A 57-year-old woman presented to our hospital because of dry cough, intermittent chest wall and back pain for 3 weeks. She complained the pain gradually aggravated but did not influence the length of sleep bouts. Simultaneously, the level of daily physical activity was significantly decreased, with a 3kg unintentional weight loss over the past month. She denied tobacco and tuberculosis exposure history. Physical examination suggests obvious swollen bilateral supraclavicular lymph nodes.
A chest enhanced computed tomography (CT) scan revealed over 200 uniform size pulmonary nodules in an evenly dispersed pattern at bilateral lungs with a 38x45mm new creature at the dorsal segment of the lower lobe of the left lung (Figure 1A-C), in addition to a small amount of left-sided pleural and pericardial effusion. Interestingly, the artificial intelligence (AI) system (The AI software supported by Yitu CT, YITU Healthcare Technology Co., Ltd., China. The AI system of deep learning-based quantification was performed using a novel established lung nodule net based on one automatic segmentation software. This module was developed as a combination of U-net and fully convolutional networks. Approaches for lung nodule segmentation involved the detection of a volume of interest (VOI) covering the nodule area and segmentation inside this VOI. These methods can be generally classified into machine-learning methods based on China big date, which covered more than 10 provinces and more than 50 hospitals), only identified 18 pulmonary nodules (Figure 2), which are lower than 10% of the real data. Besides, all of these were judged as low-risk nodules. Another enhanced CT scans showed multiple liver and adrenal metastases, multiple bone metastases (including thoracic spine, sternum, ribs and left scapula), as well as apparent lymphadenopathy in the left hilar, bilateral mediastinal and retroperitoneal area. Magnetic resonance imaging (MRI) revealed multiple osteolytic bone destruction in thoracic vertebrae and a T7 vertebral body's compression fracture. T-SPOT was negative while a significant elevation of the serum tumor markers (including CEA 839.30 ng/mL , NSE 60.38 ng/mL , Cyfra 21-1 20.11 ng/mL , CA125 466.70 U/mL , CA153 181.00 U/mL , CA199 74.16 U/mL  and CA724 151.40 U/mL ). Biopsy of the left supraclavicular node confirmed metastatic adenocarcinoma (Figure 3A) with supportive immunohistochemical staining reaction: positive for TTF-1 (Figure 3B), PCK (Figure 3C), CK7, but negative for P40, Syn, and the Ki 67 index was reported in 70% (Figure 3D). The peripheral blood gene detection showed wild-type epidermal growth factor receptor (EGFR) with no gene mutation sites. In light of clinical and instrumental examinations, the diagnosis of lung adenocarcinoma (T4N3M1 stage IV), EGFR-negative, was made.
This patient lost the chance of surgical treatment due to the extensive metastatic transfer of primary tumors to distant organs. The negative gene detection result indicated that she could not benefit from target therapy. We recommended a combination therapy regimen, the subsequent imaging revealed a significant decrease in the size and number of primary tumors and metastases (Figure 4).
After combined therapy, the primary tumor size significantly decreased and the miliary lung metastasis almost wholly disappeared on 16-slice computed tomography.