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

Lee, Jae Ho; Kim, Tae Hoon; Lee, Sungsoo; Han, Kyunghwa; Byun, Min Kwang; Chang, Yoon Soo; Kim, Hyung Jung; Lee, Geun Dong; Park, Chul Hwan

doi:10.1371/journal.pone.0205490

Cited by 5 publications

(5 citation statements)

References 31 publications

(31 reference statements)

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“…According to phantom study and clinical practice, we determined the consistency between solid component size on thin-section CT evaluated by MPVR and PIS to predict invasive degree of SSNs. On MPVR images, the component within SSN with the CT value of greater than −350 HU was defined as solid component and displayed as red part consistent with the color of pulmonary vessels, which was close to the results of previous studies ( 32 - 35 ). Cohen et al ( 34 ) reported that software measurements of solid component at a threshold of -350 HU showed the highest agreement without significant difference with invasive component sizes on pathology with a mean difference of −0.12 mm (P>0.05).…”

Section: Discussionsupporting

confidence: 87%

Accuracy of solid portion size measured on multiplanar volume rendering images for assessing invasiveness in lung adenocarcinoma manifesting as subsolid nodules

Li,

Chu,

et al. 2024

Quant Imaging Med Surg

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Background The solid component of subsolid nodules (SSNs) is closely associated with the invasiveness of lung adenocarcinoma, and its accurate assessment is crucial for selecting treatment method. Therefore, this study aimed to evaluate the accuracy of solid component size within SSNs measured on multiplanar volume rendering (MPVR) and compare it with the dimensions of invasive components on pathology. Methods A pilot study was conducted using a chest phantom to determine the optimal MPVR threshold for the solid component within SSN, and then clinical validation was carried out by retrospective inclusion of patients with pathologically confirmed solitary SSN from October 2020 to October 2021. The radiological tumor size on MPVR and solid component size on MPVR (RSS m ) and on lung window (RSS l ) were measured. The size of the tumor and invasion were measured on the pathological section, and the invasion, fibrosis, and inflammation within SSNs were also recorded. The measurement difference between computed tomography (CT) and pathology, inter-observer and inter-measurement agreement were analyzed. Receiver operating characteristic (ROC) analysis and Bland-Altman plot were performed to evaluate the diagnostic efficiency of MPVR. Results A total of 142 patients (mean age, 54±11 years, 39 men) were retrospectively enrolled in the clinical study, with 26 adenocarcinomas in situ, 92 minimally invasive adenocarcinomas (MIAs), and 24 invasive adenocarcinomas (IAs). The RSS l was significantly smaller than pathological invasion size with fair inter-measurement agreement [intraclass correlation coefficient (ICC) =0.562, P<0.001] and moderate interobserver agreement (ICC =0.761, P<0.001). The RSS m was significantly larger than pathological invasion size with the excellent inter-measurement agreement (ICC =0.829, P<0.001) and excellent (ICC =0.952, P<0.001) interobserver agreement. ROC analysis showed that the cutoff value of RSS m for differentiating adenocarcinoma in situ from MIA and MIA from IA was 1.85 and 6.45 mm (sensitivity: 93.8% and 95.5%, specificity: 85.7% and 88.2%, 95% confidence internal: 0.914–0.993 and 0.900–0.983), respectively. The positive predictive value-and negative predictive value of MPVR in predicting invasiveness were 92.8% and 100%, respectively. Conclusions Using MPVR to predict the invasive degree of SSN had high accuracy and good inter-observer agreement, which is superior to lung window measurements and helpful for clinical decision-making.

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Section: Discussionsupporting

confidence: 87%

Accuracy of solid portion size measured on multiplanar volume rendering images for assessing invasiveness in lung adenocarcinoma manifesting as subsolid nodules

Li,

Chu,

et al. 2024

Quant Imaging Med Surg

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“…Information about the characteristic findings of AIS and MIA is important given that patients have a 100% or near‐100% chance of disease‐free survival, respectively, if these lesions are completely resected 4,5 . Despite the growing number of published cases, no definitive rates for recurrence have so far been reported in patients with AIS 15–22 .…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, several recent studies have reported the characteristics of invasive and noninvasive adenocarcinoma imaging patterns 2–4 . Nonetheless, there is insufficient evidence in the current literature about the differences in the rate of recurrence and prognosis between AIS and MIA 5 .…”

Section: Introductionmentioning

confidence: 99%

Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?

et al. 2021

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Background Given the subtle pathological signs of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), effective differentiation between the two entities is crucial. However, it is difficult to predict these conditions using preoperative computed tomography (CT) imaging. In this study, we investigated whether histological diagnosis of AIS and MIA using quantitative three‐dimensional CT imaging analysis could be predicted. Methods We retrospectively analyzed the images and histopathological findings of patients with lung cancer who were diagnosed with AIS or MIA between January 2017 and June 2018. We used Synapse Vincent (v. 4.3) (Fujifilm) software to analyze the CT attenuation values and performed a histogram analysis. Results There were 22 patients with AIS and 22 with MIA. The ground‐glass nodule (GGN) rate was significantly higher in patients with AIS (p < 0.001), whereas the solid volume (p < 0.001) and solid rate (p = 0.001) were significantly higher in those with MIA. The mean (p = 0.002) and maximum (p = 0.025) CT values were significantly higher in patients with MIA. The 25th, 50th, 75th, and 97.5th percentiles (all p < 0.05) for the CT values were significantly higher in patients with MIA. Conclusions We demonstrated that quantitative analysis of 3D‐CT imaging data using software can help distinguish AIS from MIA. These analyses are useful for guiding decision‐making in the surgical management of early lung cancer, as well as subsequent follow‐up.

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“…Meanwhile, Cohen et al ( 13 ) suggested that segmentation of the solid component shows the best performance at a threshold of −350 HU, and measurements on mediastinal windows (window width, 400 HU; level, 30 HU) were significantly smaller than the actual sizes of the invasive components. In the same context, Lee et al ( 20 ) compared two different thresholds, namely, −160 HU and −400 HU. They concluded high diagnostic accuracy in −400 HU for determining the presence of solid components of SSNs, whereas low sensitivity and negative predictive value in −160 HU.…”

Section: Discussionmentioning

confidence: 99%

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

이

et al. 2021

J Korean Soc Radiol

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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.

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

Cited by 5 publications

References 31 publications

Accuracy of solid portion size measured on multiplanar volume rendering images for assessing invasiveness in lung adenocarcinoma manifesting as subsolid nodules

Accuracy of solid portion size measured on multiplanar volume rendering images for assessing invasiveness in lung adenocarcinoma manifesting as subsolid nodules

Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?

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

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