Extended bronchoplasty for locally advanced left lower lobe lung cancer: surgical technique and outcomes†

Lower lobe atelectasis may be the initial imaging manifestation of lung cancer, and its detection on chest radiography and/or CT often allows the interpreting radiologist to be the first to suggest the diagnosis. Affected patients may be asymptomatic or present with vague complaints. Varying degrees of lower lobe atelectasis may occur due to other etiologies. Moderate and marked degrees of lobar atelectasis typically result in a triangular-shaped opacity with its apex oriented towards the hilum. Displaced interlobar fissures are a direct (primary) sign of atelectasis. A unique imaging feature of right lower lobe atelectasis is associated displacement of the minor fissure, in addition to the displaced major fissure that characteristically occurs in right or left lower lobe atelectasis.

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Involvement of the #12u Lymph Nodes Around the Upper Lobe Bronchi in Patients with Lung Cancer of the Right Middle Lobe, Right Lower Lobe, or Left Lower Lobe

Surgery Today ◽

10.1007/s005950050395 ◽

1999 ◽

Vol 29 (3) ◽

pp. 238-242

Author(s):

Masami Sato ◽

Yasuki Saito ◽

Hirokazu Aikawa ◽

Akira Sakurada ◽

Tatsuo Tanita ◽

...

Keyword(s):

Lung Cancer ◽

Lymph Nodes ◽

Lower Lobe ◽

Middle Lobe ◽

Left Lower Lobe ◽

Right Middle Lobe ◽

The Right

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Is T2 non-small cell lung cancer located in left lower lobe appropriate to upstage?

Interactive Cardiovascular and Thoracic Surgery ◽

10.1510/icvts.2004.104380 ◽

2005 ◽

Vol 4 (2) ◽

pp. 126-129 ◽

Cited By ~ 13

Author(s):

A. Iwasaki

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Lower Lobe ◽

Small Cell ◽

Left Lower Lobe ◽

Small Cell Lung

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The left main bronchus transected incorrectly during video-assisted thoracoscopic lobectomy: a case report

Surgical Case Reports ◽

10.1186/s40792-020-01073-8 ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Yuma Shindo ◽

Masahiro Miyajima ◽

Yasuyuki Nakamura ◽

Wataru Arai ◽

Ryunosuke Maki ◽

...

Keyword(s):

Lung Cancer ◽

Main Bronchus ◽

Lower Lobe ◽

Left Main Bronchus ◽

Left Lower Lobe ◽

Left Main ◽

Lobe Bronchus ◽

Intraoperative Complication ◽

Pleural Adhesion ◽

Lower Lobectomy

Abstract Background Several severe intraoperative complications of lung cancer surgery have been reported, but the incorrect transection of the main bronchus is a very rare and serious complication. We report a surgical case of a patient with left lower lobe lung cancer invading the inferior segment of the lingula, with fused interlobar fissure and dense pleural adhesion, in which the left main bronchus was mistaken for the left lower lobe bronchus and was transected. Case presentation A 64-year-old woman with lung adenocarcinoma was referred to our hospital for surgical treatment. Chest computed tomography (CT) scan showed a 30-mm nodule with a clear border and irregular margins in the center of the anterior (S8) segment of the lower lobe of the left lung and another similar 30-mm nodule in the lateral (S9) segment of the same lobe. Metastasis within the same lobe was suspected. A thoracoscopic left lower lobectomy was scheduled for the patient. As the patient had a moderately, fused fissure, dense pleural adhesion, and suspicious tumor invasion from the left S8 segment to the left S5 segment, and the interlobar node tightly adhered to the main PA at the site of basilar artery origin of the LLL, we performed left lower lobectomy and a left S5 segmentectomy using the fissureless fissure-last technique. During surgery, the left main bronchus was mistaken for the left lower lobe bronchus and was transected. After transecting the left main bronchus, we performed a sleeve bronchoplasty to prevent pneumonectomy. Conclusions We experienced the rare and serious intraoperative complication of the incorrect transection of the main bronchus. There are few reports of this intraoperative complication, and it should not be overlooked by surgeons.

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A 2D–3D hybrid convolutional neural network for lung lobe auto-segmentation on standard slice thickness computed tomography of patients receiving radiotherapy

BioMedical Engineering OnLine ◽

10.1186/s12938-021-00932-1 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Hengle Gu ◽

Wutian Gan ◽

Chenchen Zhang ◽

Aihui Feng ◽

Hao Wang ◽

...

Keyword(s):

Neural Network ◽

Computed Tomography ◽

Lung Cancer ◽

Cancer Patients ◽

Locally Advanced ◽

Lower Lobe ◽

Slice Thickness ◽

Lung Lobe ◽

Lung Cancer Patients ◽

Lung Lobes

Abstract Background Accurate segmentation of lung lobe on routine computed tomography (CT) images of locally advanced stage lung cancer patients undergoing radiotherapy can help radiation oncologists to implement lobar-level treatment planning, dose assessment and efficacy prediction. We aim to establish a novel 2D–3D hybrid convolutional neural network (CNN) to provide reliable lung lobe auto-segmentation results in the clinical setting. Methods We retrospectively collected and evaluated thorax CT scans of 105 locally advanced non-small-cell lung cancer (NSCLC) patients treated at our institution from June 2019 to August 2020. The CT images were acquired with 5 mm slice thickness. Two CNNs were used for lung lobe segmentation, a 3D CNN for extracting 3D contextual information and a 2D CNN for extracting texture information. Contouring quality was evaluated using six quantitative metrics and visual evaluation was performed to assess the clinical acceptability. Results For the 35 cases in the test group, Dice Similarity Coefficient (DSC) of all lung lobes contours exceeded 0.75, which met the pass criteria of the segmentation result. Our model achieved high performances with DSC as high as 0.9579, 0.9479, 0.9507, 0.9484, and 0.9003 for left upper lobe (LUL), left lower lobe (LLL), right upper lobe (RUL), right lower lobe (RLL), and right middle lobe (RML), respectively. The proposed model resulted in accuracy, sensitivity, and specificity of 99.57, 98.23, 99.65 for LUL; 99.6, 96.14, 99.76 for LLL; 99.67, 96.13, 99.81 for RUL; 99.72, 92.38, 99.83 for RML; 99.58, 96.03, 99.78 for RLL, respectively. Clinician's visual assessment showed that 164/175 lobe contours met the requirements for clinical use, only 11 contours need manual correction. Conclusions Our 2D–3D hybrid CNN model achieved accurate automatic segmentation of lung lobes on conventional slice-thickness CT of locally advanced lung cancer patients, and has good clinical practicability.

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