Ground-glass Opacity Percentage Research Articles

Quantification of preexisting lung ground glass opacities on CT for predicting checkpoint inhibitor pneumonitis in advanced non-small cell lung cancer patients

BackgroundImmune checkpoint inhibitors (ICIs) can lead to life-threatening pneumonitis, and pre-existing interstitial lung abnormalities (ILAs) are a risk factor for checkpoint inhibitor pneumonitis (CIP). However, the subjective assessment of ILA and the lack of standardized methods restrict its clinical utility as a predictive factor. This study aims to identify non-small cell lung cancer (NSCLC) patients at high risk of CIP using quantitative imaging.MethodsThis cohort study involved 206 cases in the training set and 111 cases in the validation set. It included locally advanced or metastatic NSCLC patients who underwent ICI therapy. A deep learning algorithm labeled the interstitial lesions and computed their volume. Two predictive models were developed to predict the probability of grade ≥ 2 CIP or severe CIP (grade ≥ 3). Cox proportional hazard models were employed to analyze predictors of progression-free survival (PFS).ResultsIn a training cohort of 206 patients, 21.4% experienced CIP. Two models were developed to predict the probability of CIP based on different predictors. Model 1 utilized age, histology, and preexisting ground glass opacity (GGO) percentage of the whole lung to predict grade ≥ 2 CIP, while Model 2 used histology and GGO percentage in the right lower lung to predict grade ≥ 3 CIP. These models were validated, and their accuracy was assessed. In another exploratory analysis, the presence of GGOs involving more than one lobe on pretreatment CT scans was identified as a risk factor for progression-free survival.ConclusionsThe assessment of GGO volume and distribution on pre-treatment CT scans could assist in monitoring and manage the risk of CIP in NSCLC patients receiving ICI therapy.Clinical relevance statementThis study’s quantitative imaging and computational analysis can help identify NSCLC patients at high risk of CIP, allowing for better risk management and potentially improved outcomes in those receivingICI treatment.

Radiomics for the Prediction of Response to Antifibrotic Treatment in Patients with Idiopathic Pulmonary Fibrosis: A Pilot Study.

Antifibrotic therapy has changed the treatment paradigm for idiopathic pulmonary fibrosis (IPF); however, a subset of patients still experienced rapid disease progression despite treatment. This study aimed to determine whether CT-based radiomic features can predict therapeutic response to antifibrotic agents. In this retrospective study, 35 patients with IPF on antifibrotic treatment enrolled from two centers were divided into training (n = 26) and external validation (n = 9) sets. Clinical and pulmonary function data were collected. The patients were categorized into stable disease (SD) and progressive disease (PD) groups based on functional or radiologic criteria. From pretreatment non-enhanced high-resolution CT (HRCT) images, twenty-six radiomic features were extracted through whole-lung texture analysis, and six parenchymal patterns were quantified using dedicated imaging platforms. The predictive factors for PD were determined via univariate and multivariate logistic regression analyses. In the training set (SD/PD: 12/14), univariate analysis identified eight radiomic features and ground-glass opacity percentage (GGO%) as potential predicators of PD. However, multivariate analysis found that the single independent predictor was the sum entropy (accuracy, 80.77%; AUC, 0.75). The combined sum entropy-GGO% model improved the predictive performance in the training set (accuracy, 88.46%; AUC, 0.77). The overall accuracy of the combined model in the validation set (SD/PD: 7/2) was 66.67%. Our preliminary results demonstrated that radiomic features based on pretreatment HRCT could predict the response of patients with IPF to antifibrotic treatment.

Development of a Machine Learning-Assisted Model for the Early Detection of Severe COVID-19 Cases Combining Blood Test and Quantitative Computed Tomography Parameters

<sec> <title>Purpose:</title> This study aimed to identify severe Coronavirus Disease 2019 (COVID-19) cases combining blood test results and imaging parameters based on a machine learning classifier at the initial admission. </sec> <sec> <title>Materials and methods:</title> Ninety-five non-severe and 22 severe laboratory-confirmed COVID-19 cases treated between January 23, 2020 and March 25, 2020 were examined in this retrospective trial. Blood test results and chest computed tomography (CT) images were obtained at the initial admission. The lesions on CT images were segmented using an artificial intelligent (AI) tool. Then, quantitative CT (QCT) parameters, including the volume, percentage, ground glass opacity (GGO) percentage and heterogeneity of the lesions were calculated. Correlations of blood test results and QCT parameters were analyzed by the Pearson test first. Then, discriminative features for detecting severe cases were selected by both the independent samples t test and least absolute shrinkage and selection operator (LASSO) regression. Next, support vector machine (SVM), Gaussian naïve Bayes (GNB), Knearest neighbor (KNN), decision tree (DT), random forest (RF) and multi-layer perceptron-neural net (MLP-NN) algorithms were used as classifiers, and their accuracies were assessed by 10-fold-cross-validation. </sec> <sec> <title>Results:</title> Blood test indexes and CT parameters were moderately to medially correlated. Of all selected features, lesion percentage contributed mostly to the classification of the two groups, followed by lesion volume, patient age, lymphocyte count, neutrophil count, GGO percentage and tumor heterogeneity. RF-assisted identification had the highest accuracy of 91.38%, followed by GNB (87.83%), KNN (87.93%), SVM (86.21%), MLP-NN (85.34%) and DT (84.48%). </sec> <sec> <title>Conclusions:</title> The RF-assisted model combining blood test and QCT parameters is helpful in the identification of severe COVID-19 cases. </sec>

Quantitative CT for detecting COVID\u201119 pneumonia in suspected cases

BackgroundCorona Virus Disease 2019 (COVID-19) is currently a worldwide pandemic and has a huge impact on public health and socio-economic development. The purpose of this study is to explore the diagnostic value of the quantitative computed tomography (CT) method by using different threshold segmentation techniques to distinguish between patients with or without COVID-19 pneumonia.MethodsA total of 47 patients with suspected COVID-19 were retrospectively analyzed, including nine patients with positive real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR) test (confirmed case group) and 38 patients with negative RT-PCR test (excluded case group). An improved 3D convolutional neural network (VB-Net) was used to automatically extract lung lesions. Eight different threshold segmentation methods were used to define the ground glass opacity (GGO) and consolidation. The receiver operating characteristic (ROC) curves were used to compare the performance of various parameters with different thresholds for diagnosing COVID-19 pneumonia.ResultsThe volume of GGO (VOGGO) and GGO percentage in the whole lung (GGOPITWL) were the most effective values for diagnosing COVID-19 at a threshold of − 300 HU, with areas under the curve (AUCs) of 0.769 and 0.769, sensitivity of 66.67 and 66.67%, specificity of 94.74 and 86.84%. Compared with VOGGO or GGOPITWL at a threshold of − 300 Hounsfield units (HU), the consolidation percentage in the whole lung (CPITWL) with thresholds at − 400 HU, − 350 HU, and − 250 HU were statistically different. There were statistical differences in the infection volume and percentage of the whole lung, right lung, and lobes between the two groups. VOGGO, GGOPITWL, and volume of consolidation (VOC) were also statistically different at the threshold of − 300 HU.ConclusionsQuantitative CT provides an image quantification method for the auxiliary diagnosis of COVID-19 and is expected to assist in confirming patients with COVID-19 pneumonia in suspected cases.

Pulmonary embolism in COVID-19: Ancillary findings on chest CT angiography.

Pulmonary embolism in COVID-19: Ancillary findings on chest CT angiography.

Temporal Changes of CT Findings in 90 Patients with COVID-19 Pneumonia: A Longitudinal Study.

BackgroundCT may play a central role in the diagnosis and management of COVID-19 pneumonia.PurposeTo perform a longitudinal study to analyze the serial CT findings over time in patients with COVID-19 pneumonia.Materials and MethodsDuring January 16 to February 17, 2020, 90 patients (male:female, 33:57; mean age, 45 years) with COVID-19 pneumonia were prospectively enrolled and followed up until they were discharged or died, or until the end of the study. A total of 366 CT scans were acquired and reviewed by 2 groups of radiologists for the patterns and distribution of lung abnormalities, total CT scores and number of zones involved. Those features were analyzed for temporal change.ResultsCT scores and number of zones involved progressed rapidly, peaked during illness days 6-11 (median: 5 and 5), and followed by persistence of high levels. The predominant pattern of abnormalities after symptom onset was ground-glass opacity (35/78 [45%] to 49/79 [62%] in different periods). The percentage of mixed pattern peaked (30/78 [38%]) on illness days 12-17, and became the second most predominant pattern thereafter. Pure ground-glass opacity was the most prevalent sub-type of ground-glass opacity after symptom onset (20/50 [40%] to 20/28 [71%]). The percentage of ground-glass opacity with irregular linear opacity peaked on illness days 6-11 (14/50 [28%)]) and became the second most prevalent subtype thereafter. The distribution of lesions was predominantly bilateral and subpleural. 66/70 (94%) patients discharged had residual disease on final CT scans (median CT scores and zones involved: 4 and 4), with ground-glass opacity (42/70 [60%]) and pure ground-glass opacity (31/42 [74%]) the most common pattern and subtype.ConclusionThe extent of lung abnormalities on CT peaked during illness days 6-11. The temporal changes of the diverse CT manifestations followed a specific pattern, which might indicate the progression and recovery of the illness.

Stepwise flowchart for decision making on sublobar resection through the estimation of spread through air space in early stage lung cancer1

ObjectivesThe sensitivity for tumor spread through air space (STAS), an independent risk factor for locoregional recurrence after sublobar resection for lung cancer, has been relatively low in frozen sections. We aimed to determine predictors with high negative predictive value for the presence of STAS and to provide the flowchart in combination with these predictors for the decision-making for sublobar resection. Materials and MethodsBetween July 2015 and December 2017, 387 patients who underwent surgery for non-small cell lung cancer (NSCLC) with pathologic findings of the total masses measuring ≤ 2 cm were enrolled. The lesions were divided into two groups according to presence of STAS. We compared the preoperative characteristics, operative data, and developed a flowchart for STAS prediction using receiver operator characteristic curve analysis and multivariable logistic regression. ResultsThe STAS-positive group (N = 111) had a significantly higher preoperative tumor size (1.70 [1.5] vs 1.50 [0.69], p < 0.001) and standardized uptake value tumor-to-liver (SUV T/L) ratio (1.40 [1.60] vs 0.60 [1.10], p < 0.001) and a significantly lower two-dimensional ground-glass opacity (GGO) percentage (35.86 [61.00] vs 78.14 [39.00], p < 0.001). Meanwhile, the STAS-negative group (N = 286) had higher lepidic predominance (41.6% vs. 1.8%, p < 0.001). We developed a flowchart for predicting STAS in combination with two-dimensional GGO percentage on computed tomography (CT), SUV T/L ratio on positron-emission CT, and lepidic predominant pattern. The sensitivity, specificity, and negative predictive value for STAS positivity were 79.3%, 68.5%, and 89.5%, respectively. ConclusionsThe stepwise flowchart using two-dimensional GGO percentage on CT, maximum SUV, and lepidic predominance might be helpful in selecting patients with early NSCLC for sublobar resection.

Morphological classification of pre-invasive lesions and early-stage lung adenocarcinoma based on CT images

To retrospectively analyze the computed tomography (CT) features in patients with pre-invasive lesions and early-stage lung adenocarcinoma and to explore the correlation between tumor morphological changes and pathological diagnoses. CT morphological characteristics in 2106 patients with pre-invasive (stage 0) and early-stage (stage I) lung adenocarcinoma were analyzed; lesions were confirmed by surgical pathology. Based on the morphological characteristics, the lesions were divided into eight types: I (cotton ball, ground-glass nodules), II (solid fill), III (granular), IV (dendriform), V (bubble-like lucencies), VI (alveolate or honeycomb), VII (scar-like), and VIII (notched or umbilication). The different distributions of eight morphological types in pathological types of the lesions and subtypes of invasive adenocarcinoma were analyzed by chi-squared or Fisher's exact test. Correlation between the percentage of ground-glass opacity in the lesions and pathology types were analyzed by two-tailed Pearson's test. A negative correlation was observed between the pathological types and proportion of ground-glass component in the lesions (p < 0.001 and r = - 0.583). Significant differences in morphological characteristics among various pathological types of pre-invasive lesions and early lung adenocarcinomas were observed (p < 0.05). Furthermore, among the different pathological subtypes of stage I invasive adenocarcinoma, the differences in their manifestation as morphological types I, II, III, and VI were statistically significant (p< 0.05). The eight types of morphological classification of pre-invasive lesions and early-stage (stage 0 or stage I) lung adenocarcinoma has different pathological bases, and morphological classification may be useful for the diagnosis and differential diagnosis of lung adenocarcinoma. • CT morphological classification of pre-invasive lesions and lung adenocarcinoma is intuitive. • CT morphological classification characterizes morphological changes of the entire lesion. • Different pathological types of lung adenocarcinoma have different morphological features.

Diagnostic value of 18F-FDG PET/CT for subsolid pulmonary nodules

Objective To determine the value of 18F-FDG PET/CT in the detection of subsolid pulmonary nodules. Methods The 18F-FDG PET/CT imaging data of 44 patients (35 males, 9 females, mean age (68.05±9.89) years) with 49 subsolid pulmonary nodules were retrospectively analyzed. There were 28 pure ground-glass nodules (pGGN) and 21 part-solid nodules (PSN), which were all confirmed by postsurgical pathology or imaging results during follow-up. The lesion size (dmax), ground-glass opacity (GGO) percentage, SUVmax, retention index (RI), and the positive rates on PET images were accessed. The correlation between SUVmax and lesion size and GGO percentage was analyzed by Pearson correlation analysis. The SUVmax between benign and malignant pGGN, and that between malignant pGGN and PSN, were compared using two-sample t test. The diagnostic accuracy was compared using χ2 test. Results (1) Six pGGN were benign while 43 nodules (including 22 pGGN and 21 PSN) were malignant among the 49 nodules. (2) SUVmax was positively correlated with lesion size (r=0.500, P 0.05) between 6 benign pGGN (0.78±0.25, range: 0.50-1.20) and 22 malignant pGGN (0.91±0.34, range: 0.40-1.70); SUVmax of 21 malignant PSN (2.10±1.16, range: 0.60-5.60) was higher than that of 22 malignant pGGN (t=-4.645, P 10%, the accuracy rates for PSN and pGGN were 65.0%(13/20) and 45.8%(11/24), respectively (χ2=1.616, P>0.05). Conclusion 18F-FDG PET/CT shows no clear advantage for diagnosis of pGGN, but is helpful for PSN. Key words: Lung neoplasms; Tomography, emission-computed; Tomography, X-ray computed; Deoxyglucose

Impact of the IASLC/ATS/ERS classification in pN0 pulmonary adenocarcinomas: A study with radiological–pathological comparisons and survival analyses

The aim of this study was: (1) to compare the new pathological findings as detected by the IASLC/ATS/ERS classification with the traditional radiological features in pulmonary pN0 adenocarcinomas, (2) to evaluate their prognostic significance on overall survival (OS).A total of 42 surgically resected pN0 pulmonary adenocarcinomas were analyzed. On CT scans, the following radiological data were recorded: sphericity, predominant margins, cavitation and bronchogram, attenuation and percentage of ground glass opacity (GGO). On pathological examination, tumors were categorized according to the IASLC/ATS/ERS classification; Sica score and grade, pathological stage, tumor major axis, pleural invasion, vascular and lymphatic invasion, peritumoral lymphoid infiltration, and cytological features were also determined. Clinical follow up was available in 37 cases (range 1–117 months).Radiologically, 31 solid and 11 semisolid tumors were found. Morphologically, 2 minimally invasive and 40 invasive adenocarcinomas were diagnosed. In radiological–pathological comparisons, (1) the acinar pattern was higher in tumors with solid attenuation and low GGO (p=0.018); (2) the lepidic pattern was more elevated in tumors with high GGO (p=0.012).In multivariate survival analyses with stage, predominant margins on CT scans (p=0.036) and Sica score (p=0.028) significantly affected OS.This study confirms the validity of the new classification of pulmonary adenocarcinomas in radiological–pathological comparisons and underlines the importance of both radiological and pathological findings in correctly identifying their prognostic features.

Epidermal Growth Factor Receptor Mutation in Lung Adenocarcinomas: Relationship with CT Characteristics and Histologic Subtypes

To retrospectively identify quantitative computed tomographic (CT) features that correlate with epidermal growth factor receptor (EGFR) mutation in surgically resected lung adenocarcinomas stratified by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS) classification in an East Asian cohort of patients known to have a high prevalence of EGFR mutations. An institutional review board approved this study and waived informed consent. In 153 surgically resected lung adenocarcinomas, EGFR mutation was determined by direct DNA sequencing. Histologic subtype was classified according to IASLC/ATS/ERS classification of lung adenocarcinoma. At preoperative chest CT, the percentage of ground-glass opacity (GGO) volume and total tumor volume of each tumor were measured by using a semiautomated algorithm. Distribution of EGFR mutation according to histologic subtype, percentage of GGO volume, and total tumor volume was evaluated by using the Fisher exact test, the Student t test, trend analysis, and multiple logistic regression analysis. Exon 21 missense mutation was more frequent in lepidic predominant adenocarcinomas than in other histologic subtypes (odds ratio, 3.44; 95% confidence interval: 1.53, 7.74; P = .003). GGO volume percentage in tumors with exon 21 missense mutation (61.7% ± 31.9 [standard deviation]) was significantly higher than that in EGFR wild-type tumors (30.0% ± 38.5) (P = .0001) and exon 19-mutated tumors (28.9% ± 37.7) (P = .0006). A significant trend of prevalence of exon 21 missense mutation increasing along with increasing GGO volume (P = .0008) was found. GGO volume percentage in tumors with exon 21 missense mutation was significantly higher than that in tumors with other EGFR mutation status. This can be related to the fact that exon 21 missense mutation was significantly more frequent in lepidic predominant adenocarcinomas, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic predominant invasive adenocarcinoma, according to IASLE/ATS/ERS classification.

Is There a Role for FDG PET in the Management of Lung Cancer Manifesting Predominantly as Ground-Glass Opacity?

The purposes of our study were to evaluate 18F-FDG PET findings of ground-glass opacity (GGO) nodules and to determine the value of FDG PET for the preoperative staging of lung cancer manifesting predominantly as GGO. Eighty-nine patients (46 men and 43 women; mean [±SD] age, 62.4±7.2 years [range, 33-81 years] and 61.7±6.7 years [range, 34-75 years], respectively) with 134 GGO nodules (56 single and 78 multiple) who underwent CT and FDG PET before surgery were included. CT and PET findings were assessed in terms of lesion size, GGO percentage, multiplicity, and maximum standardized uptake value (SUVmax). SUVmax was correlated with lesion size and GGO percentage using linear regression. The SUVmax and hypermetabolism rates of solitary and multiple GGO nodules were compared using the Student t test or Fisher exact test. Lymph node and distant organ metastasis staging by FDG PET were correlated with histopathologic findings. SUVmax was positively correlated with lesion size (mean, 14.5 mm; range, 5-37 mm) (r=0.6705; p<0.0001) and was negatively correlated with GGO percentage (mean, 77%; range, 50-100%) (r=-0.7465; p<0.0001). Solitary nodules showed higher hypermetabolism rates (73% [41/56]) than did multiple nodules (27% [21/78]) (p=0.0001), but SUVmax was not significantly different between solitary and multiple nodules. There was no true-positive interpretation of nodal or distant metastasis from GGO nodules by FDG PET. FDG PET showed no clear advantage for the staging of lung cancer with predominant GGO because of the low incidences of nodal and distant metastasis.

Percutaneous Computed Tomography-Guided Coaxial Core Biopsy for Small Pulmonary Lesions with Ground-Glass Attenuation

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). 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. 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). 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.

Treatment strategy for patients with small peripheral lung lesion(s): intermediate-term results of prospective study

This prospective study was undertaken to establish a novel management algorithm using new indicators to decide the type of lung resection for small peripheral lung lesions. Inclusion criteria were: (1) <or=20mm peripheral lung lesion(s) and (2) absence of significant lymph node swelling on preoperative CT. Along with the conventional criteria, the percentage of ground-glass opacity (GGO) (>or=50% as GGO type and <50% as solid type) on high-resolution CT scan was employed. In accordance with such indicators, a wide wedge resection (WWR), segmentectomy or lobectomy was planned for individual patients. The primary endpoint was to estimate the effectiveness of limited resection in patients with lung cancer by analyzing their locally disease-free survival rates at 5 and 10 years. Of 179 patients enrolled between 1997 and 2002, 90 were male and 89 female. They were divided into 77 GGO types and 102 solid types. During surgery, conversions from limited resections to standard operations were performed on six patients to avoid the risk of local-regional recurrence. Finally, WWR was performed on 73 patients, segmentectomy on 26 and lobectomy on 80, respectively. There were 138 lung cancers and 41 non-cancers. Of 138 cancer patients, 114 patients are alive and 24 died. There were no local-regional recurrences among the 58 cancer patients who underwent limited resection. This intermediate-term outcome suggests that the selection of the type for lung resection using this management algorithm for small peripheral lung lesions was effective for preventing both local-regional recurrences and the excessive resection of normal lung tissue.

Detection of EGFR Gene Mutations Using the Wash Fluid of CT-Guided Biopsy Needle in NSCLC Patients

In this study, we examined whether epidermal growth factor receptor (EGFR) mutations were detectable using a polymerase chain reaction-based assay and wash fluid of computed tomography (CT)-guided lung biopsy needles. DNA was extracted from wash fluid of CT-guided biopsy needles of 53 lung tumors (as diagnosed according to the results of the CT-guided biopsies). EGFR mutations, specifically exon19 deletions and exon21 L858R mutations, were examined using a mutant-enriched polymerase chain reaction assay. We also examined the presence of EGFR mutations in 26 surgically resected tumor specimens and compared the results with those obtained for the corresponding wash fluid samples. The amount of DNA obtained for the wash fluid of the CT-guided biopsy needles ranged from 35 to 2360 ng. There were no significant differences in the amount of extracted DNA according to the tumor characteristics, including tumor size and the percentage of ground glass opacity. Thirty-four of the 53 lung tumor samples were histologically diagnosed as non-small cell lung cancer (NSCLC). Exon19 deletions and exon21 L858R mutations in EGFR were detected in 4 (12%) and 13 (38%) of 34 NSCLC cases, respectively. No EGFR mutations were found in the non-NSCLC cases. The EGFR mutation status in the wash fluid samples was consistent with those obtained for all 26 corresponding surgical specimens. Our results indicate that EGFR mutations can be detected using wash fluid of CT-guided biopsy needles. In this manner, the DNA genotype can be determined even in extremely small clinical specimens using highly sensitive assays.

M01-02: Treatment for the screen-detected lung cancer: characteristics and outcome

Owing to the advent of refined chest CT images with higher resolution and CT screening programs, smaller lung cancers are being discovered in asymptomatic patients. Most of them are more often found on a low-dose CT images, and they tend to have characteristic appearance on high-resolution CT scan as ground glass opacity (GGO), a focal intermediate/mild increase in the CT density. Of course, the screening program is still picking up the more solid tumors with/without lymph node involvement, the percentage of GGO or GGO-like lesions is obviously increased in low-dose CT screening era. These GGO tumors are pathologically characterized by the morphology of non-/minimally invasive form of well-differentiated adenocarcinoma termed as bronchioloalveolar carcinoma (BAC) of the non-mucinous type. The superb prognosis of these GGO-BAC tumors is being recognized in the surgical community. Although the gold standard operation for peripheral lung cancer has been lobectomy with lymph node sampling/dissection, the revision is thought to be necessary, especially for these screen-detected GGO-BAC tumors. The possibility of limited resection such as segmentectomy/wedge resection seems to be realistic. Enough number of institutional reports describing the equivalent surgical outcome by limited resection have been accumulated. Therefore, the randomized phase III trial between lobectomy and limited resection is being planned both in US and Japan in a non-inferiority design setting. The results of these studies might be applied in the management of screen-detected, small-sized tumors in the near future.

末梢小型肺腺癌のGGO面積比率と野口分類 : 縮小手術に対する1考察

腫瘍最大径2cm以下の末梢発生肺腺癌切除141例に対して, HRCT上腫瘍最大割面でのGGO面積比率(G)をG=100%(G100), 50%<G<100%(G75), 0%<G≦50%(G25), G=0%(G0)の4群に分類して, 病理学的所見, 予後に関して検討した.G100は11例で, 全例がNoguchi type AもしくはBであった.G75は29例でリンパ節転移を認めず, 1例にリンパ管侵襲を, 2例に血管侵襲を認めた.G25は55例でリンパ節転移を6例に, リンパ管侵襲を17例に, 血管侵襲を20例に認めた.G0は46例でリンパ節転移を13例に, リンパ管侵襲を14例に, 血管侵襲を25例に認めた.G100, G75は全例無再発生存中.G25, G0の5年生存率はそれぞれ77.3%, 77.6%であった.GGO面積比率は肺腺癌の悪性度と密接な関係があり, 積極的縮小手術の適応基準となる可能性が示唆された.

E-43. Most influential papers in surgery

However, three topics have generated a particularly large amount of interest and resulted in papers which, although may not be definitive, have provided valuable insight into their respective clinical areas. These include: PET scan staging of lung cancer, defining early stage bronchioloalveolar carcinoma (BAC) and multi-modality treatment of superior sulcus tumours. The PLUS group from the Netherlands performed a randomized trial in 188 patients with presumed resectable non small cell lung cancer (NSCLC) [6]. Patients underwent a conventional metastatic work-up either with or without ‘*FDG-PET scanning. The primary endpoint was the number of futile thoracotomies, defined as recurrence or death within one year, benign lesion, pathologic stage IIIA or BIB or exploratory thoracotomy without resection. With the addition of PET scanning, futile thoracotomies declined from 41% to 21% and the percentage of patients upstaged as a result of the pre-operative work-up increased from 12% to 27%. Matsuguma and colleagues correlated the percentage of ground glass opacity (GGO) seen on high resolution CT scan with lymph node metastasis and other potential prognostic factors in 96 patients with stage 1A lung cancer [7]. Tumours showing >50% GGO were all found to be BAC with no lymph node metastasis or lymphatic invasion. These patients were more likely to be non-smoking women and none have recurred. This group may be appropriate to consider for limited resection. A single armed study of concurrent induction chemo-radiotherapy followed by surgical resection was performed in 111 patients with T3 or T4 NO-l superior sulcus NSCLC under the Intergroup Trial mechanism of the U.S. National Cancer Institute [8]. Patients received 2 cycles of cisplatin and etoposide and 45Gy of radiation. 92% had a complete resection with a 2.4% operative mortality and a 25% pathologic complete response rate. The 2 year survival is 55% overall and 70% for those who had a complete resection. All three of these studies should have a major impact on the way we practice thoracic surgical oncology in the future.

High-Resolution CT Features: Prognostic Significance in Peripheral Lung Adenocarcinoma with Bronchioloalveolar Carcinoma Components

Background: Based on Noguchi’s classification, adenocarcinomas with bronchioloalveolar carcinoma (BAC) components have a heterogeneous prognosis. However, until now, the prognostic factors in this tumor category have not been clarified. Objectives: We studied the prognostic significance of high-resolution CT (HRCT) findings in this tumor subtype. Materials and Methods: HRCT findings [lesion size, percentage of ground-glass opacity (GGO) areas in the lesion, presence or absence of lobulation, coarse spiculation, pleural tag, satellite lesion, air bronchogram, and site of the lesion], clinical data (age, gender and surgical method), and pathologic findings (degree of tumor differentiation and presence or absence of nodal metastasis) were analyzed in 52 consecutive patients with adenocarcinoma with BAC components <3 cm (mean, 1.7 cm). The patients included 32 women and 20 men with a mean age of 66 years. The results correlated with survival using univariate and multivariate analysis. The mean follow-up period was 41 months. Results: Nine (17%) of the 52 patients died of lung cancer. In univariate analysis, a significant difference was found for lobulation (p = 0.018), %GGO (p = 0.043), air bronchogram (p = 0.003), site of lesion (p = 0.034), degree of tumor differentiation (p = 0.001), and nodal metastasis (p = 0.040). Multivariate analysis using the 6 factors that were significant in univariate analysis as independent variables revealed that an air bronchogram (p = 0.010) and the degree of tumor differentiation (p = 0.008) were significant independent factors for survival. Conclusion: The presence of an air bronchogram on HRCT may have an independent prognostic significance in lung adenocarcinoma with BAC components.

Prognostic significance of high-resolution CT findings in small peripheral adenocarcinoma of the lung: a retrospective study on 64 patients

Objective: We studied the prognostic importance of high-resolution CT (HRCT) findings in lung adenocarcinomas. Patients and methods: HRCT findings (lesion size, percentage of ground-glass opacity (GGO) areas of lesion, and presence or absence of lobulation, coarse spiculation, air space, pleural tag, and multiplicity of lesion), clinical data (age and surgical method), and pathologic findings (tumor subtypes and presence or absence of nodal metastasis) in 64 consecutive patients with 64 peripheral adenocarcinomas of 20 mm or less (mean, 13 mm), including 36 women and 28 men with a mean age of 64 years were analyzed and correlated with survival of the patients using Kaplan–Meier method and stepwise Cox proportional hazards modeling. Follow-up periods of the patients ranged from 6 to 45 months (mean, 22 months). Tumors were classified into six subtypes (types A–F) according to tumor growth patterns defined by Noguchi et al. Results: Six (9%) of the 64 patients died of lung cancer. In univariate analyses, a significant difference was noted for lesion size ( P=0.043), the percentage of GGO areas ( P=0.005), and tumor subtypes ( P=0.006). Lesion size of <15 mm ( n=35), a lesion with GGO areas of >57% ( n=36), and type A ( n=16) or type B adenocarcinomas ( n=16) indicated a significantly better survival. In multivariate analyses using these three parameters as independent variables, the percentage of GGO areas was the only significant independent factor for survival ( P=0.044, relative risk=0.95). Conclusion: GGO areas measured on HRCT may have an independent prognostic significance of small adenocarcinomas of the lung.