Objective definition and measurement method of ground-glass opacity for planning limited resection in patients with clinical stage IA adenocarcinoma of the lung1

Mean computed tomography value to predict spread through air spaces in clinical N0 lung adenocarcinoma

BACKGROUND

The aim of this study was to assess the ability of radiologic factors such as mean computed tomography (mCT) value, consolidation/tumor ratio (C/T ratio), solid tumor size, and the maximum standardized uptake (SUVmax) value by F-18 fluorodeoxyglucose positron emission tomography to predict the presence of spread through air spaces (STAS) of lung adenocarcinoma.

METHODS

A retrospective study was conducted on 118 patients those diagnosed with clinically without lymph node metastasis and having a pathological diagnosis of adenocarcinoma after undergoing surgery. Receiver operating characteristics (ROC) analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUVmax value to predict STAS. Univariate and multiple logistic regression analyses were performed to determine the independent variables for the prediction of STAS.

RESULTS

Forty-one lesions (34.7%) were positive for STAS and 77 lesions were negative for STAS. The STAS positive group was strongly associated with a high mCT value, high C/T ratio, large solid tumor size, large tumor size and high SUVmax value. The mCT values were - 324.9 ± 19.3 HU for STAS negative group and - 173.0 ± 26.3 HU for STAS positive group (p < 0.0001). The ROC area under the curve of the mCT value was the highest (0.738), followed by SUVmax value (0.720), C/T ratio (0.665), solid tumor size (0.649). Multiple logistic regression analyses using the preoperatively determined variables revealed that mCT value (p = 0.015) was independent predictive factors of predicting STAS. The maximum sensitivity and specificity were obtained at a cutoff value of - 251.8 HU.

CONCLUSIONS

The evaluation of mCT value has a possibility to predict STAS and may potentially contribute to the selection of suitable treatment strategies.

Quantifying invasiveness of clinical stage IA lung adenocarcinoma with computed tomography texture features

OBJECTIVES

The study objectives were to establish and validate a nomogram for pathological invasiveness prediction in clinical stage IA lung adenocarcinoma and to help identify those potentially unsuitable for sublobar resection-based computed tomography texture features.

METHOD

Patients with clinical stage IA lung adenocarcinoma who underwent surgery at Guangdong Provincial People's Hospital between January 2015 and October 2018 were retrospectively reviewed. All surgically resected nodules were pathologically classified into less-invasive and invasive cohorts. Each nodule was manually segmented, and its computerized texture features were extracted. Clinicopathological and computed tomographic texture features were compared between 2 cohorts. A nomogram for distinguishing the pathological invasiveness was established and validated.

RESULTS

Among 428 enrolled patients, 249 were diagnosed with invasive pathological subtypes. Smoking status (odds ratio, 2.906; 95% confidence interval, 1.285-6.579; P = .011), mean computed tomography attenuation value (odds ratio, 1.005, 95% confidence interval, 1.002-1.007; P < .001), and entropy (odds ratio, 8.536, 95% confidence interval, 3.478-20.951; P < .001) were identified as independent predictors for pathological invasiveness by multivariate logistics regression analysis. The nomogram showed good calibration (P = .182) with an area under the curve of 0.849 when validated with testing set data. Decision curve analysis indicated the potentially clinical usefulness of the model with respect to treat-all or treat-none scenario. Compared with intraoperative frozen-section, the nomogram performed better in pathological invasiveness diagnosis (area under the curve, 0.815 vs 0.670; P = .00095).

CONCLUSIONS

We established and validated a nomogram to compute the probability of invasiveness of clinical stage IA lung adenocarcinoma with great calibration, which may contribute to decisions related to resection extent.

Predicting recurrence of non-small cell lung cancer based on mean computed tomography value

Background

The aim of this study was to assess the ability of using mean computed tomography (mCT) values to predict non-small cell lung cancer (NSCLC) tumor recurrence.

Methods

A retrospective study was conducted on 494 patients with stage IA NSCLC. Receiver operating characteristics analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUV to predict tumor recurrence. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of tumor recurrence.

Results

The m-CT values were − 213.7 ± 10.2 Hounsfield Units (HU) for the recurrence group and − 594.1 ± 11.6 HU for the non-recurrence group (p < 0.0001). Recurrence occurred in 45 patients (9.1%). The tumor recurrence group was strongly associated with a high CT attenuation value, high C/T ratio, large solid tumor size, and SUV. The diagnostic value of mCT value was more accurate than the C/T ratio, excluding the pure ground-glass opacity and pure solid (0 < C/T ratio < 100) groups. The SUV and mCT are independent predictive factors of tumor recurrence.

Conclusions

The evaluation of mCT values was useful for predicting recurrence after the limited resection of small-sized NSCLC, and may potentially contribute to the selection of suitable treatment strategies.

Semi-Quantitative Analysis for Determining the Optimal Threshold Value on CT to Measure the Solid Portion of Pulmonary Subsolid Nodules

PURPOSE

This study aimed to investigate the optimal threshold value in Hounsfield units (HU) on CT to detect the solid components of pulmonary subsolid nodules using pathologic invasive foci as reference.

MATERIALS AND METHODS

Thin-section non-enhanced chest CT scans of 25 patients with pathologically confirmed minimally invasive adenocarcinoma were retrospectively reviewed. On CT images, the solid portion was defined as the area with higher attenuation than various HU thresholds ranging from -600 to -100 HU in 50-HU intervals. The solid portion was measured as the largest diameter on axial images and as the maximum diameter on multiplanar reconstruction images. A linear mixed model was used to evaluate bias in each threshold by using the pathological size of invasive foci as reference.

RESULTS

At a threshold of -400 HU, the biases were lowest between the largest/maximum diameter of the solid portion of subsolid nodule and the size of invasive foci of the pathological specimen, with 0.388 and -0.0176, respectively. They showed insignificant difference (p = 0.2682, p = 0.963, respectively) at a threshold of -400 HU.

CONCLUSION

For quantitative analysis, -400 HU may be the optimal threshold to define the solid portion of subsolid nodules as a surrogate marker of invasive foci.

Generalized chest CT and lab curves throughout the course of COVID-19

A better understanding of temporal relationships between chest CT and labs may provide a reference for disease severity over the disease course. Generalized curves of lung opacity volume and density over time can be used as standardized references from well before symptoms develop to over a month after recovery, when residual lung opacities remain. 739 patients with COVID-19 underwent CT and RT-PCR in an outbreak setting between January 21st and April 12th, 2020. 29 of 739 patients had serial exams (121 CTs and 279 laboratory measurements) over 50 ± 16 days, with an average of 4.2 sequential CTs each. Sequential volumes of total lung, overall opacity and opacity subtypes (ground glass opacity [GGO] and consolidation) were extracted using deep learning and manual segmentation. Generalized temporal curves of CT and laboratory measurements were correlated. Lung opacities appeared 3.4 ± 2.2 days prior to symptom onset. Opacity peaked 1 day after symptom onset. GGO onset was earlier and resolved later than consolidation. Lactate dehydrogenase, and C-reactive protein peaked earlier than procalcitonin and leukopenia. The temporal relationships of quantitative CT features and clinical labs have distinctive patterns and peaks in relation to symptom onset, which may inform early clinical course in patients with mild COVID-19 pneumonia, or may shed light upon chronic lung effects or mechanisms of medical countermeasures in clinical trials.

A Subsolid Nodules Imaging Reporting System (SSN-IRS) for Classifying 3 Subtypes of Pulmonary Adenocarcinoma

OBJECTIVES

To develop an imaging reporting system for the classification of 3 adenocarcinoma subtypes of computed tomography (CT)-detected subsolid pulmonary nodules (SSNs) in clinical patients.

METHODS

Between November 2011 and October 2017, 437 pathologically confirmed SSNs were retrospectively identified. SSNs were randomly divided 2:1 into a training group (291 cases) and a testing group (146 cases). CT-imaging characteristics were analyzed using multinomial univariable and multivariable logistic regression analysis to identify discriminating factors for the 3 adenocarcinoma subtypes (pre-invasive lesions, minimally invasive adenocarcinoma, and invasive adenocarcinoma). These factors were used to develop a classification and regression tree model. Finally, an SSN Imaging Reporting System (SSN-IRS) was constructed based on the optimized classification model. For validation, the classification performance was evaluated in the testing group.

RESULTS

Of the CT-derived characteristics of SSNs, qualitative density (nonsolid or part-solid), core (non-core or core), semantic features (pleural indentation, vacuole sign, vascular invasion), and diameter of solid component (≤6 mm or >6 mm), were the most important factors for the SSN-IRS. The total sensitivity, specificity, and diagnostic accuracy of the SSN-IRS was 89.0% (95% confidence interval [CI], 84.8%-92.4%), 74.6% (95% CI, 70.8%-78.1%), and 79.4% (95% CI, 76.5%-82.0%) in the training group and 84.9% (95% CI, 78.1%-90.3%), 68.5% (95% CI, 62.8%-73.8%), and 74.0% (95% CI, 69.6%-78.0%) in the testing group, respectively.

CONCLUSIONS

The SSN-IRS can classify 3 adenocarcinoma subtypes using CT-based characteristics of subsolid pulmonary nodules. This classification tool can help clinicians to make follow-up recommendations or decisions for surgery in clinical patients with SSNs.

Three-dimensional mean CT attenuation value of pure and part-solid ground-glass lung nodules may predict invasiveness in early adenocarcinoma

AIM

This study evaluated the relationship between three-dimensional (3D) mean computed tomography (CT) attenuation values of ground-glass nodules (GGN) and pathological invasiveness in early lung adenocarcinoma. The diagnostic accuracy of 3D CT attenuation values was compared with that of two-dimensional (2D) CT attenuation values and standardised uptake value on positron-emission tomography (PET).

MATERIALS AND METHODS

Surgical and radiological data from 96 pure or part-solid GGNs of <20 mm were analysed retrospectively. Mean 2D and 3D CT attenuation values of the tumours were obtained with semi-automated volumetric software. Pathological invasiveness was diagnosed according to the International Association for the Study of Lung Cancer (IASLC))/American Thoracic Society (ATS)/European Respiratory Society (ERS) classification. Pre-invasive lesions and minimally invasive adenocarcinomas were classified as non-invasive adenocarcinoma. Univariate and multivariate analyses determined relationships between pathological invasiveness and clinical/radiological findings. Receiver operating characteristic (ROC) analysis was performed to determine the optimal cut-off value for detecting invasive adenocarcinoma.

RESULTS

A total of 66 non-invasive and 30 invasive adenocarcinoma cases between 2010 and 2016 were analysed. Univariate analysis revealed four tumour invasiveness-associated predictors: maximum diameter, SUVmax, mean 2D CT attenuation value, and mean 3D CT attenuation value (p<0.05). Multivariate analysis revealed that the maximum diameter, SUVmax, and mean 3D CT attenuation value were significant predictors of pathological invasiveness (p=0.023, 0.022, 0.004). The area under the ROC curve to predict invasive adenocarcinoma for mean 3D CT attenuation value was 0.838 and the cut-off value was -489 HU.

CONCLUSION

The mean 3D CT attenuation value could distinguish pre-invasive lesions and minimally invasive adenocarcinoma from invasive adenocarcinoma.

Can Quantitative Volumetric Analysis Predict Tumor Recurrence in the Patients with Mucinous Adenocarcinoma of the Lung After Surgical Resection?

RATIONALE AND OBJECTIVES

Mucinous adenocarcinoma (MAC) is a distinct histologic variant subtype of lung adenocarcinomas. However, detailed radiologic findings and prognostic factors are still poorly understood. Thus, this study aimed to investigate the prognostic value of quantitative volumetric analysis of the computed tomography images of patients with MAC after. surgical resection.

MATERIALS AND METHODS

Semiautomatic segmentation from computed tomography images of 60 patients with pathologically confirmed MAC was performed and retrospectively reviewed. The main cutoff value in Hounsfield Units (HU) to predict tumor recurrence was defined by receiver-operating curve analysis. Solid volume of mass (SVM) was defined as the volume of HU greater than this cutoff, and solid ratio (Sratio) was defined as SVM divided by total volume. Each parameter was compared to clinicopathologic characteristics and maximum standardized uptake value. Disease-free survival (DFS) was assessed and was compared among patients. Univariate and multivariate Cox regression was performed to predict DFS of MAC.

RESULTS

The cutoff value of HU as determined by ROC analysis was 20 HU. SVM and Sratio were positively correlated with the maximum standardized uptake and pathologic invasion size, respectively (p < 0.001). SVM and Sratio were significantly higher in the recurrence group than in the no-recurrence group (p < 0.001). Multivariate Cox proportional hazards regression analysis revealed that the SVM (Hazard Ratio 1.016; 95% Confidence Interval 1.000-1.032; p = 0.048) and Sratio (Hazard Ratio 29.136; 95% Confidence Interval 1.419-598.191; p = 0.029) were independent significant predictors of DFS.

CONCLUSION

Quantitative volumetric parameters can predict the prognosis of patients with MAC after surgical resection.

High versus low attenuation thresholds to determine the solid component of ground-glass opacity nodules

Objectives

To evaluate and compare the diagnostic accuracy of high versus low attenuation thresholds for determining the solid component of ground-glass opacity nodules (GGNs) for the differential diagnosis of adenocarcinoma in situ (AIS) from minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA).

Methods

Eighty-six pathologically confirmed GGNs < 3 cm observed in 86 patients (27 male, 59 female; mean age, 59.3 ± 11.0 years) between January 2013 and December 2015 were retrospectively included. The solid component of each GGN was defined using two different attenuation thresholds: high (-160 Hounsfield units [HU]) and low (-400 HU). According to the presence or absence of solid portions, each GGN was categorized as a pure GGN or part-solid GGN. Solid components were regarded as indicators of invasive foci, suggesting MIA or IA.

Results

Among the 86 GGNs, there were 57 cases of IA, 19 of MIA, and 10 of AIS. Using the high attenuation threshold, 44 were categorized as pure GGNs and 42 as part-solid GGNs. Using the low attenuation threshold, 13 were categorized as pure GGNs and 73 as part-solid GGNs. The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for the invasive focus were 55.2%, 100%, 100%, 22.7%, and 60.4%, respectively, for the high attenuation threshold, and 93.4%, 80%, 97.2%, 61.5%, and 91.8%, respectively, for the low attenuation threshold.

Conclusion

The low attenuation threshold was better than the conventional high attenuation threshold for determining the solid components of GGNs, which indicate invasive foci.

The "solid" component within subsolid nodules: imaging definition, display, and correlation with invasiveness of lung adenocarcinoma, a comparison of CT histograms and subjective evaluation

OBJECTIVE

To validate three proposed definitions of the "solid" component of subsolid nodules, as compared to CT histograms and the use of different window settings, for discriminating the invasiveness of adenocarcinomas in a manner that facilitates routine clinical assessment.

METHODS

We retrospectively analyzed 328 pathologically confirmed lung adenocarcinomas, manifesting as subsolid nodules. Three-dimensional CT histograms were generated by setting 11 CT attenuation intervals from - 400 to 50 HU, at 50 HU intervals, and the voxel percentage within each CT attenuation interval was generated automatically. Three definitions of the "solid" component were proposed, and 10 medium window settings were set to evaluate the "solid" component. The diagnostic performance of the three definitions for identifying invasive adenocarcinoma was compared with that of CT histogram analysis and subjective evaluation with medium window settings.

RESULTS

A parallel diagnosis using five intervals with the largest AUC (AUC ≥ 0.797) demonstrated good differential diagnostic performance, with 78% sensitivity and 73.7% specificity. Definition 2 (visibility in the mediastinum window) yielded higher accuracy (75.6%) than the other two definitions (p < 0.01). A medium window setting of - 50 WL/2 WW gave a larger AUC than the other nine medium window settings as well as definition 2, with 82.5% specificity and 88.5% PPV, which was higher than those of parallel diagnosis with CT histogram and definition 2.

CONCLUSION

Using - 50 WL/2 WW is the optimum approach for evaluating the "solid" component and discriminating invasiveness, superior to using 3D CT histograms and definition 2, and convenient in routine clinical assessment.

KEY POINTS

• - 50 WL/2 WW gave a larger AUC than definition 2. • The specificity of - 50 WL/2 WW was higher than CT histograms. • - 50 WL/2 WW offers the best evaluation of the solid component.

Controversies on lung cancers manifesting as part-solid nodules

PURPOSE

Summarise survival of patients with resected lung cancers manifesting as part-solid nodules (PSNs).

METHODS

PubMed/MEDLINE and EMBASE databases were searched for all studies/clinical trials on CT-detected lung cancer in English before 21 December 2015 to identify surgically resected lung cancers manifesting as PSNs. Outcome measures were lung cancer-specific survival (LCS), overall survival (OS), or disease-free survival (DFS). All PSNs were classified by the percentage of solid component to the entire nodule diameter into category PSNs <80% or category PSNs ≥80%.

RESULTS

Twenty studies reported on PSNs <80%: 7 reported DFS and 2 OS of 100%, 6 DFS 96.3-98.7%, and 11 OS 94.7-98.9% (median DFS 100% and OS 97.5%). Twenty-seven studies reported on PSNs ≥80%: 1 DFS and 2 OS of 100%, 19 DFS 48.0%-98.0% (median 82.6%), and 16 reported OS 43.0%-98.0% (median DFS 82.6%, OS 85.5%). Both DFS and OS were always higher for PSNs <80%.

CONCLUSION

A clear definition of the upper limit of solid component of a PSN is needed to avoid misclassification because cell-types and outcomes are different for PSN and solid nodules. The workup should be based on the size of the solid component.

KEY POINTS

• Lung cancers manifesting as PSNs are slow growing with high cure rates. • Upper limits of the solid component are important for correct interpretation. • Consensus definition is important for the management of PSNs. • Median disease-free-survival (DFS) increased with decreasing size of the nodule.

[Threshold Segmentation of Pulmonary Subsolid Nodules on CT Images: Detection and Quantification of the Solid Component]

BACKGROUND

The detection and quantification of solid components in pulmonary subsolid nodules (SSN) are of vital importance on differential diagnosis, pathological speculation and prognosis prediction. However, no objective and wide-accepted criterion has been built up to now. The purpose of this study is to explore the optimal threshold that can be used for the detection and quantification of solid components in SSNs by using threshold segmentation method on computed tomography (CT) images.

METHODS

CT images of 102 SSNs were retrospectively analyzed. To establish a reference standard, the observers made judgments on whether the solid component existed in every SSN and did manual measurements of the volume of solid component with the help of software. Threshold segmentations of every nodule were then performed using different threshold settings and all of the measured volumes were assumed to be solid volumes, then solid-to-total volume ratios were calculated. The results were compared with the reference standards using the receiver operating characteristic curve and Wilcoxon test.

RESULTS

The application of thresholds as -250 HU or -300 HU resulted in high diagnostic value on the detection of solid component, with area under curve values as 0.982 and 0.977, respectively; the cut-off values of solid-to-total volume ratio were 1.10% and 6.14%, respectively; the median volumes of solid components were 202.7 mm3 (598.2 mm3), 247.1 mm3(696.0 mm3), which were not significantly different from the reference standard[199.5 mm3 (743.1 mm3)](P=0.125,1, 0.061,3).

CONCLUSIONS

Threshold segmentation on chest CT images is valuable to detect and quantify the solid component on SSNs, the thresholds as -250 HU and -300 HU are recommended.
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Mean Computed Tomography Value to Predict the Tumor Invasiveness in Clinical Stage IA Lung Cancer

BACKGROUND

The purpose of this study was to validate the ability of the mean computed tomography (m-CT) value to predict tumor invasiveness and recurrence, and further, to compare with other measurements such as consolidation/tumor ratio and solid tumor size.

METHODS

A retrospective study was conducted of 494 patients with clinical stage IA lung cancer who had peripherally located lung adenocarcinoma. Receiver operating characteristic curve analysis was used to compare the ability to predict tumor invasiveness and recurrence between m-CT value, consolidation/tumor ratio, and tumor size. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of pathologic, less invasive lung cancer. Disease-free survival was measured from the date of the operation until any recurrence.

RESULTS

The m-CT values were 643.6 ± 9.4 Hounsfield units in the noninvasive cancer group and 365.9 ± 11.4 Hounsfield units in the invasive cancer group (p < 0.0001). The invasive cancer group was strongly associated with a high CT attenuation value, high consolidation/tumor ratio, large solid tumor size, large tumor size, and high standardized uptake value. Multiple logistic analyses, including the preoperatively determined variables, revealed that standardized uptake value and m-CT are independent predictive factors of less invasive lung cancer. In addition, the hazard ratio of the m-CT value was higher than that of the standardized uptake value value.

CONCLUSIONS

The evaluation of m-CT value is useful in predicting less invasive lung cancer. The m-CT value can potentially determine operative procedure, particularly limited resection for peripheral lung adenocarcinoma.

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

OBJECTIVE

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.

MATERIALS AND METHODS

Screenings were performed under a common protocol. Participants with solid, nonsolid, and part-solid nodules and the diagnoses of lung cancer were documented.

RESULTS

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).

CONCLUSION

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).

Evaluation of lymph node metastasis in lung cancer: who is the chief justice?

Accurate determination of the diagnosis and the stage of lung cancer play a critical role to ensure that patients are provided the optimal treatment. However, the process is usually beyond complex. Early studies have suggested lymph nodes (LNs) >1.0 cm in size on computed tomography (CT) are considered as metastatic nodes, while the sensitivity of this criterion is not satisfied. Subsequently, positron emission tomography-computed tomography (PET-CT) was shown to be superior to CT alone on assessment of nodal involvement and was widely used to estimate suitability for resection with curative intent, but the dependability also remains controversial. Furthermore, transbronchial needle aspiration (TBNA) with and without endobronchial ultrasound (EBUS), as a well-accepted minimally invasive approach for LN biopsy, has been documented as an efficient tool in evaluation of CT and PET-CT negative LNs. Additionally, radiographic features including ground-glass/solid nodules ratio, referring as imaging biomarker, were indicated to be correlated with metastasis. Hence, we highlight the importance of comprehensive estimation of mediastinal and hilar LNs, and we suggested the judgment of LNs by radiographic tools alone might not be reliable and TBNA is indispensable in certain circumstances.

Computer-Aided Nodule Assessment and Risk Yield Risk Management of Adenocarcinoma: The Future of Imaging?

Increased clinical use of chest high-resolution computed tomography results in increased identification of lung adenocarcinomas and persistent subsolid opacities. However, these lesions range from very indolent to extremely aggressive tumors. Clinically relevant diagnostic tools to noninvasively risk stratify and guide individualized management of these lesions are lacking. Research efforts investigating semiquantitative measures to decrease interrater and intrarater variability are emerging, and in some cases steps have been taken to automate this process. However, many such methods currently are still suboptimal, require validation and are not yet clinically applicable. The computer-aided nodule assessment and risk yield software application represents a validated tool for the automated, quantitative, and noninvasive tool for risk stratification of adenocarcinoma lung nodules. Computer-aided nodule assessment and risk yield correlates well with consensus histology and postsurgical patient outcomes, and therefore may help to guide individualized patient management, for example, in identification of nodules amenable to radiological surveillance, or in need of adjunctive therapy.

Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT

PURPOSE

To investigate the importance of presurgical computed tomography (CT) intensity and texture information from ground-glass opacities (GGO) and solid nodule components for the prediction of adenocarcinoma recurrence.

METHODS

For this study, 101 patients with surgically resected stage I adenocarcinoma were selected. During the follow-up period, 17 patients had disease recurrence with six associated cancer-related deaths. GGO and solid tumor components were delineated on presurgical CT scans by a radiologist. Computational texture models of GGO and solid regions were built using linear combinations of steerable Riesz wavelets learned with linear support vector machines (SVMs). Unlike other traditional texture attributes, the proposed texture models are designed to encode local image scales and directions that are specific to GGO and solid tissue. The responses of the locally steered models were used as texture attributes and compared to the responses of unaligned Riesz wavelets. The texture attributes were combined with CT intensities to predict tumor recurrence and patient hazard according to disease-free survival (DFS) time. Two families of predictive models were compared: LASSO and SVMs, and their survival counterparts: Cox-LASSO and survival SVMs.

RESULTS

The best-performing predictive model of patient hazard was associated with a concordance index (C-index) of 0.81 ± 0.02 and was based on the combination of the steered models and CT intensities with survival SVMs. The same feature group and the LASSO model yielded the highest area under the receiver operating characteristic curve (AUC) of 0.8 ± 0.01 for predicting tumor recurrence, although no statistically significant difference was found when compared to using intensity features solely. For all models, the performance was found to be significantly higher when image attributes were based on the solid components solely versus using the entire tumors (p < 3.08 × 10(-5)).

CONCLUSIONS

This study constitutes a novel perspective on how to interpret imaging information from CT examinations by suggesting that most of the information related to adenocarcinoma aggressiveness is related to the intensity and morphological properties of solid components of the tumor. The prediction of adenocarcinoma relapse was found to have low specificity but very high sensitivity. Our results could be useful in clinical practice to identify patients for which no recurrence is expected with a very high confidence using a presurgical CT scan only. It also provided an accurate estimation of the risk of recurrence after a given duration t from surgical resection (i.e., C-index = 0.81 ± 0.02).

Radiologic Predictors for Clinical Stage IA Lung Adenocarcinoma with Ground Glass Components: A Multi-Center Study of Long-Term Outcomes

Objective

This study was to define preoperative predictors from radiologic findings for the pathologic risk groups based on long-term surgical outcomes, in the aim to help guide individualized patient management.

Methods

We retrospectively reviewed 321 consecutive patients with clinical stage IA lung adenocarcinoma with ground glass component on computed tomography (CT) scanning. Pathologic diagnosis for resection specimens was based on the 2011 IASLC/ATS/ERS classification of lung adenocarcinoma. Patients were classified into different pathologic risk grading groups based on their lymph node status, local regional recurrence and overall survival. Radiologic characteristics of the pulmonary nodules were re-evaluated by reconstructed three-dimension CT (3D-CT). Univariate and multivariate analysis identifies independent radiologic predictors from tumor diameter, total volume (TV), average CT value (AVG), and solid-to-tumor (S/T) ratio. Receiver operating characteristic curves (ROC) studies were carried out to determine the cutoff value(s) for the predictor(s). Univariate cox regression model was used to determine the clinical significance of the above findings.

Results

A total of 321 patients with clinical stage IA lung adenocarcinoma with ground glass components were included in our study. Patients were classified into two pathologic low- and high- risk groups based on their distinguished surgical outcomes. A total of 134 patients fell into the low-risk group. Univariate and multivariate analyses identified AVG (HR: 32.210, 95% CI: 3.020–79.689, P<0.001) and S/T ratio (HR: 12.212, 95% CI: 5.441–27.408, P<0.001) as independent predictors for pathologic risk grading. ROC curves studies suggested the optimal cut-off values for AVG and S/T ratio were-198 (area under the curve [AUC] 0.921), 2.9 (AUC 0.996) and 54% (AUC 0.907), respectively. The tumor diameter and TV were excluded for the low AUCs (0.778 and 0.767). Both the cutoff values of AVG and S/T ratio were correlated with pathologic risk classification (p<0.001). Univariate Cox regression model identified clinical risk classification (RR: 3.011, 95%CI: 0.796–7.882, P = 0.095) as a good predictor for recurrence-free survival (RFS) in patients with clinical stage IA lung adenocarcinoma. Statistical significance of 5-year OS and RFS was noted among clinical low-, moderate- and high-risk groups (log-rank, p = 0.024 and 0.010).

Conclusions

The AVG and the S/T ratio by reconstructed 3D-CT are important preoperative radiologic predictors for pathologic risk grading. The two cutoff values of AVG and S/T ratio are recommended in decision-making for patients with clinical stage IA lung adenocarcinoma with ground glass components.

Correlation between histological invasiveness and the computed tomography value in pure ground-glass nodules

Purpose

The purpose of this study was to evaluate the correlation between histological invasiveness and the computed tomography (CT) value and size in pure ground-glass nodules (GGNs) to determine optimal “follow-up or resection” strategies.

Methods

Between 2001 and 2014, 78 resected, pure GGNs were retrospectively evaluated. The maximum diameter and CT value of pure GGNs were measured using a computer graphics support system.

Results

All GGNs with a maximum diameter ≤10 mm and CT value ≤−600 Hounsfield units (HU) were considered to be noninvasive lesions, while 21 of 26 (81 %) with a maximum diameter >10 mm and CT value >−600 HU were considered to be invasive lesions. With respect to the correlation between each histological type and pure GGN with a maximum diameter ≤10 mm and CT value ≤−600 HU, the specificity was 90 % and the sensitivity and negative predictive value were both 100 % in atypical adenomatous hyperplasia (AAH), while the specificity was 58 % and the sensitivity and positive predictive value were 0 % in minimally invasive and invasive adenocarcinoma.

Conclusion

Pure GGNs with a maximum diameter of ≤10 mm and CT value of ≤−600 HU are nearly always pre-invasive lesions; therefore, surgery should be carefully selected in such patients.

Computerized texture analysis of persistent part-solid ground-glass nodules: differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas

PURPOSE

To retrospectively investigate the value of computerized three-dimensional texture analysis for differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas (IPAs) that manifest as part-solid ground-glass nodules (GGNs).

MATERIALS AND METHODS

The institutional review board approved this retrospective study with a waiver of patients' informed consent. The study consisted of 86 patients with 86 pathologic analysis-confirmed part-solid GGNs (mean size, 16 mm ± 5.4 [standard deviation]) who had undergone computed tomographic (CT) imaging between January 2005 and October 2011. Each part-solid GGN was manually segmented and its computerized texture features were quantitatively extracted by using an in-house software program. Multivariate logistic regression analysis was performed to investigate the differentiating factors of preinvasive lesions from IPAs. Three-layered artificial neural networks (ANNs) with a back-propagation algorithm and receiver operating characteristic curve analysis were used to build a discriminating model with texture features and to evaluate its discriminating performance.

RESULTS

Pathologic analysis confirmed 58 IPAs (seven minimally invasive adenocarcinomas and 51 invasive adenocarcinomas) and 28 preinvasive lesions (four atypical adenomatous hyperplasias and 24 adenocarcinomas in situ). IPAs and preinvasive lesions exhibited significant differences in various histograms and volumetric parameters (P < .05). Multivariate analysis revealed that smaller mass (adjusted odds ratio, 0.092) and higher kurtosis (adjusted odds ratio, 3.319) are significant differentiators of preinvasive lesions from IPAs (P < .05). With mean attenuation, standard deviation of attenuation, mass, kurtosis, and entropy, the ANNs model showed excellent accuracy in differentiation of preinvasive lesions from IPAs (area under the curve, 0.981).

CONCLUSION

In part-solid GGNs, higher kurtosis and smaller mass are significant differentiators of preinvasive lesions from IPAs, and preinvasive lesions can be accurately differentiated from IPAs by using computerized texture analysis. Online supplemental material is available for this article.

Can image analysis on high-resolution computed tomography predict non-invasive growth in adenocarcinoma of the lung?

PURPOSE

Preoperative radiological predictions of pathological invasiveness must be objective and reproducible in addition to being accurate when considering limited surgery for early lung cancer.

METHODS

Two cohorts were used for the analysis. Two independent observers traced lesion edges and measured areas and proportions of solid component on tumor images with the largest diameter by high resolution computed tomography images and "Image J" software.

RESULTS

The value of the intraclass correlation was 0.997 (95% confidence interval [CI], 0.996-0.998) for the area of solid component and 0.979 (95%CI, 0.958-0.986) for the proportion of solid component, suggesting such parameters were reliable in terms of reproducibility. Az value was 0.898 (95%CI, 0.842-0.953) for the area of solid component and 0.882 (95%CI, 0.816-0.949) for the proportion of solid component, demonstrating 2 parameters were both highly predictive of non-invasive adenocarcinoma. The optimal prediction of non-invasive adenocarcinoma with a cut-off value of 7.5 mm(2) for the area of solid component resulted in a sensitivity of 85.3% and specificity of 86.2% in Cohort 1 and a sensitivity of 66.7% and specificity of 88.5% in Cohort 2.

CONCLUSION

Image analysis using "Image J" software was promising for predicting non-invasive adenocarcinoma with its limited inter-observer variability and high predictive performance.

Characteristics of subsolid pulmonary nodules showing growth during follow-up with CT scanning

OBJECTIVE

The positive results of a screening CT scan trial are likely to lead to an increase in the use of CT scanning, and, consequently, an increase in the detection of subsolid nodules. Noninvasive methods including follow-up with CT scanning, to determine which nodules require invasive diagnosis and surgical treatment, should be defined promptly.

METHODS

Between 2000 and 2008, from our database of . 60,000 examinations with CT scanning, we identified 174 subsolid nodules, which showed a ground-glass opacity area . 20% of the nodule and measured 2 cm in diameter, in 171 patients. We investigated the clinical characteristics and CT images of the subsolid nodules in relation to changes identified during the follow-up period.

RESULTS

The nodule sizes ranged from 4 mm to 20 mm at the fi rst presentation. Nonsolid nodules numbered 98. During the follow-up period, 18 nodules showed resolution or shrinkage, and 41 showed growth of 2 mm or more in diameter. The time to 2-mm nodule-growth curves calculated by Kaplan-Meier methods indicated that the 2-year and 5-year cumulative percentages of growing nodules were 13% and 23% in patients with nonsolid nodules and 38% and 55% in patients with part-solid nodules, respectively. Multivariate analysis disclosed that a large nodule size ( . 10 mm) and history of lung cancer were significant predictive factors of growth in nonsolid nodules.

CONCLUSIONS

An effective schedule for follow-up with CT scanning for subsolid nodules should be developed according to the type of subsolid nodule, initial nodule size, and history of lung cancer.

[Correlation between regional node metastasis and imageological characteristics in non-small cell lung cancer]

非小细胞肺癌（non-small cell lung cancer, NSCLC）局部淋巴结（N）分期是影响患者治疗方案选择的关键因素之一。目前临床所使用的无创和有创性N分期方法均有其局限性。研究发现NSCLC的某些影像学特点可预测淋巴结转移的危险性，包括大小、CT密度和氟代脱氧葡萄糖（fluorodeoxyglucose, FDG）标准化摄取值（standardized uptake value, SUV）等。期待系统性多因素分析，以发现影响肺癌淋巴结转移的关键因素。

Correlation between dynamic CT findings and pathological prognostic factors of small lung adenocarcinoma

PURPOSE

To compare pathological prognostic factors of small lung adenocarcinomas with findings of contrast-enhanced dynamic computed tomography (CT) scans.

MATERIALS AND METHODS

We evaluated 108 patients with lung adenocarcinomas ≤ 30 mm in diameter who underwent dynamic CT scans (80-96 ml of contrast material, 2.5-3 ml/s injection) and tumor resections. Attenuation values of both the early phase (20-36 s after injection) and delayed phase (91-95 s) of enhanced CT minus baseline plain CT attenuation were defined as ΔEarly and ΔDelay. The early enhancement ratio was defined as ΔEarly/ΔDelay×100 (%). We statistically compared the early enhancement ratios between the presence and absence of each pathological finding (lymph node metastasis, lymphatic permeation, vascular invasion, and pleural involvement). Patients were divided into 2 groups based on early enhancement ratios: ratio ≥50% (n = 41) and ratio <50% (n = 67) and we statistically compared these 2 groups.

RESULTS

The early enhancement ratios in the group with lymph node metastasis, lymphatic permeation, and vascular invasion were significantly lower than in the group without these findings (24.9% vs 48.6%; P < 0.001, 30.0% vs 47.5%; P = 0.002, and 26.5% vs 47.0%; P = 0.002, respectively). Lymph node metastasis, lymphatic permeation, and vascular invasion were significantly more frequent in tumors with a ratio <50% than in tumors with ratio ≥50% (P < 0.001, P = 0.008, and P = 0.005, respectively).

CONCLUSIONS

There was a significant correlation between the early enhancement ratio of enhanced dynamic CT and the pathological prognostic factors in small lung adenocarcinomas.

Simple preoperative computed tomography image analysis shows good predictive performance for pathological vessel invasion in clinical stage IA non-small cell lung cancer

OBJECTIVES

Pathological vessel invasion is a well-known prognostic factor in early-stage, non-small cell lung cancer and preoperative predicting vessel invasion may enable us to improve prognosis by additional interventions. We evaluated the importance of vessel invasion as a prognostic factor in clinical stage IA non-small cell lung cancer and predictive performance of simple diameter-based computed tomography image analysis for vessel invasion.

METHODS

The study design was retrospective, and we reviewed 398 patients who underwent surgical resection of clinical stage IA non-small cell lung cancer from 1999 to 2009. The prognostic factors for recurrence-free survival were examined by univariate and multivariate analyses. Additionally, we analyzed preoperative high-resolution computed tomography images of patients with adenocarcinoma. The greatest diameter of the tumor in the lung window and the length of the consolidation part of L in the mediastinal window were measured. Then the ratio (mediastinal window/lung window) was calculated, and the correlation between the ratio (mediastinal window/lung window) and vessel invasion was analyzed by receiver operating characteristic analysis.

RESULTS

Sixty-eight recurrences occurred. Multivariate analysis revealed that vessel invasion, high preoperative serum carcinoembryonic antigen, and history of other malignancy were independent prognostic factors; their hazard ratios were 2.98, 2.45, and 1.98, respectively. The receiver operating characteristic analysis showed that the area under the curve was 0.75. When we set the cut-off value of the ratio (mediastinal window/lung window) at 0.67, the sensitivity and specificity were 75% and 72%, respectively.

CONCLUSIONS

Vessel invasion had the greatest impact on recurrence in clinical stage IA non-small cell lung cancer. Our simple computed tomography image analysis showed good predictive performance for vessel invasion.

One-dimensional mean computed tomography value evaluation of ground-glass opacity on high-resolution images

Objective

Differentiation of atypical adenomatous hyperplasia (AAH), bronchioloalveolar carcinoma (BAC), and invasive carcinoma on computed tomography (CT) is useful for determining “follow-up or resection” strategies for lesions displaying ground-glass opacity (GGO). The purpose of this study is to evaluate one-dimensional quantitative CT values of GGO on high-resolution CT (HRCT) images using computer-aided diagnosis.

Methods

Between April 2001 and March 2010, a total of 44 nodules in 42 patients with pure or mixed GGOs ≤2 cm were retrospectively evaluated. Maximum diameter and one-dimensional mean CT (m-CT) value of the diameter were measured using a computer graphics support system (HOPE/DrABLE-EX, Fujitsu, Tokyo, Japan) that displays a CT density profile across the tumor.

Results

m-CT values were −682 ± 64 HU (range) for AAH lesions, −544 ± 179 (range) for Type A lesions, −496 ± 147 (range) for Type B lesions, and −371 ± 142 (range) for invasive lesions. AAH lesions had a significantly lower m-CT value than Type B lesions. AAH, Type A, and Type B lesions had significantly lower m-CT values than invasive lesions (p < 0.05). All seven GGO lesions with a maximum diameter ≤1 cm and m-CT value ≤−600 HU were pre-invasive lesions, while 16 of 22 (73 %) cases with maximum diameter >1 cm and m-CT value >−600 HU were invasive lesions.

Conclusion

Observation may be indicated for GGO lesions with a maximum diameter ≤1 cm and m-CT value ≤−600 HU.

Percutaneous computed tomography-guided coaxial core biopsy for small pulmonary lesions with ground-glass attenuation

INTRODUCTION

The aim of this study was to investigate the diagnostic value of percutaneous computed tomography (CT)-guided coaxial transthoracic needle biopsy (TNB) for small pulmonary lesions (≤ 3 cm) with persistent ground-glass opacity (GGO).

METHODS

From January 2004 to February 2010, consecutive patients with persistent small GGO lesions (≤ 3 cm) who underwent CT-guided TNB were analyzed. The pathologic results of CT-guided TNB were compared with final diagnoses, and the GGO percentage on CT was correlated with the stromal invasion in surgical pathology.

RESULTS

We performed CT-guided TNB on 1612 patients during the study period. Among them, 55 patients had persistent small GGO lesions (size range 0.5-3.0 cm; 1.72 ± 0.73 cm), 47 were diagnosed with lung adenocarcinomas, and 8 with benign nonspecific lesions. Minor procedure-related complications occurred in 26 patients (47.3%) with small pneumothorax and 11 patients (20.0%) with self-limited mild hemoptysis. The final diagnoses of the 43 patients receiving lobectomy were invasive adenocarcinoma (n = 23), pure bronchioloalveolar carcinoma (n = 19), and mucosa-associated lymphoid tissue lymphoma (n = 1). The diagnostic accuracy was 93.0% (40/43) using CT-guided TNB. Pure GGO lesions had a higher incidence of pure bronchioloalveolar carcinoma than GGO-dominant lesions (70.0% versus 21.7%; p = 0.004). Compared with surgical pathology, stromal invasion was underestimated in 43.5% (10/23) of the TNB specimens, especially in pure GGO lesions (83%, 5/6). In logistic regression analysis, the GGO percentage correlated inversely with stromal tumor invasion (p = 0.0028).

CONCLUSIONS

CT-guided coaxial TNB is a safe and useful method for diagnosing small (≤ 3 cm) persistent GGO lesions. Stromal invasion may be underestimated by TNB in GGO lesions.

Approach to the ground-glass nodule

The detection of ground-glass opacity (GGO) is increasingly common. Sufficient data have been accumulated to formulate recommendations for observation, intervention, and treatment modalities. However, an understanding of many nuances and uncertainties in the available data is needed to avoid making management errors. This article discusses the range of possible entities, risk factors and characteristics that help make a presumptive clinical diagnosis, how often and for how long these should be followed when and how a biopsy should be done, how these lesions should be treated, and how multifocal GGOs should be approached.

Diffusion-weighted magnetic resonance imaging in differentiating the invasiveness of small lung adenocarcinoma

BACKGROUND

Magnetic resonance imaging (MRI) with several sequences may provide a valuable additional modality for evaluating the grade of invasiveness lesions. Diffusion-weighted magnetic resonance imaging (DWI) represents the biological characteristics of tissues.

PURPOSE

To retrospectively evaluate the usefulness of DWI for evaluating the invasiveness of small lung adenocarcinomas.

MATERIAL AND METHODS

From May 2005 to June 2008, 46 patients with lung adenocarcinomas measuring 2 cm or less across the greatest dimension underwent a preoperative MRI study followed by surgery at the Gunma Prefectural Cancer Center. Fourteen of the tumors were bronchioloalveolar carcinomas (so-called Noguchi's type A+B group), 26 were adenocarcinomas with mixed subtypes (type C group) and six were other histological subtypes of adenocarcinomas (type D+E+F group). The mean signal intensities of a lesion (DWI) and the spinal cord (SC) were analyzed in the region of interests (ROIs), and the mean DWI/SC ratio was then calculated with the value of DWI divided by the value of SC.

RESULTS

The calculated mean DWI/SC ratio for the lesions were as follows: 0.448±0.261 (mean±standard deviation [SD]) for type A+B group, 0.963±0.465 for type C group, and 0.816±0.291 for type D+E+F group. The mean DWI/SC ratio of type A+B group was significantly lower than that for the type C (P = 0.0005) or type D+E+F groups (P = 0.0117).

CONCLUSION

DWI may thus provide useful supplementary information before determining the surgical strategy, including a limited resection.

Accuracy of CT parameters for assessment of tumour size and aggressiveness in lung adenocarcinoma with bronchoalveolar elements

Accurate determination of tumour size in lung adenocarcinoma with bronchoalveolar features (BAC) is important for the determination of TNM (tumour, nodes, metastasis) scores used in staging, prognosis and therapy response assessment. However, tumour sizes derived using lung window (LW) CT or soft-tissue/mediastinal window (MW) CT often give different results. This study examines which measurement correlates best with actual tumour size and which best identifies advanced disease. This retrospective study included 43 BAC patients who underwent surgical resection with mediastinal lymphadenectomy <4 weeks post CT scan. The largest unidimensional tumour diameter on each CT window was compared with actual histopathological tumour size (HP). LW, MW and HP size measurements and a recently described CT parameter - the modified tumour shadow disappearance rate (mTDR) = (1 - [MW/LW]) - were then used to determine which parameter best discriminated between the presence or absence of advanced disease. There was no difference between HP and LW sizes, but MW significantly underestimated HP size (p<0.0001). Unlike MW (p = 0.01) and mTDR (p = 0.001), neither HP (p = 0.14) nor LW (p = 0.10) distinguished between patients with or without advanced disease. On receiver operating characteristic (ROC) analysis at a cut-off of ≤0.13, the sensitivity and specificity of mTDR for detecting advanced disease were 69% and 89%, respectively. In patients with tumours ≤3 cm, only mTDR remained a significant predictor of advanced disease (p = 0.017), with best cut-off at ≤0.20, giving a sensitivity and specificity of 71% and 94%, respectively. MW better predicts advanced disease than LW and might also need to be recorded for RECIST (response evaluation criteria in solid tumours) assessment for T staging of BAC; however, mTDR appears to be an even better predictor and should also be used.

Comparison of thin-section CT and pathological findings in small solid-density type pulmonary adenocarcinoma: prognostic factors from CT findings

OBJECTIVE

We divided pulmonary adenocarcinoma of ≤ 20 mm into air-containing and solid-density types based on a percentage reduction of the maximum tumor diameter in the mediastinal window image compared to the area in the lung window image on thin-section (TS) CT of ≥ 50% (air-containing type) and <50% (solid-density type). No relapse occurred in patients with air-containing type. The prognosis of solid-density type may be poor even when the tumor size is 20mm or smaller. We investigated whether CT findings for these tumors could serve as prognostic factors.

METHODS

The subjects were 105 patients with solid-density type pulmonary adenocarcinoma that was identified on TSCT and found to have a diameter of 20mm or smaller after surgical resection during the period from April 1997 to November 2004. Notches, air bronchogram, pleural retraction, spiculation, venous involvement, and ground glass opacity were examined on TSCT, and their associations with pathological findings (i.e., pleural invasion, lymphatic permeation, vascular invasion, lymph node metastasis, and Noguchi's classification) and relapse were investigated using chi-square test and Cox proportional hazards model.

RESULTS

The incidence of relapse was significantly higher in cases with notches. The incidence of notches increased with tumor growth and notches were frequent in Noguchi type D tumors, reflecting poorly differentiated adenocarcinoma. Lymphatic permeation and type D cases were independent factors associated with a poor prognosis using Cox proportional hazards model.

CONCLUSIONS

TSCT findings may be useful for prediction of the prognosis of solid-density type pulmonary adenocarcinoma.

Volumetric measurement pulmonary ground-glass opacity nodules with multi-detector CT: effect of various tube current on measurement accuracy--a chest CT phantom study

RATIONALE AND OBJECTIVES

The purpose of this study was to evaluate the effect of various tube currents on the accuracy of volumetric measurements of ground-glass opacity (GGO) nodules using a chest phantom.

MATERIALS AND METHODS

A chest phantom containing 13 artificial GGO nodules with known volumes was scanned using a 64-slice computed tomographic scanner at different tube currents (30, 60, 90, 120, 150, 180, and 210 mA). Volumetric measurements were performed using software. The relative percentage error and the absolute percentage error between the volume measures on computed tomography and the reference-standard volumes were calculated. Correlations between the mean absolute percentage error and the mean attenuation of nodules and between the ratio of solid component and the mean attenuation of nodules were analyzed.

RESULTS

The relative percentage errors showed that there was substantial underestimation of nodule volumes at 30, 60, and 90 mA and substantial overestimation of volumes at 120, 150, 180, and 210 mA, but there was no statistically significant difference in absolute percentage errors (P = .876). Pearson's correlation coefficient of the mean absolute percentage errors of nodules on volumetric measurement versus the mean attenuation value of nodules showed a negative correlation, and the ratio of solid component to whole nodule versus the mean attenuation of nodules showed a positive correlation.

CONCLUSION

Volume measurement is a promising method for the quantification of GGO nodule volume. It is important to know that different tube currents can affect the accuracy of volumetric measurements.

Magnetic resonance imaging in peripheral lung adenocarcinoma: correlation with histopathologic features

OBJECTIVE

Magnetic resonance imaging (MRI) with various technologic advancements has generally been used to elevate the accuracy of diagnosis for several malignant tumors. This study retrospectively evaluated the efficacy of newer MRI techniques for differentiating among the different types of invasiveness in lung adenocarcinoma by comparing the MRI findings with the pathologic findings.

MATERIALS AND METHODS

From May 2005 to April 2007, 46 patients with lung adenocarcinoma measuring 3 cm or less across the greatest dimension underwent a surgical operation including preoperative MRI study in this hospital. The MR imaging protocol included 3 pulse sequences: (1) respiratory-triggered T2-weighted short TI inversion recovery; (2) respiratory-triggered high b-value diffusion-weighted imaging (DWI); (3) gadolinium-enhanced dynamic MRI studies.

RESULTS

Of all the tumors, 13 were bronchioloalveolar carcinoma (BAC), 24 were adenocarcinomas with mixed subtypes (advanced BAC), and 9 were other histologic subtypes (non-BAC). Both the moderate and strong signal intensity on DWI was significantly greater in the advanced BAC (79.2%) and the non-BAC (88.9%) than in the BAC (38.5%). In the dynamic study, a strong enhancement on the time-intensity curve was significantly greater in the advanced BAC (95.2%) and the non-BAC (87.5%) than in the BAC (25%). When the lesions demonstrated a strong enhancement in dynamic study or showed strong signal intensity on DWI, they were judged to be positive. Sensitivity, specificity, and accuracy were 97%, 76.9%, and 91.3%, respectively.

CONCLUSIONS

DWI could therefore be a useful diagnostic modality for differentiating the subtypes of lung adenocarcinomas, and the MRI finding may thus provide useful supplementary information before surgery comprising limited resections.

Computer-aided diagnosis of lung cancer: definition and detection of ground-glass opacity type of nodules by high-resolution computed tomography

PURPOSE

The ground-glass opacity (GGO) of lung cancer is identified only subjectively on computed tomography (CT) images as no quantitative characteristic has been defined for GGOs. We sought to define GGOs quantitatively and to differentiate between GGOs and solid-type lung cancers semiautomatically with a computer-aided diagnosis (CAD).

METHODS AND MATERIALS

High-resolution CT images of 100 pulmonary nodules (all peripheral lung cancers) were collected from our clinical records. Two radiologists traced the contours of nodules and distinguished GGOs from solid areas. The CT attenuation value of each area was measured. Differentiation between cancer types was assessed by a receiver-operating characteristic (ROC) analysis.

RESULTS

The mean CT attenuation of the GGO areas was -618.4 +/- 212.2 HU, whereas that of solid areas was -68.1 +/- 230.3 HU. CAD differentiated between solidand GGO-type lung cancers with a sensitivity of 86.0% and specificity of 96.5% when the threshold value was -370 HU. Four nodules of mixed GGOs were incorrectly classified as the solid type. CAD detected 96.3% of GGO areas when the threshold between GGO and solid areas was 194 HU.

CONCLUSION

Objective definition of GGO area by CT attenuation is feasible. This method is useful for semiautomatic differentiation between GGOs and solid types of lung cancer.

Evaluation of lesions corresponding to ground-glass opacities that were resected after computed tomography follow-up examination

BACKGROUND

Ground-glass opacity (GGO), which is closely related with bronchioloalveolar carcinoma (BAC), is being detected more frequently. BAC is considered to be a relatively less aggressive tumor, and immediate resection at the time of detection might not be necessary. Therefore, when GGO is detected, a CT follow-up examination is often performed. If growth is detected during the follow-up CT examination, resection is usually considered. However, the possible treatment delay caused by the scheduling of a CT follow-up examination is an issue that must be clarified. Since the cancer might progress during the follow-up period, such follow-up periods might have a negative influence on the patient's prognosis. This study attempted to clarify whether CT follow-up causes treatment delay.

METHODS

A total of 113 lung cancer patients with pure or mixed GGO findings who underwent a resection after a CT follow-up examination between 1999 and 2005 were retrospectively examined. The CT findings at the initial detection, the changes in the CT findings during the CT follow-up period, the histology, the pathological stage and the outcomes after resection were reviewed and evaluated.

RESULTS

The CT finding at the time of the initial detection showed pure GGO in 63 patients and mixed GGO in 50 patients. Histology revealed that adenocarcinoma was found in all 113 patients; squamous cell carcinoma was not found in any of the patients. One-hundred twelve patients were diagnosed as having Stage IA, and a singe patient with visceral pleura invasion was diagnosed as having Stage IB. Complete resections were performed in all the patients. The median postoperative follow-up period was 45.0 months. No recurrences or deaths were observed during the study period.

CONCLUSIONS

No treatment delays or negative influences on patient outcome resulted from the CT follow-up period. A future prospective study should be conducted to establish the optimal CT follow-up program.

Estimation of ground-glass opacity measurement in CT lung images

We propose to measure quantitatively the opacity property of each pixel in a ground-glass opacity tumor from CT images. Our method results in an opacity map in which each pixel takes opacity value of [0-1]. Given a CT image, our method accomplishes the estimation by constructing a graph Laplacian matrix and solving a linear equations system, with assistance from some manually drawn scribbles for which the opacity values are easy to determine manually. Our method resists noise and is capable of eliminating the negative influence of vessels and other lung parenchyma. Experiments on 40 selected CT slices of 11 patients demonstrate the effectiveness of this technique. The opacity map produced by our method is invaluable in practice. From this map, many features can be extracted to describe the spatial distribution pattern of opacity and used in a computer-aided diagnosis system.

Pulmonary adenocarcinomas with ground-glass attenuation on thin-section CT: Quantification by three-dimensional image analyzing method

PURPOSE

The purpose of this study was to evaluate software designed to calculate whole tumor volumes and the ratio of the solid component to whole volume (%solid) in pulmonary nodules with ground-glass opacity in three dimensions.

METHODS

The study included 49 patients with histologically diagnosed adenocarcinomas smaller than 2 cm in diameter. The %solid was calculated both automatically using new software, and by manual measurement of the following four parameters by two observers: the ratio of the largest diameter (a) and the area (b) at the mediastinal window to those at the lung window, and the ratio of the largest diameter (c) and the area (d) of the solid component to those of the ground-glass component at the lung window. Agreement of intra- and inter-observer data by both Spearman's rank correlation test and Bland-Altman's method, and a comparison by Spearman's rank correlation test of the %solid in both Noguchi sub-classifications and vessel invasion in histologic specimens, between the software and manual methods, were assessed.

RESULTS

Of the 49 nodules, 48 were successfully measured and assessed. The agreement of the observers with the software was better (Bland-Altman's method; mean difference, -0.3%; 95% limits of agreement, -3.1 to 2.5%) than with the manual measurements (a: 5.3%, -17.6 to 28.3%; b: 8.3%, -10.6 to 26.9%; c: 10.7%, -17.6 to 39%; d: 6.4%, -22 to 34.8%). The correlation between %solid and the histological group was worse with the software (Spearman's rank correlation test; r=0.487, p<0.001) than with the manual method (a, r=0.534; b, r=0.557; c, r=0.552; d, r=0.545).

CONCLUSION

Although the software requires improvement in the calculation of %solid with volumetric analysis, this is a reproducible and promising quantitative method for determining the grades of malignancy of small lung cancers.