lesions also decreased significantly, but only by 0.69 mm. The size of solid nodules did not change. Neither the number of new lesions nor the number of lung cancers differed in the two arms. Inhaled budesonide given for 1 year significantly decreased the size of non-solid nodules detected by screening LDCT after 5 years. This is of potential importance since some of these nodules may progress slowly to adenocarcinoma. However, further studies are required to assess clinical implications. NCT01540552.

Preoperative flexible bronchoscopy in patients with persistent ground-glass nodule.

There are no accurate data on the diagnostic value of preoperative flexible bronchoscopy (FB) for persistent ground-glass nodule (GGN) of the lung. We evaluated the value of preoperative FB in patients with suspected GGN-type lung cancer. We retrospectively searched a database for subjects who had ‘ground-glass opacity’, ‘non-solid nodule’, ‘part-solid nodule’, or ‘sub-solid nodule’ on chest computed tomography reports between February 2004 and March 2012. Patients who had infiltrative ground-glass opacity lesions, mediastinal lymphadenopathy, or pleural effusion, focal ground-glass opacity lesions >3 cm, and were lost to follow-up were excluded. We assessed the diagnostic value of preoperative FB in patients with persistent GGNs who underwent surgical resection. In total, 296 GGNs were evaluated by FB in 264 patients with persistent GGNs who underwent preoperative FB and surgical resection. The median size of the GGNs was 18 mm; 135 (46%) were pure GGN and 161 (54%) were part-solid GGN. No visible tumor or unsuspected endobronchial metastasis was identified by preoperative FB. Only 3 (1%, 3/208) GGNs were identified preoperatively as malignant by bronchial washing cytology; all were part-solid GGNs. No other etiology was identified by FB. Of the GGNs, 271 (91%) were subsequently confirmed as malignant and 25 (9%) were confirmed as benign at surgical resection. Consequently, the overall diagnostic sensitivity and negative predictive value of preoperative FB on a per-nodule basis was 1% (3/271) and 8% (25/293), respectively. The preoperative FB did not change the surgical strategy. Preoperative FB did not add much to the evaluation of persistent GGNs of the lung. Routine preoperative FB may have limited value in surgical candidates with small persistent pure GGNs.

Adenocarcinoma with BAC features presented as the nonsolid nodule is prone to be false-negative on 18F-FDG PET/CT.

Purpose. The present study investigated which type of adenocarcinoma with BAC features was prone to be false-negative on 18F-FDG PET/CT. Materials and Methods. A retrospective study was performed on 51 consecutive patients with localized adenocarcinoma with BAC features. CT and PET were assessed for lesion size, GGO percentage, and SUVmax. Lesions with FDG uptake the same as or more than mediastinal blood-pool activity were considered as PET-positive. Results. Of the 51 cases, 19.6% presented as pure GGO nodules, 31.4% as mixed nodules, and 49.0% as solid nodules. None of the pure GGO nodules was 18F-FDG avid, compared with 37.5% of mixed nodules and 96.0% of solid nodules (χ 2 = 31.55, P = 0.000). In the mixed nodule group, SUVmax was negatively correlated with GGO percentage (r = −0.588; P = 0.021). The positive detection rate of 18F-FDG PET/CT was 50.0%, 55.6%, and 100% in tumors 1.1–2.0 cm, 2.1–3.0 cm, and >3.0 cm in diameter, respectively (χ 2 = 5.815, P = 0.055). General linear model factor analysis showed that the GGO was an important factor contributing to false-negative PET/CT results (F = 23.992, P = 0.000), but lesion size was not (F = 0.602, P = 0.866). Conclusions. The present study indicated that the adenocarcinoma with BAC features presented as nonsolid nodule is prone to be false negative on 18F-FDG PET/CT.

Management of solid and sub-solid lung nodules

Pulmonary nodules present a unique challenge for radiologists which includes the detection of malignancy and identification of benign disease, recommending the appropriate procedures to avoid unnecessary thoracotomy, and ensuring that excessive radiation from follow-up computed tomography (CT) examinations is kept to a minimum. Although seasoned radiologists can use an approach based on their extensive experience, in this era of evidence-based medicine, guidelines have been established that include both radiologic and clinical factors in an integrated fashion. Such guidelines have been developed by the Fleischner Society, first in 2005, for the management of small pulmonary nodules detected on CT scans, and then, in 2013, for the management of sub-solid nodules [1]. For incidentally detected solitary nodules, these guidelines integrate elements as individual risk factors (via pre-test probability), with lesion size, growth rate, and morphology, based on imaging characteristics. Relevant risk factors to consider in the evaluation of pulmonary nodules are smoking history and patient age. Patients with a substantial smoking history and over 40 years of age are defined as high-risk patients, whereas low-risk patients are those with a negligible smoking history and no other known risk factors, and who are below 40 years of age. Based on the Fleischner Society recommendation [1], lesions less than 4 mm do not require any further invasive or non-invasive measures or evaluations. However, lesions with a diameter of more than 8mm should be evaluated with either follow-up CT scans, including dynamic, contrast-enhanced scans, positron emission tomography (PET)-CT, and biopsy. For lesions that fall between the 4 mm and 8 mm size, CT follow-up with a limited number of scans is recommended. Sub-solid nodules are often found during screening studies or incidentally on CT scans. They are characterized by their appearance as rounded areas of increased attenuation, and a homogeneous or heterogeneous texture. Sub-solid nodules can be subdivided according to their composition: non-solid lesions that consist of ground-glass opacity only; and part solid lesions that contain both ground-glass and soft tissue elements. Sub-solid nodules can regress, persist, or grow. Small persistent non-solid nodules are often atypical adenomatous hypoplasia (AAH) and focal fibrosis, whereas non-solid and part-solid nodules that increase in size typically indicate malignancy, which can include adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma, as well as lympho-proliferative disease. How these lesions develop has not been entirely elucidated as yet, but it seems that a small percentage of ground-glass opacities (AAH) develop into larger lesions that can eventually comprise solid components due to invasion and alveolar collapse [2]. In any case, radiologically, an increase in lesion density, growth, or the development of solid portions are all indicative of malignancy. CT analysis and surveillance of sub-solid nodules is the modality of choice for the identification of malignant lesions. The primary factor is nodule size. While lesions less than 5 mm in diameter are usually AAHs, lesions greater than 15 mm is size are malignant, and are typically MIAs and invasive adenocarcinomas. Generally, a diameter of more than 8 mm is indicative of malignancy. Another important indicator of malignancy is lesion growth. The growth of the lesion may affect either the ground-glass or the solid components, or both. Volume doubling times of AIS and MIAs are much longer, compared to invasive adenocarcinomas and squamous cell lesions. Morphologically, the presence of lobulated borders, air bronchograms and bubble-like lucencies, and the development of solid portions in pure ground-glass abnormalities are all indicative of malignancy. Lesion morphology is closely related to prognosis. Nodules with an increasing percentage of solid components represent a poorer prognosis, but, for patients with pure ground-glass abnormalities or those with only a small area of a solid component, the survival rate after lesion resection is 100%. The Fleischner Society management guidelines [2] for sub-solid lesions recommend that part solid nodules, especially those that persist or grow in size, mandate further evaluation and monitoring, and typically, require surgical resection. Smaller lesions, with a negligible area of solid components, can be managed with follow-up CT scans.

Session: Evaluation of lung nodules: role of PET/CT

Computed Tomographic (CT) screening for lung cancer remains controversial, although the National Lung Screening Trial (NLST) found that low dose CT (LDCT) reduced lung cancer mortality by about 20% [1], the high rate of indeterminate and false positive lung nodules was worrying. The diagnostic work-up of CT nodules considers size (diameter or volume), characteristics (density, morphology, homogeneity) and volume doubling time (VDT), but several studies have investigated the ability of positron emission tomography (PET) to characterize nodules, although its role in diagnostic algorithms for screening-detected nodules has not been defined. The first PET study with [18F]fluorodeoxyglucose to characterize indeterminate nodules outside screening was published in 2001 [2]. In a previous study on PET-CT at baseline screening, we found an overall sensitivity of 88% for diagnosing malignancy, while for solid nodules >10 mm, sensitivity was 100%, suggesting PET-CT as an alternative to invasive procedures in the screening setting [3]. When assessing the ability of PET-CT to diagnose indeterminate nodules detected during the subsequent years of the screening and analyzing 383 PET-CT examinations performed over 6 study years of screening, the sensitivity, specificity and accuracy of visually evaluated PET-CT, in distinguishing benign from malignant nodules, were 64%, 89% and 76% respectively. PET performance varied with nodule diameter (accuracy increased from 70% for nodules <10 mm to 82% for nodules ≥15 mm) and nodule type (accuracy ranged from 88% for solid nodules to 46% for non-solid nodules). We do not use FNAB routinely in our screening protocol. Typically we proceed to surgery when nodule characteristics, including VDT, often backed up by PET-CT, indicate malignancy. The disadvantage is that a preoperative pathological diagnosis is not available and a wedge resection with frozen section examination is required before radical surgery. Nodules on PET-CT are commonly evaluated by semi-quantitative SUVbw max, which is operator independent, as well as by visual assessment of uptake by the nuclear medicine physician, whose experience can markedly influence the result. In our study we evaluated both methods and found visual assessment afforded higher accuracy (76%) than any SUV threshold with a good compromise between sensitivity (64%) and specificity (89%); while increasing the threshold from 1.5 to 2.5 decreased sensitivity (67% to 51%) and increased specificity (80% to 91%). To conclude, PET-CT has high NPV for solid nodules ≥15 mm, and high PPV for sub-solid nodules <10 mm, justifying its inclusion in the diagnostic work-up of indeterminate nodules identified on LDCT screening. It is more useful for nodules detected at baseline, while sensitivity is low for sub-solid nodules and nodules discovered after baseline: for these other diagnostic modalities, particularly VDT, are more useful.