Radiological-pathological correlation of subsolid pulmonary nodules: A single centre retrospective evaluation of the 2011 IASLC adenocarcinoma classification system

INTRODUCTION

The 2011 IASLC classification system proposes guidelines for radiologists and pathologists to classify adenocarcinomas spectrum lesions as preinvasive, minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IA). IA portends the worst clinical prognosis, and the imaging distinction between MIA and IA is controversial.

MATERIALS AND METHODS

Subsolid pulmonary nodules resected by microcoil localization over a three-year period were retrospectively reviewed by three chest radiologists and a pulmonary pathologist. Nodules were classified radiologically based on preoperative computed tomography (CT), with the solid nodule component measured on mediastinal windows applied to high-frequency lung kernel reconstructions, and pathologically according to 2011 IASLC criteria. Radiology interobserver and radiological-pathological variability of nodule classification, and potential reasons for nodule classification discordance were assessed.

RESULTS

Seventy-one subsolid nodules in 67 patients were included. The average size of invasive disease focus at histopathology was 5 mm (standard deviation 5 mm). Radiology interobserver agreement of nodule classification was good (Cohen's Kappa = 0.604, 95 % CI: 0.447 to 0.761). Agreement between consensus radiological interpretation and pathological category was fair (Cohen's Kappa = 0.236, 95 % CI: 0.054-0.421). Radiological and pathological nodule classification were concordant in 52 % (37 of 71) of nodules. The IASLC proposed CT solid component cut-off of 5 mm to distinguish MIA and IA yielded a sensitivity of 59 % and specificity of 80 %. Common reasons for nodule classification discordance included multiple solid components within a nodule on CT, scar and stromal collapse at pathology, and measurement variability.

CONCLUSION

Solid component(s) within persistent part-solid pulmonary nodules raise suspicion for invasive adenocarcinoma. Preoperative imaging classification is frequently discordant from final pathology, reflecting interpretive and technical challenges in radiological and pathological analysis.

CT Evaluation for Clinical Lung Cancer Staging: Do Multiplanar Measurements Better Reflect Pathologic T-Stage than Axial Measurements?

Objective

To retrospectively investigate whether tumor size assessment on multiplanar reconstruction (MPR) CT images better reflects pathologic T-stage than evaluation on axial images and evaluate the additional value of measurement in three-dimensional (3D) space.

Materials and Methods

From 1661 patients who had undergone surgical resection for primary lung cancer between June 2013 and November 2016, 210 patients (145 men; mean age, 64.4 years) were randomly selected and 30 were assigned to each pathologic T-stage. Two readers independently measured the maximal lesion diameters on MPR CT. The longest diameters on 3D were obtained using volume segmentation. T-stages determined on CT images were compared with pathologic T-stages (overall and subgroup—Group 1, T1a/b; Group 2, T1c or higher), with differences in accuracy evaluated using McNemar's test. Agreement between readers was evaluated with intraclass correlation coefficients (ICC).

Results

The diagnostic accuracy of MPR measurements for determining T-stage was significantly higher than that of axial measurement alone for both reader 1 (74.3% [156/210] vs. 63.8% [134/210]; p = 0.001) and reader 2 (68.1% [143/210] vs. 61.9% [130/210]; p = 0.049). In the subgroup analysis, diagnostic accuracy with MPR diameter was significantly higher than that with axial diameter in only Group 2 (p < 0.05). Inter-reader agreements for the ICCs on axial and MPR measurements were 0.98 and 0.98. The longest diameter on 3D images showed a significantly lower performance than MPR, with an accuracy of 54.8% (115/210) (p < 0.05).

Conclusion

Size measurement on MPR CT better reflected the pathological T-stage, specifically for T1c or higher stage lung cancer. Measurements in a 3D plane showed no added value.

Measurement accuracy of lung nodule volumetry in a phantom study: Effect of axial-volume scan and iterative reconstruction algorithm

An axial-volume scan with adaptive statistical iterative reconstruction-V (ASIR-V) is newly developed. Our goal was to identify the influence of axial-volume scan and ASIR-V on accuracy of automated nodule volumetry.An "adult' chest phantom containing various nodules was scanned using both helical and axial-volume modes at different dose settings using 256-slice CT. All CT scans were reconstructed using 30% and 50% blending of ASIR-V and filtered back projection. Automated nodule volumetry was performed using commercial software. The image noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were measured.The axial-volume scan reduced radiation dose by 19.7% compared with helical scan at all radiation dose settings without affecting the accuracy of nodule volumetric measurement (P = .375). Image noise, CNR, and SNR were not significantly different between two scan modes (all, P > .05).The use of axial-volume scan with ASIR-V achieved effective radiation dose reduction while preserving the accuracy of nodule volumetry.

Stereotactic body radiotherapy in patients with lung tumors composed of mainly ground-glass opacity

We retrospectively reviewed the effect of stereotactic body radiation therapy (SBRT) in patients with stage I lung cancer whose lung tumor showed a nodular appearance of ground glass opacity, so-called ground glass nodule (GGN). A total of 84 patients (42 men, 42 women; mean age, 75 years) with stage I lung cancer with GGN accompanying a solid component <50% in diameter of the tumor and no metastases were studied. Concerning histology, 32 tumors were adenocarcinoma, 1 was squamous cell carcinoma, 2 were unclassified carcinoma and 49 cases were histology-unproven but increased in size or had a positive finding in 18F-FDG positron emission tomography (PET) examination. The median tumor size was 20 mm (range, 10-41 mm). All of the patients were treated with SBRT, and the total prescribed dose at the isocenter ranged between 48 Gy in four fractions and 84 Gy in ten fractions. Median follow-up duration was 33 months. No patient had local failure nor regional lymph node failure. The 3-year rate of distant failure was 2.6%. Two patients who experienced distant metastases had a past surgical history of initial lung cancer before SBRT. The rates of cause-specific and overall survival at 3 years were 98.2 and 94.6%, respectively. Treatment-related adverse events of ≥grade 4 were not reported. Although more cases and longer follow-ups are mandatory, SBRT may be one of the radical treatment options for patients with GGN.

Organ-based tube current modulation in chest CT. A comparison of three vendors

INTRODUCTION

Organ-based tube current modulation (OBTCM) is designed for anterior dose reduction in Computed Tomography (CT). The purpose was to assess dose reduction capability in chest CT using three organ dose modulation systems at different kVp settings. Furthermore, noise, diagnostic image quality and tumour detection was assessed.

METHODS

A Lungman phantom was scanned with and without OBTCM at 80-135/140 kVp using three CT scanners; Canon Aquillion Prime, GE Revolution CT and Siemens Somatom Flash. Thermo-luminescent dosimeters were attached to the phantom surface and all scans were repeated five times. Image noise was measured in three ROIs at the level of the carina. Three observers visually scored the images using a fivestep scale. A Wilcoxon Signed-Rank test was used for statistical analysis of differences.

RESULTS

Using the GE revolution CT scanner, dose reductions between 1.10 mSv (12%) and 1.56 mSv (24%) (p < 0.01) were found in the anterior segment and no differences posteriorly and laterally. Total dose reductions between 0.64 (8%) and 0.91 mSv (13%) were found across kVp levels (p < 0.00001). Maximum noise increase with OBTCM was 0.8 HU. With the Canon system, anterior dose reductions of 6-10% and total dose reduction of 0.74-0.76 mSv across kVp levels (p < 0.001) were found with a maximum noise increase of 1.1 HU. For the Siemens system, dose increased by 22-51% anteriorly; except at 100 kVp where no dose difference was found. Noise decreased by 1 to 1.5 HU.

CONCLUSION

Organ based tube current modulation is capable of anterior and total dose reduction with minimal loss of image quality in vendors that do not increase posterior dose.

IMPLICATIONS FOR PRACTICE

This research highlights the importance of being familiar with dose reduction technologies.

Stepwise Disease Progression Model of Subsolid Lung Adenocarcinoma with Cystic Airspaces

OBJECTIVES

Subsolid lung adenocarcinoma with cystic airspaces (LACA) is a unique manifestation of lung cancer. This study was conducted to establish a radiologic disease progression model of LACA and to explore its association with the clinical course and clinicopathologic features of LACA.

MATERIALS AND METHODS

Sixty patients with LACA who underwent surgery at our center between 2004 and 2017 were retrospectively reviewed. The morphological changes of LACA over time on 98 serial computed tomography scans from 27 of 60 patients were tracked to establish a radiologic disease progression model. Associations between this model and the clinicopathologic characteristics of LACA were investigated.

RESULTS

The following stepwise progression model of LACA was developed: in phase I, cystic airspaces (CAs) appear in the middle of non-solid nodules; in phase II, the CAs grow; in phase III, a solid component appears on the border of the CAs; and in phase IV, the solid component gradually surrounds the CAs and becomes thicker, and the CAs shrink. In total, 10 (17%), 33 (55%), and 17 (28%) LACA patients were classified as belonging to phases II, III, and IV at the time of surgery, respectively. More advanced phases were associated with higher pathologic T and N staging, lymphovascular invasion, visceral pleural invasion, spread through air spaces, and solid/micropapillary subtype. In the multivariate analysis, our model demonstrated a good discrimination capability for cancer recurrence risk.

CONCLUSIONS

The stepwise disease progression model of LACA based on radiologic findings developed in this study represented its natural clinical course and clinicopathologic features well.

The combined nomogram based on the CT features may be used as a complementary method of frozen sections to predict invasive lung adenocarcinoma manifesting as ground-glass nodules

Background

Frozen sections (FS) deferral sometimes occurs in the intraoperative pathological classification of early lung adenocarcinoma, which is not conducive to the decision-making of surgical treatment. Here, we compared the predictive performance of the combined nomogram based on the computer tomography (CT) features with FS to investigate whether the nomogram could be used as a complementary method for FS when FS deferral occurs to predict invasive adenocarcinoma (IAC) manifesting as ground-glass nodules (GGNs) during surgery.

Methods

In this study, 205 early lung adenocarcinomas manifesting as GGNs from 178 patients who had undergone surgical treatment were included and divided into a training set (n=123) and a validation set (n=82). The training set defined a hybrid nomogram incorporating CT features and intraoperative measured tumor size based on multivariate logistic regression to predict IAC, and the validation set was used to verified the predictive performance. We also collected the diagnostic results of FS and compared the predictive performance of the established nomogram with FS.

Results

The accuracy of combined nomogram in predicting IAC in the training and validation sets was 91.1% and 89.0%, respectively, and the predictive accuracy of FS in the training set and validation set was 87.0% and 86.6%, respectively. The predictive accuracy between the combined nomogram and FS have no significant difference.

Conclusions

Compared with FS, the performance of the combined nomogram in predicting the lung IAC manifesting as GGNs is satisfactory, which has the potential to be used as a complementary method for FS when FS deferrals during surgery.

Growth and Clinical Impact of 6-mm or Larger Subsolid Nodules after 5 Years of Stability at Chest CT

Background It remains unclear whether 5 years of stability is sufficient to establish the benign behavior of subsolid nodules (SSNs) of the lung. There are no guidelines for the length of follow-up needed for these SSNs. Purpose To investigate the incidence of interval growth of pulmonary SSNs 6 mm or greater in diameter after 5 years of stability and their clinical outcome. Materials and Methods This retrospective study assessed SSNs 6 mm or greater that were stable for 5 years after detection (January 2002 to December 2018). The incidence of interval growth after 5 years of stability and the clinical and radiologic features of these SSNs were investigated. Clinical stage shifts of growing SSNs, presence of metastasis, and overall survival were assessed during the follow-up period. Subgroup analysis was performed in patients with nonenhanced thin-section (section thickness ≤1.5 mm) CT for interval growth after 5 years of stability. Results A total of 235 SSNs in 235 patients (mean age, 64 years ± 10 [standard deviation]; 132 women) were evaluated. There were 212 pure ground-glass nodules and 24 part-solid nodules. During follow-up (median, 112 months; range, 84-208 months), five of the 235 SSNs (2%; three primary ground-glass nodules and two part-solid nodules) showed interval growth. Three of these five growing SSNs were 10 mm or greater. Three of the five SSNs with interval growth had clinical stage shifts after growth (from Tis [in situ] to T1mi [minimally invasive] in one lesion; from T1mi to T1a in two lesions). There were no deaths or metastases from lung cancer during follow-up. Of 160 SSNs imaged with section thickness of 1.5 mm or less, two (1%) grew; both lesions were 10 mm or greater. Conclusion Only 2% of subsolid pulmonary nodules greater than or equal to 6 mm that had been stable for 5 years showed subsequent growth. At median follow-up of 9 years (after the initial 5-year period of stability), growth of those lung nodules had no clinical effect. © RSNA, 2020 See also the editorial by Naidich and Azour in this issue.

CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists

OBJECTIVES

To evaluate the deep learning models for differentiating invasive pulmonary adenocarcinomas (IACs) among subsolid nodules (SSNs) considered for resection in a retrospective diagnostic cohort in comparison with a size-based logistic model and expert radiologists.

METHODS

This study included 525 patients (309 women; median, 62 years) to develop models, and an independent cohort of 101 patients (57 women; median, 66 years) was used for validation. A size-based logistic model and deep learning models using 2.5-dimension (2.5D) and three-dimension (3D) CT images were developed to discriminate IAC from less invasive pathologies. Overall performance, discrimination, and calibration were assessed. Diagnostic performances of the three thoracic radiologists were compared with those of the deep learning model.

RESULTS

The overall performances of the deep learning models (Brier score, 0.122 for the 2.5D DenseNet and 0.121 for the 3D DenseNet) were superior to those of the size-based logistic model (Brier score, 0.198). The area under the receiver operating characteristic curve (AUC) of the 2.5D DenseNet (0.921) was significantly higher than that of the 3D DenseNet (0.835; p = 0.037) and the size-based logistic model (0.836; p = 0.009). At equally high sensitivities of 90%, the 2.5D DenseNet showed significantly higher specificity (88.2%; all p < 0.05) and positive predictive value (97.4%; all p < 0.05) than other models. Model calibration was poor for all models (all p < 0.05). The 2.5D DenseNet had a comparable performance with the radiologists (AUC, 0.848-0.910).

CONCLUSION

The 2.5D DenseNet model could be used as a highly sensitive and specific diagnostic tool to differentiate IACs among SSNs for surgical candidates.

KEY POINTS

• The deep learning model developed using 2.5D DenseNet showed higher overall performance and discrimination than the size-based logistic model for the differentiation of invasive adenocarcinomas among subsolid nodules for surgical candidates. • The 2.5D DenseNet demonstrated a thoracic radiologist-level diagnostic performance and had higher specificity (88.2%) at equal sensitivities (90%) than the size-based logistic model (specificity, 52.9%). • The 2.5D DenseNet could be used to reduce potential overtreatment for the indolent subsolid nodules or to select candidates for sublobar resection instead of the standard lobectomy.

Preoperative bronchial cytology for the assessment of tumor spread through air spaces in lung adenocarcinoma resection specimens

BACKGROUND

Tumor spread through air spaces (STAS), a significant prognostic indicator, has been described recently as a pattern of invasion in pulmonary carcinomas. However, questions remain regarding preoperative identification of STAS and whether it represents an in vivo phenomenon versus an ex vivo artifact.

METHODS

We retrospectively reviewed 67 paired preoperative bronchoalveolar lavage (BAL) or bronchial washing (BW) cytology specimens with the subsequent lung adenocarcinoma surgical resection specimen to determine whether preoperative cytology could predict STAS. Other clinical, radiologic, and pathologic features of the resected lesions were also correlated with preoperative bronchial cytology results.

RESULTS

Positive bronchial cytology was observed in 28 cases (41.8%), 24 of which had STAS (85.7%); however, negative BAL/BW cytology was observed in 39 cases (58.2%), 29 of which had STAS (74.4%) (x²  = 1.27, P = .26, not significant). High-STAS burden was observed in 44 cases (83.0%), 21 (47.7%) with negative BAL/BW and 23 (52.3%) with positive BAL/BW. Low-STAS burden was observed in 9 cases (17.0%), 8 (88.9%) with negative BAL/BW and only 1 (11.1%) with positive BAL/BW (x²  = 5.11, P = .024, significant). For tumors with STAS, a statistically significant difference was identified in the maximal STAS distance from the main tumor edge between BAL/BW-positive and BAL/BW-negative groups (P = .007). Of the remaining clinicopathologic and radiologic features, only visceral pleural invasion was significantly associated with BAL/BW positivity.

CONCLUSION

Presurgical bronchial cytology alone cannot adequately predict tumor STAS; however, it may provide useful information regarding the extent and overall burden of STAS on the subsequent resection specimen.

Percutaneous CT-guided biopsy of lytic bone lesions in patients clinically suspected of lung cancer: Diagnostic performances for pathological diagnosis and molecular testing

OBJECTIVES

Bone is a common location for lung cancer metastasis. Clinicians are often reluctant to biopsy bone metastases, as they are known to require a decalcification process that damages nucleic acids, which makes it incompatible with molecular testing. We performed this study to assess the diagnostic performance of histopathology and molecular testing of computed tomography (CT)-guided percutaneous bone biopsies of lytic bone lesions during the initial assessment or during the progression of lung cancer.

MATERIALS AND METHODS

This retrospective study included all patients suspected of having or known to have primary lung cancer and CT-guided percutaneous bone biopsies of lytic bone from January 2010 to June 2017. The main judgment criterion was the diagnostic performance of the pathological analysis. Secondary endpoints were the diagnostic performance of molecular testing and incidence of complications.

RESULTS

Fifty patients were included. The yield of CT-guided percutaneous bone biopsies for pathological analysis was 100 %, allowing for a diagnosis of certainty in all cases. The percentage of tumor cells in samples was higher than the 20 % threshold in 83.9 % of cases. The yield of molecular analysis was 94.6 %. A mutation was found in 60 % of cases; most frequently in KRAS (Kirsten rat sarcoma viral oncogene homolog) (28.6 %) and EGFR (epidermal growth factor receptor) (14.3 %). The complication rate was 2 %, i.e. a minor undrained pneumothorax.

CONCLUSION

CT-guided percutaneous biopsies of lytic bone is associated with a very low complication rate and high diagnostic performance for histopathology and mutation testing.

Preoperative CT-based radiomics combined with intraoperative frozen section is predictive of invasive adenocarcinoma in pulmonary nodules: a multicenter study

Objectives

Develop a CT-based radiomics model and combine it with frozen section (FS) and clinical data to distinguish invasive adenocarcinomas (IA) from preinvasive lesions/minimally invasive adenocarcinomas (PM).

Methods

This multicenter study cohort of 623 lung adenocarcinomas was split into training (n = 331), testing (n = 143), and external validation dataset (n = 149). Random forest models were built using selected radiomics features, results from FS, lesion volume, clinical and semantic features, and combinations thereof. The area under the receiver operator characteristic curves (AUC) was used to evaluate model performances. The diagnosis accuracy, calibration, and decision curves of models were tested.

Results

The radiomics-based model shows good predictive performance and diagnostic accuracy for distinguishing IA from PM, with AUCs of 0.89, 0.89, and 0.88, in the training, testing, and validation datasets, respectively, and with corresponding accuracies of 0.82, 0.79, and 0.85. Adding lesion volume and FS significantly increases the performance of the model with AUCs of 0.96, 0.97, and 0.96, and with accuracies of 0.91, 0.94, and 0.93 in the three datasets. There is no significant difference in AUC between the FS model enriched with radiomics and volume against an FS model enriched with volume alone, while the former has higher accuracy. The model combining all available information shows minor non-significant improvements in AUC and accuracy compared with an FS model enriched with radiomics and volume.

Conclusions

Radiomics signatures are potential biomarkers for the risk of IA, especially in combination with FS, and could help guide surgical strategy for pulmonary nodules patients.

Key Points

• A CT-based radiomics model may be a valuable tool for preoperative prediction of invasive adenocarcinoma for patients with pulmonary nodules.

• Radiomics combined with frozen sections could help in guiding surgery strategy for patients with pulmonary nodules.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06597-8) contains supplementary material, which is available to authorized users.

Novelties in imaging in pulmonary fibrosis and nodules. A narrative review

In recent months two major fields of interest in pulmonary imaging have stood out: pulmonary fibrosis and pulmonary nodules. New guidelines have been released to define pulmonary fibrosis and subsequent studies have proved the value of these changes. In addition, new recommendations for classification of pulmonary nodules have been released. Radiological images are of major interest for automated and standardized analysis and so in both cases software tools using artificial intelligence were developed for visualization and quantification of the disease. These tools have been validated by human readers and demonstrated their capabilities. This review summarizes the new recommendations for classification of pulmonary fibrosis and nodules and reviews the capabilities of radiomics within these two entities.

Detection of pulmonary nodules: a clinical study protocol to compare ultra-low dose chest CT and standard low-dose CT using ASIR-V

INTRODUCTION

Lung cancer screening in individuals at risk has been recommended by various scientific institutions. One of the main concerns for CT screening is repeated radiation exposure, with the risk of inducing malignancies in healthy individuals. Therefore, lowering the radiation dose is one of the main objectives for radiologists. The aim of this study is to demonstrate that an ultra-low dose (ULD) chest CT protocol, using recently introduced hybrid iterative reconstruction (ASiR-V, GE medical Healthcare, Milwaukee, Wisconsin, USA), is as performant as a standard 'low dose' (LD) CT to detect non-calcified lung nodules ≥4 mm.

METHODS AND ANALYSIS

The total number of patients to include is 150. Those are referred for non-enhanced chest CT for detection or follow-up of lung nodule and will undergo an additional unenhanced ULD CT acquisition, the dose of which is on average 10 times lower than the conventional LD acquisition. Total dose of the entire exam (LD+ULD) is lower than the French diagnostic reference level for a chest CT (6.65 millisievert). ULD CT images will be reconstructed with 50% and 100% ASiR-V and LD CT with 50%. The three sets of images will be read in random order by two pair of radiologists, in a blind test, where patient identification and study outcomes are concealed. Detection rate (sensitivity) is the primary outcome. Secondary outcomes will include concordance of nodule characteristics; interobserver reproducibility; influence of subjects' characteristics, nodule location and nodule size; and concordance of emphysema, coronary calcifications evaluated by visual scoring and bronchial alterations between LD and ULD CT. In case of discordance, a third radiologist will arbitrate.

ETHICS AND DISSEMINATION

The study was approved by the relevant ethical committee. Each study participant will sign an informed consent form.

TRIAL REGISTRATION NUMBER

NCT03305978; Pre-results.

Volumetric assessment of solid pulmonary nodules on ultralow-dose CT: a phantom study

Background

To reduce the radiation exposure from chest computed tomography (CT), ultralow-dose CT (ULDCT) protocols performed at sub-millisievert levels were previously tested for the evaluation of pulmonary nodules (PNs). The purpose of our study was to investigate the effect of ULDCT and iterative image reconstruction on volumetric measurements of solid PNs.

Methods

CT datasets of an anthropomorphic chest phantom containing solid microspheres were obtained with a third-generation dual-source CT at standard dose, 1/8th, 1/20th and 1/70th of standard dose [CT volume dose index (CTDI_vol): 0.03-2.03 mGy]. Semi-automated volumetric measurements were performed on CT datasets reconstructed with filtered back projection (FBP) and advanced modelled iterative reconstruction (ADMIRE), at strength level 3 and 5. Absolute percentage error (APE) evaluated measurement accuracy related to the effective volume. Scan repetition differences were evaluated using Bland-Altman analysis. Two-way analysis of variance (ANOVA) assessed influence of different scan parameters on APE. Proportional differences (PDs) tested the effect of dose settings and reconstruction algorithms on volumetric measurements, as compared to the standard protocol (standard dose-FBP).

Results

Bland-Altman analysis revealed small mean interscan differences of APE with narrow limits of agreement (-0.1%±4.3% to -0.3%±3.8%). Dose settings (P<0.001), reconstruction algorithms (P<0.001), nodule diameters (P<0.001) and nodule density (P=0.011) had statistically significant influence on APE. Post-hoc Bonferroni tests showed slightly higher APE when scanning with 1/70th of standard dose [mean difference: 3.4%, 95% confidence interval (CI): 2.5-4.3%; P<0.001], and for image reconstruction with ADMIRE5 (mean difference: 1.8%, 95% CI: 1.0-2.5%; P<0.001). No significant differences for scanning with 1/20th of standard dose (P=0.42), and image reconstruction with ADMIRE3 (P=0.19) were found. Scanning with 1/70th of standard dose and image reconstruction with FBP showed the widest range of PDs (-16.8% to 23.4%) compared to standard dose-FBP.

Conclusions

Our phantom study showed no significant difference between nodule volume measurements on standard dose CT (CTDI_vol: 2 mGy) and ULDCT with 1/20th of standard dose (CTDI_vol: 0.10 mGy).

Visceral Pleural Invasion in Pulmonary Adenocarcinoma: Differences in CT Patterns between Solid and Subsolid Cancers

PURPOSE

To analyze the incidence and CT patterns of visceral pleural invasion (VPI) in adenocarcinomas on the basis of their CT presentation as solid or subsolid nodules.

MATERIALS AND METHODS

A total of 286 adenocarcinomas in direct contact with a pleural surface, resected at an institution between 2005 and 2016, were included in this retrospective, institutional review board-approved study. CT size and longest contact length with a pleural surface were measured and their ratios computed. Pleural deviation, pleural thickening, spiculations, different pleural tag types, pleural effusion, and the CT appearance of transgression into an adjacent lobe or infiltration of surrounding tissue were evaluated. Fisher exact tests and simple and multiple logistic regression models were used.

RESULTS

Of the 286 nodules, 179 of 286 (62.6%) were solid and 107 of 286 (37.4%) were subsolid. VPI was present in 49 of 286 (17.1%) nodules and was significantly more frequent in solid (44 of 179; 24.6%) than in subsolid nodules (five of 107; 4.7%; P < .001). In solid nodules, multiple regression analysis showed an association of higher contact length-to-size ratio (adjusted odds ratio [OR], 1.02; P = .007) and the presence of multiple pleural tag types (adjusted OR, 5.88; P = .002) with VPI. In subsolid nodules, longer pleural contact length of the solid nodular component (adjusted OR, 1.27; P = .017) and the CT appearance of transgression or infiltration (adjusted OR, 10.75; P = .037) were associated with VPI.

CONCLUSION

During preoperative evaluation of adenocarcinomas for the likelihood of VPI, whether a tumor manifests as a solid or a subsolid nodule is important to consider because the incidence of VPI is significantly higher in solid than in subsolid nodules. In addition, this study showed that the CT patterns associated with VPI differ between solid and subsolid nodules.© RSNA, 2019Supplemental material is available for this article.See also the commentary by Elicker in this issue.

Which T descriptor is more predictive of recurrence after sublobar resection: whole tumour size versus solid component size?

OBJECTIVES

We aimed to assess the predictive value of different T descriptors, including the whole tumour size (Dwhole) and solid component size (Dsolid), in patients with clinical Stage IA adenocarcinoma who underwent sublobar resection.

METHODS

According to computed tomography images in the lung window, T descriptors, Dwhole and Dsolid, were applied. To evaluate the predictive value of these 2 different descriptors in predicting tumour recurrence and pathological malignant behaviours, Cox hazard regression and a receiver-operating characteristic curve analysis, respectively, were used.

RESULTS

In total, 247 patients were included. Of these patients, 109 and 138 had ground glass and solid nodules, respectively. When the T descriptor was changed from Dwhole to Dsolid, 37 tumours (15%) were downgraded to T1a status from T1b/T1c status. Multivariable Cox analysis showed that Dsolid was an independent risk factor of worse recurrence-free survival [hazard ratio (HR) 2.36, 95% confidence interval (CI) 1.24-4.47; P = 0.009], while Dwhole was not (HR 1.51, 95% CI 0.79-2.89; P = 0.215). In the receiver-operating characteristic analysis, the areas under the curves for Dwhole and Dsolid used to identify pathological malignant behaviours were 0.598 and 0.739, respectively.

CONCLUSIONS

The T descriptor, which is represented by Dsolid, rather than Dwhole, is a better predictor of tumour recurrence after sublobar resection in clinical Stage IA lung adenocarcinoma. Furthermore, our results provide some clues indicating that sublobar resection should be performed cautiously in patients with lung adenocarcinoma manifesting as ground glass nodule with Dsolid >2 cm.

Can texture features improve the differentiation of infiltrative lung adenocarcinoma appearing as ground glass nodules in contrast-enhanced CT?

OBJECTIVES

To investigate the validity and efficacy of comparing texture features from contrast-enhanced images with non-enhanced images in identifying infiltrative lung adenocarcinoma represented as ground glass nodules (GGN).

MATERIALS AND METHODS

A retrospective cohort study was conducted with patients presenting with lung adenocarcinoma and treated at a single centre between January 2015 to December 2017. All patients underwent standard and contrast-enhanced thoracic CT scans with 0.5 mm collimation and 1 mm slice reconstruction thickness before surgery. A total of 34 lung adenocarcinoma patients (representing 34 lesions) were analysed; including 21 instances of invasive adenocarcinoma (IAC) lesions, 4 instances of adenocarcinoma in situ (AIS) lesions, and 9 minimally invasive adenocarcinoma (MIA) lesions. After radiologists manually segmented the lesions, texture features were quantitatively extracted using Artificial Intelligence Kit (AK) software. Then, multivariate logistic regression analysis based on standard and contrast-enhanced CT texture features was employed to analyse the invasiveness of lung adenocarcinoma lesions appearing as GGNs. A receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of those models.

RESULTS

A total of 21 quantitative texture features were extracted using the AK software. After dimensionality reduction, 5 and 3 features extracted from thin-section unenhanced and contrast-enhanced CT, respectively, were used to establish the model. The area under the ROC curve (AUC) values for unenhanced CT and enhanced CT features were 0.890 and 0.868, respectively. There was no significant difference (P = 0.190) in the AUC between models based on non-enhanced and contrast-enhanced CT texture features.

CONCLUSION

Compared with unenhanced CT, texture features extracted from contrast-enhanced CT provided no benefit in improving the differential diagnosis of infiltrative lung adenocarcinoma from non-infiltrative malignancies appearing as GGNs.

Incidental pulmonary nodules: characterization and management

This update covers the management of solitary or multiple pulmonary nodules detected incidentally in imaging studies done for other reasons. It describes the most appropriate computed tomography technique for the evaluation of these nodules, how they are classified, and how the different types of nodules are measured. It also reviews the patient-related and nodule-related criteria for determining the risk of malignancy. It discusses the recommendations in the guidelines recently published by the Fleischner Society for the management and follow-up of each type of nodules according to its size and risk of malignancy.

Management of pulmonary nodules

Pulmonary nodules are frequently detected during clinical practice and require a structured approach in their management in order to identify early lung cancers and avoid harm from over investigation. The article reviews the 2015 British Thoracic Society guidelines for the management of pulmonary nodules and the evidence behind them.

CT-Based Radiomics Model for Predicting Brain Metastasis in Category T1 Lung Adenocarcinoma

OBJECTIVE. The purpose of this study is to develop and evaluate an unenhanced CT-based radiomics model to predict brain metastasis (BM) in patients with category T1 lung adenocarcinoma. MATERIALS AND METHODS. A total of 89 eligible patients with category T1 lung adenocarcinoma were enrolled and classified as patients with BM (n = 35) or patients without BM (n = 54). A total of 1160 quantitative radiomic features were extracted from unenhanced CT images of each patient. Three prediction models (the clinical model, the radiomics model, and a hybrid [clinical plus radiomics] model) were established. The ROC AUC value and 10-fold cross-validation were used to evaluate the prediction performance of the models. RESULTS. In terms of predictive performance, the mean AUC value was 0.759 (95% CI, 0.643-0.867; sensitivity, 82.9%; specificity, 57.4%) for the clinical model, 0.847 (95% CI, 0.739-0.915; sensitivity, 80.0%; specificity, 81.5%) for the radiomics model, and 0.871 (95% CI, 0.767-0.933; sensitivity = 82.9%, specificity = 83.3%) for the hybrid model. The hybrid and radiomics models (p = 0.0072 and 0.0492, respectively) performed significantly better than the clinical model. No significant difference was found between the radiomics model and the hybrid model (p = 0.1022). CONCLUSION. A CT-based radiomics model presented good predictive performance and great potential for predicting BM in patients with category T1 lung adenocarcinoma. As a promising adjuvant tool, it can be helpful for guiding BM screening and thus benefiting personalized surveillance for patients with lung cancer.

Implementation planning for lung cancer screening in China

Lung cancer is the leading cause of cancer-related deaths in China, with over 690 000 lung cancer deaths estimated in 2018. The mortality has increased about five-fold from the mid-1970s to the 2000s. Lung cancer low-dose computerized tomography (LDCT) screening in smokers was shown to improve survival in the US National Lung Screening Trial, and more recently in the European NELSON trial. However, although the predominant risk factor, smoking contributes to a lower fraction of lung cancers in China than in the UK and USA. Therefore, it is necessary to establish Chinese-specific screening strategies. There have been 23 associated programmes completed or still ongoing in China since the 1980s, mainly after 2000; and one has recently been planned. Generally, their entry criteria are not smoking-stringent. Most of the Chinese programmes have reported preliminary results only, which demonstrated a different high-risk subpopulation of lung cancer in China. Evidence concerning LDCT screening implementation is based on results of randomized controlled trials outside China. LDCT screening programmes combining tobacco control would produce more benefits. Population recruitment (e.g. risk-based selection), screening protocol, nodule management and cost-effectiveness are discussed in detail. In China, the high-risk subpopulation eligible for lung cancer screening has not as yet been confirmed, as all the risk parameters have not as yet been determined. Although evidence on best practice for implementation of lung cancer screening has been accumulating in other countries, further research in China is urgently required, as China is now facing a lung cancer epidemic.

Does aggressive management of solitary pulmonary nodules pay off?

Indeterminate solitary pulmonary nodules (SPNs), measuring up to 3 cm in diameter, are incidental radiological findings. The ever-growing use of modern imaging has increased their detection. The majority of those nodules are benign; however, the possibility of diagnosing early-stage lung cancer still stands. Guidelines for the management of SPNs have never been validated in prospective comparative studies.

Positron emission tomography (PET) is a useful tool to provide functional information on SPNs. However, overall sensitivity and specificity of PET in detecting malignant SPNs of at least 10 mm in diameter are about 90% and false-negative results are reported.

The development of video-assisted thoracic surgery has provided minimally invasive diagnosis and treatment of SPNs. In our series, 105 patients underwent surgery based on combined increased ¹⁸F-labelled 2-fluoro-2-deoxy-d-glucose (FDG) uptake on PET computed tomography and radiological features (morphology and density) without prior histological confirmation. We detected 26 false negatives (24.8%) and only nine false positives (8.57%). Therefore, our minimally invasive surgical approach prevented 25% of patients with lung cancer from a delayed treatment versus only 9% undergoing “overtreatment”.

In our monocentric cohort, patients with SPNs with large diameter, irregular outline, no calcifications, central location, increased FDG uptake and/or subsolid aspect benefited from a primary surgical resection.

There is much debate on the best management of solitary pulmonary nodules. Even if they are mostly benign, they may represent an early-stage lung cancer. Minimally invasive surgical removal is probably the best approach to this insidious disease.http://ow.ly/wMKz30nemjR

CT Manifestations of Tumor Spread Through Airspaces in Pulmonary Adenocarcinomas Presenting as Subsolid Nodules

PURPOSE

The aim of this study was to identify potential computed tomography manifestations of pulmonary adenocarcinomas presenting as subsolid nodules and associated with the histologic evidence of spread of tumor through air spaces (STAS).

MATERIALS AND METHODS

From a radiologic-pathologic repository of resected pulmonary adenocarcinomas including 203 subsolid nodules, 40 STAS-positive nodules were randomly selected and matched to 40 STAS-negative nodules. Total average diameter, as well as average and long-axis diameters of the solid component, was measured. The proportion of solid component diameter to total average diameter was calculated. Measurements and proportions between STAS-positive and STAS-negative nodules were compared with paired samples t test, χ test, or the Fisher exact test.

RESULTS

The total average diameter in STAS-positive nodules was significantly larger than in STAS-negative nodules (P=0.024). The average and long-axis diameters of the solid component of STAS-positive nodules were significantly larger than that of STAS-negative nodules (P=0.001 and 0.003). The proportion of solid component to total average diameter was significantly larger in STAS-positive than in STAS-negative nodules (P=0.041). At a threshold of ≥10 mm for the average and the solid component long-axis diameters, significantly more nodules were STAS-positive than STAS-negative (P=0.015 and 0.001).

CONCLUSIONS

Total average diameter, average and long-axis diameters of the solid component, and a high proportion of solid component diameter compared with total average diameter are computed tomography manifestations of subsolid pulmonary adenocarcinomas with STAS. These findings could serve as an in-vivo tool for the likelihood estimation of STAS, and consequently influence management of subsolid adenocarcinomas.

Computer-Aided Detection of Pulmonary Nodules in Computed Tomography Using ClearReadCT

This study evaluates the accuracy of a computer-aided detection (CAD) application for pulmonary nodular lesions (PNL) in computed tomography (CT) scans, the ClearReadCT (Riverain Technologies). The study was retrospective for 106 biopsied PNLs from 100 patients. Seventy-five scans were Contrast-Enhanced (CECT) and 25 received no enhancer (NECT). Axial reconstructions in soft-tissue and lung kernel were applied at three different slice thicknesses, 0.75 mm (CECT/NECT n = 25/6), 1.5 mm (n = 18/9) and 3.0 mm (n = 43/18). We questioned the effect of (1) enhancer, (2) kernel and (3) slice thickness on the CAD performance. Our main findings are: (1) Vessel suppression is effective and specific in both NECT and CECT. (2) Contrast enhancement significantly increased the CAD sensitivity from 60% in NECT to 80% in CECT, P = 0.025 Fischer's exact test. (3) The CAD sensitivity was 84% in 3 mm slices compared to 68% in 0.75 mm slices, P > 0.2 Fischer's exact test. (4) Small lesions of low attenuation were detected with higher sensitivity. (5) Lung kernel reconstructions increased the false positive rate without affecting the sensitivity (P > 0.05 McNemar's test). In conclusion, ClearReadCT showed an optimized sensitivity of 84% and a positive predictive value of 67% in enhanced lung scans with thick, soft kernel reconstructions. NECT, thin slices and lung kernel reconstruction were associated with inferior performance.

Correlation between maximal tumor diameter of fresh pathology specimens and computed tomography images in lung adenocarcinoma

The authors compared maximal tumor diameters between fresh lung tissue and axial and multiplanar reformatted chest computed-tomography (CT) images in lung adenocarcinoma and investigated the factors affecting tumor-size discrepancies. This study included 135 surgically resected lung adenocarcinomas. An experienced pulmonary pathologist aimed to cut the largest tumor section and measured pathological tumor size (PTS) in fresh specimens. Radiological maximal tumor sizes (RTS) were retrospectively measured on axial (RTSax) and multiplanar reformatted (RTSre) chest CT images. Mean PTS, RTSax, and RTSre were 19.13 mm, 18.63 mm, and 20.80 mm, respectively. RTSre was significantly larger than PTS (mean difference, 1.68 mm; p<0.001). RTSax was also greater than PTS for 6−10-mm and 11−20-mm tumors. PTS and RTS were strongly positively correlated (RTSax, r² = 0.719, p<0.001; RTSre, r² = 0.833, p<0.001). The intraclass correlation coefficient was 0.915 between PTS and RTSax and 0.954 between PTS and RTSre. Postoperative down-staging occurred in 11.0% and 27.4% of tumors on performing radiological staging using RTSax and RTSre, respectively. Postoperative up-staging occurred in 12.3% and 1.4% of tumors on performing radiological staging using RTSax and RTSre, respectively. Multiple linear regression revealed that pleural dimpling (p = 0.024) was an independent factor affecting differences between PTS and RTSax. Specimen type (p = 0.012) and tumor location (p = 0.020) were independent factors affecting differences between PTS and RTSre. In conclusion, RTSre was significantly larger than PTS and caused postoperative down-staging in 27.4% of the tumors. Reliability analysis revealed that RTSre was more strongly correlated with PTS than RTSax. Specimen type and anatomical tumor location influenced the measured size differences between PTS and RTSre.

Variable radiological lung nodule evaluation leads to divergent management recommendations

Radiological evaluation of incidentally detected lung nodules on computed tomography (CT) influences management. We assessed international radiological variation in 1) pulmonary nodule characterisation; 2) hypothetical guideline-derived management; and 3) radiologists' management recommendations.107 radiologists from 25 countries evaluated 69 CT-detected nodules, recording: 1) first-choice composition (solid, part-solid or ground-glass, with percentage confidence); 2) morphological features; 3) dimensions; 4) recommended management; and 5) decision-influencing factors. We modelled hypothetical management decisions on the 2005 and updated 2017 Fleischner Society, and both liberal and parsimonious interpretations of the British Thoracic Society 2015 guidelines.Overall agreement for first-choice nodule composition was good (Fleiss' κ=0.65), but poorest for part-solid nodules (weighted κ 0.62, interquartile range 0.50-0.71). Morphological variables, including spiculation (κ=0.35), showed poor-to-moderate agreement (κ=0.23-0.53). Variation in diameter was greatest at key thresholds (5 mm and 6 mm). Agreement for radiologists' recommendations was poor (κ=0.30); 21% disagreed with the majority. Although agreement within the four guideline-modelled management strategies was good (κ=0.63-0.73), 5-10% of radiologists would disagree with majority decisions if they applied guidelines strictly.Agreement was lowest for part-solid nodules, while significant measurement variation exists at important size thresholds. These variations resulted in generally good agreement for guideline-modelled management, but poor agreement for radiologists' actual recommendations.

Updated Fleischner Society Guidelines for Managing Incidental Pulmonary Nodules: Common Questions and Challenging Scenarios

The new guidelines for managing incidental pulmonary nodules published by the Fleischner Society in 2017 reflect an improved understanding of the risk factors and biologic features of lung cancer. Specific topics emphasized in the updated guidelines include a new threshold size for follow-up, the importance of the morphologic features of nodules, accurate nodule measurements, recognition of subsolid components, understanding interval growth or change in nodule morphology, and knowledge of patient risk factors. The updated guidelines enable greater personal flexibility in the decision-making process and encourage individualized management of pulmonary nodules. These factors may introduce new challenges for radiologists, who previously used solely nodule size to make management recommendations. The authors describe eight scenarios that illustrate the challenges potentially encountered when applying the new guidelines to pulmonary nodule management. ^©RSNA, 2018.

Persistent/Recurrent Differentiated Thyroid Cancer: Clinical and Radiological Characteristics of Persistent Disease and Clinical Recurrence Based on Computed Tomography Analysis

BACKGROUND

The natural course of persistent/recurrent differentiated thyroid cancer (DTC) has not been fully elucidated. The purpose of this study was to assess the relative incidence and clinico-radiological characteristics of persistent disease and clinical recurrence based on computed tomography (CT) analysis in patients with persistent/recurrent DTC.

METHODS

From January 2005 to December 2016, this retrospective study included 107 patients (M:F = 28:79; M_age = 53.5 years) with surgically proven cervical locoregional recurrence of DTC. Two neck CT examinations (median interval 1.92 years; range 0.17-7.58 years) before the last thyroid cancer surgery within the study period were reevaluated. Based on the presence of the lesion on the first CT and its progression on the second CT, the locoregional recurrence was classified into the following categories: stable persistence (decrease, no change, or increase by <2 mm in short dimension on the second CT), progressive persistence (increase by ≥2 mm), and clinical recurrence (newly appeared on the second CT). Clinical and radiological characteristics of the three groups were compared using univariate and multivariate logistic regression analyses.

RESULTS

The relative incidences of stable persistence, progressive persistence, and clinical recurrence were 56.1% (60/107), 15.0% (16/107), and 29.0% (31/107), respectively. Multivariate analysis between the clinical recurrence (29.0%) and persistence (71.0%) groups revealed various independent factors for prediction of clinical recurrence. These included longer interval between the two CT examinations (median 2.67 vs. 1.79 years; p = 0.021), a smaller number of thyroid surgeries (1.16 ± 0.45 vs. 1.55 ± 0.81; p = 0.002), and a history of neck dissection at the location of the largest locoregional recurrence (70.0% vs. 31.4%; p < 0.001). There was no significant independent factor for differentiation between the stable persistence (78.9%; 60/76) and progressive persistence (21.1%; 16/76) groups. The results may have been influenced by selection bias because this study included only surgically proven cases.

CONCLUSIONS

With regard to cervical locoregional recurrence of DTC, active surveillance may be favored because more than a half of the cases are structurally persistent and stable. However, meticulous evaluation is necessary to detect progressive persistence and clinical recurrence, considering various clinical factors.

Predicting Malignancy Risk of Screen-Detected Lung Nodules-Mean Diameter or Volume

OBJECTIVE

In lung cancer screening practice low-dose computed tomography, diameter, and volumetric measurement have been used in the management of screen-detected lung nodules. The aim of this study was to compare the performance of nodule malignancy risk prediction tools using diameter or volume and between computer-aided detection (CAD) and radiologist measurements.

METHODS

Multivariable logistic regression models were prepared by using data from two multicenter lung cancer screening trials. For model development and validation, baseline low-dose computed tomography scans from the Pan-Canadian Early Detection of Lung Cancer Study and a subset of National Lung Screening Trial (NLST) scans with lung nodules 3 mm or more in mean diameter were analyzed by using the CIRRUS Lung Screening Workstation (Radboud University Medical Center, Nijmegen, the Netherlands). In the NLST sample, nodules with cancer had been matched on the basis of size to nodules without cancer.

RESULTS

Both CAD-based mean diameter and volume models showed excellent discrimination and calibration, with similar areas under the receiver operating characteristic curves of 0.947. The two CAD models had predictive performance similar to that of the radiologist-based model. In the NLST validation data, the CAD mean diameter and volume models also demonstrated excellent discrimination: areas under the curve of 0.810 and 0.821, respectively. These performance statistics are similar to those of the Pan-Canadian Early Detection of Lung Cancer Study malignancy probability model with use of these data and radiologist-measured maximum diameter.

CONCLUSION

Either CAD-based nodule diameter or volume can be used to assist in predicting a nodule's malignancy risk.

Pathologic T Descriptor of Nonmucinous Lung Adenocarcinomas Now Based on Invasive Tumor Size: How Should Pathologists Measure Invasion?

OBJECTIVES

The eighth edition of the American Joint Committee on Cancer staging manual now stratifies nonmucinous lung adenocarcinomas (nmLACAs) by the size of the invasive component only. This is determined by direct gross or microscopic measurement; however, a calculated invasive size based on the percentage of invasive growth patterns has been proposed as an alternative option.

METHODS

To compare radiologic with different pathologic assessments of invasive tumor size, we retrospectively reviewed a cohort of resected nmLACAs with a part-solid appearance on computed tomography (CT) scan (n = 112).

RESULTS

The median direct microscopic pathologic invasive measurements were not significantly different from the median calculated pathologic invasive measurements; however, the median CT invasive measurements were 0.26 cm larger than the median direct pathologic measurements (P < .001).

CONCLUSIONS

Our results show that pathologic calculated invasive tumor measurements are comparable to direct microscopic measurements of invasive tumor, thereby supporting the recommendation for use of calculated invasive tumor size by the pathologist if necessary.

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.