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

Measurement of solid size in early-stage lung adenocarcinoma by virtual 3D thin-section CT applied artificial intelligence

An artificial intelligence (AI) system that reconstructs virtual 3D thin-section CT (TSCT) images from conventional CT images by applying deep learning was developed. The aim of this study was to investigate whether virtual and real TSCT could measure the solid size of early-stage lung adenocarcinoma. The pair of original thin-CT and simulated thick-CT from the training data with TSCT images (thickness, 0.5-1.0 mm) of 2700 pulmonary nodules were used to train the thin-CT generator in the generative adversarial network (GAN) framework and develop a virtual TSCT AI system. For validation, CT images of 93 stage 0-I lung adenocarcinomas were collected, and virtual TSCTs were reconstructed from conventional 5-mm thick-CT images using the AI system. Two radiologists measured and compared the solid size of tumors on conventional CT and virtual and real TSCT. The agreement between the two observers showed an almost perfect agreement on the virtual TSCT for solid size measurements (intraclass correlation coefficient = 0.967, P < 0.001, respectively). The virtual TSCT had a significantly stronger correlation than that of conventional CT (P = 0.003 and P = 0.001, respectively). The degree of agreement between the clinical T stage determined by virtual TSCT and the clinical T stage determined by real TSCT was excellent in both observers (k = 0.882 and k = 0.881, respectively). The AI system developed in this study was able to measure the solid size of early-stage lung adenocarcinoma on virtual TSCT as well as on real TSCT.

Differences in the prognostic implication of ground-glass opacity on CT according to pathological nodal status in lung cancers treated with lobectomy or pneumonectomy

OBJECTIVES

To clarify the prognostic significance of a ground-glass opacity (GGO) component according to T category and pathological nodal status in patients with resectable non-small cell lung cancer (NSCLC).

METHODS

Patients who underwent lobectomy or pneumonectomy for NSCLC between July 2010 and December 2017 were retrospectively included. Patients were divided into GGO and solid groups based on the presence of a GGO component on CT. The effects on survival of interactions between GGO and (a) pathological nodal status (pN) and (b) cT category were evaluated using Cox regression.

RESULTS

Out of 1545 patients, 548 were classified into the GGO group (pN0: 457, pN1/2: 91) and 997 into the solid group (pN0: 660, pN1/2: 337). There were interactions between the presence of GGO and pathological nodal status on 5-year disease-free survival (DFS; p = .006) and 5-year overall survival (OS; p = .02). In multivariate analysis, better survival of patients in the GGO group than in the solid group was observed only in pN0 category (adjusted hazard ratio [HR], 0.63 for 5-year DFS; p = .002 and 0.47 for 5-year OS; p = .002), but not in pN1/2 category. Moreover, in those with pN0 category, the favorable prognostic value of GGO was limited to those with cT1 category for 5-year DFS (adjusted HR, 0.48; p < .001) and those with cT1/2 category for 5-year OS (adjusted HR, 0.37; p = .002).

CONCLUSIONS

GGO was a favorable predictor of survival only in patients with pN0 category, showing an advantage in DFS for those with cT1 category and OS for those with cT1/2 category.

KEY POINTS

• The presence of ground-glass opacity was associated with a favorable prognosis, only in pathological node-negative patients (5-year disease-free survival, p = .002; 5-year overall survival, p = .002). • Within pathological node-negative patients, the effect of ground-glass opacity on 5-year disease-free survival was valid in patients with cT1 category (adjusted hazard ratio, 0.48; 95% confidence interval, 0.32-0.72; p < .001), but not in patients with cT2 or above category. • Within pathological node-negative patients, the effect of ground-glass opacity on 5-year overall survival was valid in patients with cT1/2 category (adjusted hazard ratio, 0.37; 95% confidence interval, 0.20-0.68; p = .002), but not in patients with cT3/4 category.

Prognostic performance in lung cancer according to tumor size: Comparison of axial, multiplanar, and 3-dimensional CT measurement to pathological size

PURPOSE

This study aimed to compare the prognostic performance of clinical T staging based on axial, multiplanar, and 3-dimensional measurement on CT with that of pathological T staging in patients with non-small cell lung cancer.

METHOD

Patients with surgically resected lung cancer without pathological node metastasis between June 2010 and December 2017 were retrospectively included. Clinical T stages were determined based on the maximal tumor size on axial, multiplanar (axial, coronal, and sagittal) images and 3-dimensional tumor mask. The prognostic performances of clinical and pathological T staging for disease-free survival (DFS) were compared using the concordance indices (C-indices).

RESULTS

A total of 544 patients (64.7 ± 9.7 years, 352 men) were included; 160 patients (29.4%) experienced events including 29 (5.3%) who expired. The median DFS was 44.1 months. The mean tumor size on axial, multiplanar images, 3-dimensional tumor mask, and pathology was 30.8 ± 17.3, 33.9 ± 19.4, 39.2 ± 21.4, and 33.4 ± 18.0 mm, respectively. Clinical staging based on multiplanar measurement showed a higher agreement (67.5% [367/544]) with pathological staging than axial (60.5% [329/544]) and 3-dimensional measurement (50.9% [277/544]) based staging did (p = .0005 and <.0001, respectively). The adjusted C-indices of axial, multiplanar, 3-dimensional, and pathological tumor stages were 0.66 (95% confidence interval [CI]: 0.66-0.67), 0.66 (95% CI: 0.66-0.66), 0.67 (95% CI: 0.67-0.67), and 0.67 (95% CI: 0.66-0.67), respectively (p > .05).

CONCLUSIONS

The prognostic performances of tumor staging according to size measurement methods were not significantly different. Multiplanar measurement may be preferable for clinical staging considering its highest agreement with pathological staging.

Tumor size in patients with severe pulmonary emphysema might be underestimated on preoperative CT

OBJECTIVES

To evaluate the effect of emphysema on tumor diameter measured on preoperative computed tomography (CT) images versus pathological specimens.

MATERIALS AND METHODS

We investigated patients who underwent primary lung cancer surgery: 55 patients (57 tumors) with severe emphysema and 57 patients (57 tumors) without emphysema. The tumor diameters measured in the postoperative pathological specimens were compared with those measured on the axial CT images and on multiplanar reconstruction (MPR) CT images by two independent radiologists; a subgroup analysis according to tumor size was also performed. A paired or unpaired t test was performed, depending on the tested subjects.

RESULTS

In the emphysema group, the mean axial CT diameter was significantly smaller than the mean pathological diameter (p = 0.025/0.001 for reader 1/2), whereas in the non-emphysema group, the mean axial CT diameter was not significantly different from the pathological one for both readers. The difference between CT axial diameter and pathological diameter (= CT diameter - pathological diameter) was significantly smaller (i.e., had a stronger tendency toward underestimation on radiological measurements) in the emphysema group compared with the non-emphysema group (p = 0.014/0.008 for reader 1/2), and the difference was significantly smaller in tumors sized > 30 mm than tumors sized ≤ 20 mm in both groups.

CONCLUSIONS

Tumor size is significantly smaller on preoperative CT in patients with severe emphysema compared to patients without emphysema, especially in the case of large tumors. MPR measurement using the widest of three dimensions should be used to select T-stage for patients with severe emphysema.

KEY POINTS

• The presence of emphysema affects the accuracy of tumor size measurements on CT. • Compared to patients without emphysema, the tumor size in severe emphysema patients tends to be measured smaller in preoperative CT than the pathological specimen. • This trend is more evident when large tumors are measured on axial CT images alone.

Benefits of the multiplanar and volumetric analyses of pancreatic cancer using computed tomography

Although pancreatic cancer tumors are irregularly shaped in terms of their three-dimensional (3D) structure, when T staging by imaging results, generally only the axial plane is used to measure the largest tumor diameter. We investigated the size of pancreatic cancer tumors using multi-plane and 3D reconstructed computed tomography (CT) images and investigated their clinical usefulness. Patients who underwent surgery for pancreatic adenocarcinoma were included. We measured the largest diameter of each pancreatic tumor in the axial, coronal, and sagittal planes of CT images. In addition, maximal diameter and cancer volume were measured from 3D images that were constructed using a semi-automated software system. Final data were compared with pathologic examination and the effect of each value on prognosis was analyzed. A total of 183 patients were analyzed. The maximal diameters measured on the axial, coronal, and sagittal planes were 2.9 ± 1.1, 3.2 ± 0.9, and 3.2 ± 1.0 cm, respectively, which were significantly smaller than pathologic results (3.4 ± 1.4 cm, all p<0.05 by paired t-test). The longest diameter among them (3.4 ± 1.1 cm) was nearly similar to the pathologic diameter. Cancer volume measured on 3D images demonstrated a higher area under the receptor operating characteristic curve [0.714, (95% confidence interval: 0.640–0.788)] for predicting early death compared to any unidimensional CT diameters measured. The longest pancreatic tumor diameter measured on multiplanar CT images was most accurate when compared to its corresponding pathologic diameter. Tumor volume had a stronger correlation with overall survival than tumor diameter.

CT Characteristics for Predicting Invasiveness in Pulmonary Pure Ground-Glass Nodules

OBJECTIVE. The objective of our study was to investigate the differences in the CT features of atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA) manifesting as a pure ground-glass nodule (pGGN) with the aim of determining parameters predictive of invasiveness. MATERIALS AND METHODS. A total of 161 patients with 172 pGGNs (14 AAHs, 59 AISs, 68 MIAs, and 31 IAs) were retrospectively enrolled. The following CT features of each histopathologic subtype of nodule were analyzed and compared: lesion location, diameter, area, shape, attenuation, uniformity of density, margin, nodule-lung interface, and internal and surrounding changes. RESULTS. ROC curves revealed that nodule diameter and area (cutoff value, 10.5 mm and 86.5 mm²; sensitivity, 87.1% and 87.1%; specificity, 70.9% and 65.2%) were significantly larger in IAs than in AAHs, AISs, and MIAs (p < 0.001), whereas the latter three were similar in size (p > 0.050). CT attenuation higher than -632 HU in pGGNs indicated invasiveness (sensitivity, 78.8%; specificity, 59.8%). As opposed to noninvasive pGGNs (AAHs and AISs), invasive pGGNs (MIAs and IAs) usually had heterogeneous density, irregular shape, coarse margin, lobulation, spiculation, pleural indentation, and dilated or distorted vessels (each, p < 0.050). Multivariate analysis showed that mean CT attenuation and presence of lobulation were predictors for invasive pGGNs (p ≤ 0.001). CONCLUSION. The likelihood of invasiveness is greater in pGGNs with larger size (> 10.5 mm or > 86.5 mm²), higher attenuation (> -632 HU), heterogeneous density, irregular shape, coarse margin, spiculation, lobulation, pleural indentation, and dilated or distorted vessels.