Cystic Primary Lung Cancer

Byrne, Danielle; English, John; Atkar-Khattra, Sukhinder; Lam, Stephen; Yee, John; Myers, Renelle; Bilawich, Ana-Maria; Mayo, John R.; Mets, Onno M.

doi:10.1097/rti.0000000000000594

Cited by 9 publications

(2 citation statements)

References 20 publications

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“…Moreover, the incidence of CCLC was estimated at 0.46% in a surgical series (15). However, Byrne et al recently reported an incidence rate of 9.3% in a surgical series (11). In the present study, the incidence of CCLC was higher than previous reports.…”

Section: Discussioncontrasting

confidence: 72%

“…In high-risk individuals, CT screening for lung cancer focuses on early detection; however, there are no detailed CT findings in patients with CCLC. Currently, there are no recommendations or clinical guidelines for the surveillance of CCLC in routine practice or screening (11). Few studies on CCLC have investigated the findings of 18 F-fluorodeoxyglucose positron emission tomography ( 18 F-FDG PET); however, even when findings are available, the number of patients is relatively small (4,5).…”

Section: Introductionmentioning

confidence: 99%

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Cystic and Cavitary Lung Cancer: Its Characteristic Features on CT and FDG-PET Scans

et al. 2023

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Background: Cystic and cavitary lung cancer (CCLC) is infrequently observed on computed tomography (CT) scans; however, its diagnosis is often overlooked or delayed. Objectives: The current study aimed to investigate the CT and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) features of CCLC. Patients and Methods: A total of 809 patients who underwent lung tumor resection were examined in this study, and the presence of cystic and cavitary lesions on CT scans was investigated. Based on the CT scans, CCLC was identified in 102 consecutive patients. The diameters of the whole nodule and the airspace portion of the lesion, morphological patterns of cystic and cavitary lesions, presence of ground glass opacity (GGO), and loculation pattern (including the presence of a septum) were evaluated. The positron emission tomography (PET) scans of CCLC were also assessed visually and semi-quantitatively. Results: A total of 104 CCLC lesions were evaluated in this study. The histological analysis indicated 85 cases of adenocarcinoma (AD) and 19 cases of squamous cell carcinoma (SCC). The morphological patterns of cystic and cavitary lesions were classified into four types. The presence of GGO, type 4 morphological pattern (a soft-tissue-density structure intermixed within clusters of a cavitary lesion), and multilocular with septum (MS) loculation pattern were significantly different according to the histological type. The maximum standardized uptake value (SUVmax) on PET scans was significantly lower in AD compared to SCC (P = 0.002). In the solid nodule part of cystic and cavitary lesions, the MS pattern was significantly more common in AD (P = 0.044). Conclusion: When cystic and cavitary lesions are observed on CT scans, the presence of GGO and the MS pattern should be considered, as it may help differentiate the histological findings.

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Section: Discussioncontrasting

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Cystic and Cavitary Lung Cancer: Its Characteristic Features on CT and FDG-PET Scans

et al. 2023

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External validation of the performance of commercially available deep-learning-based lung nodule detection on low-dose CT images for lung cancer screening in Japan

Fukumoto,

Yamashita,

Kawashita

et al. 2024

Jpn J Radiol

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Purpose Artificial intelligence (AI) algorithms for lung nodule detection have been developed to assist radiologists. However, external validation of its performance on low-dose CT (LDCT) images is insufficient. We examined the performance of the commercially available deep-learning-based lung nodule detection (DL-LND) using LDCT images at Japanese lung cancer screening (LCS). Materials and methods Included were 43 patients with suspected lung cancer on LDCT images and pathologically confirmed lung cancer. The reference standard for nodules whose diameter exceeded 4 mm was set by a radiologist who referred to the reports of two other radiologists reading the LDCT images. After we applied commercially available DL-LND to the LDCT images, the radiologist reviewed all nodules detected by DL-LND. When he failed to identify an existing nodule, it was also included in the reference standard. To validate the performance of DL-LND, the sensitivity for lung nodules and lung cancer, the positive-predictive value (PPV) for lung nodules, and the mean number of false-positive (FP) nodules per CT scan were recorded. Results The radiologist detected 97 nodules including 43 lung cancers and missed 3 solid nodules detected by DL-LND. A total of 100 nodules was included in the reference standard. DL-LND detected 396 nodules including 40 lung cancers. The sensitivity for the 100 nodules was 96.0%; the PPV was 24.2% (96/396). The mean number of FP nodules per CT scan was 7.0; sensitivity for lung cancer was 93.0% (40/43). DL-LND missed three lung cancers; 2 of these were atypical pulmonary cysts. Conclusion We externally verified that the sensitivity for lung nodules and lung cancer by DL-LND was very high. However, its low PPV and the increased FP nodules remains a serious drawback of DL-LND.

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ACR Lung-RADS v2022: Assessment Categories and Management Recommendations

Christensen,

Prosper,

et al. 2024

CHEST

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Cystic Primary Lung Cancer

Cited by 9 publications

References 20 publications

Cystic and Cavitary Lung Cancer: Its Characteristic Features on CT and FDG-PET Scans

Cystic and Cavitary Lung Cancer: Its Characteristic Features on CT and FDG-PET Scans

External validation of the performance of commercially available deep-learning-based lung nodule detection on low-dose CT images for lung cancer screening in Japan

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations

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