Tongue squamous cell carcinoma (TSCC) is a prevalent malignancy that afflicts the head and neck area and presents a high incidence of metastasis and invasion. Accurate diagnosis and effective treatment are essential for enhancing the quality of life and the survival rates of TSCC patients. The current treatment modalities for TSCC frequently suffer from a lack of specificity and efficacy. Nanoparticles with diagnostic and photothermal therapeutic properties may offer a new approach for the targeted therapy of TSCC. However, inadequate accumulation of photosensitizers at the tumor site diminishes the efficacy of photothermal therapy (PTT). This study modified gold nanodots (AuNDs) with the TSCC-targeting peptide HN-1 to improve the selectivity and therapeutic effects of PTT. The Au-HN-1 nanosystem effectively targeted the TSCC cells and was rapidly delivered to the tumor tissues compared to the AuNDs. The enhanced accumulation of photosensitizing agents at tumor sites achieved significant PTT effects in a mouse model of TSCC. Moreover, owing to its stable long-term fluorescence and high X-ray attenuation coefficient, the Au-HN-1 nanosystem can be used for fluorescence and computed tomography imaging of TSCC, rendering it useful for early tumor detection and accurate delineation of surgical margins. In conclusion, Au-HN-1 represents a promising nanomedicine for imaging-based diagnosis and targeted PTT of TSCC.
Tongue Neoplasms/diagnostic imaging* ; Carcinoma, Squamous Cell/diagnostic imaging* ; Animals ; Gold/chemistry* ; Mice ; Photothermal Therapy/methods* ; Tomography, X-Ray Computed ; Photosensitizing Agents ; Metal Nanoparticles ; Humans ; Cell Line, Tumor

The presence of a positive deep surgical margin in tongue squamous cell carcinoma (TSCC) significantly elevates the risk of local recurrence. Therefore, a prompt and precise intraoperative assessment of margin status is imperative to ensure thorough tumor resection. In this study, we integrate Raman imaging technology with an artificial intelligence (AI) generative model, proposing an innovative approach for intraoperative margin status diagnosis. This method utilizes Raman imaging to swiftly and non-invasively capture tissue Raman images, which are then transformed into hematoxylin-eosin (H&E)-stained histopathological images using an AI generative model for histopathological diagnosis. The generated H&E-stained images clearly illustrate the tissue's pathological conditions. Independently reviewed by three pathologists, the overall diagnostic accuracy for distinguishing between tumor tissue and normal muscle tissue reaches 86.7%. Notably, it outperforms current clinical practices, especially in TSCC with positive lymph node metastasis or moderately differentiated grades. This advancement highlights the potential of AI-enhanced Raman imaging to significantly improve intraoperative assessments and surgical margin evaluations, promising a versatile diagnostic tool beyond TSCC.
Humans ; Spectrum Analysis, Raman/methods* ; Tongue Neoplasms/diagnostic imaging* ; Carcinoma, Squamous Cell/diagnostic imaging* ; Artificial Intelligence ; Margins of Excision

Objective To analyze the ultrasonographic features of secondary squamous cell carcinoma of the thyroid(SSCC-T)and evaluate the diagnostic value of ultrasound.Methods A retrospective analysis was conducted on clinical and ultrasonographic data from 12 patients with pathologically confirmed SSCC-T treated at Beijing Friendship Hospital,Capital Medical University between January 2016 and January 2025.Evaluated parameters included lesion size,echogenicity,edge,vascularity,calcification,and cervical lymph node metastasis.Descriptive statistical analysis was performed to analyze the ultrasonographic features of SSCC-T,and Fisher's exact test was conducted to analyze the correlation between different ultrasound classifications and thyroid dysfunction.Results The 12 patients showed the following ultrasound classifications:nodular type(50.0%,6/12),diffuse type(33.3%,4/12),and mixed type(16.7%,2/12).All diffuse-type patients exhibited a characteristic cord-like hypoechoic pattern.Cervical lymph node metastasis was observed in all the patients,with 75.0%(9/12)showing lymph nodes >2 cm in maximum diameter.Thyroid dysfunction occurred in 66.7%(8/12)of patients,including 2 patients with dynamic shifts from hyperthyroidism to hypothyroidism.Diffuse and mixed types were associated with hypothyroidism(P=0.038).Conclusions SSCC-T demonstrates specific ultrasonographic features,particularly the cord-like hypoechoic pattern in the diffuse type.For patients with squamous cell carcinoma,regular ultrasound examinations of the thyroid and cervical lymph nodes combined with changes in thyroid function are conducive to the timely detection of thyroid metastasis of squamous cell carcinoma.
Humans ; Retrospective Studies ; Ultrasonography ; Carcinoma, Squamous Cell/diagnostic imaging* ; Thyroid Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Male ; Female ; Middle Aged ; Thyroid Gland/diagnostic imaging* ; Adult

Objective: To investigate the diagnostic efficiency of conventional serum tumor markers and their combination with chest CT for stage ⅠA lung cancer. Methods: A total of 1 155 patients with stage ⅠA lung cancer and 200 patients with benign lung lesions (confirmed by surgery) treated at the Cancer Hospital, Chinese Academy of Medical Sciences from January 2016 to October 2020 were retrospectively enrolled in this study. Six conventional serum tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), squamous cell carcinoma associated antigen (SCCA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and gastrin-releasing peptide precursor (ProGRP)] and chest thin-slice CT were performed on all patients one month before surgery. Pathology was taken as the gold standard to analyze the difference of positivity rates of tumor markers between the lung cancer group and the benign group, the moderate/poor differentiation group and the well differentiation group, the adenocarcinoma group and the squamous cell carcinoma group, the lepidic and non-lepidic predominant adenocarcinoma groups, the solid nodule group and the subsolid nodule group based on thin-slice CT, and subgroups of ⅠA1 to ⅠA3 lung cancers. The diagnostic performance of tumor markers and tumor markers combined with chest CT was analyzed using the receiver operating characteristic curve. Results: The positivity rates of six serum tumor markers in the lung cancer group and the benign group were 2.32%-20.08% and 0-13.64%, respectively; only the SCCA positivity rate in the lung cancer group was higher than that in the benign group (10.81% and 0, P=0.022). There were no significant differences in the positivity rates of other serum tumor markers between the two groups (all P>0.05). The combined detection of six tumor markers showed that the positivity rate of the lung cancer group was higher than that of the benign group (40.93% and 18.18%, P=0.004), and the positivity rate of the adenocarcinoma group was lower than that of the squamous cell carcinoma group (35.66% and 47.41%, P=0.045). The positivity rates in the poorly differentiated group and moderately differentiated group were higher than that in the well differentiated group (46.48%, 43.75% and 22.73%, P=0.025). The positivity rate in the non-lepidic adenocarcinoma group was higher than that in lepidic adenocarcinoma group (39.51% and 21.74%, P=0.001). The positivity rate of subsolid nodules was lower than that of solid nodules (30.01% vs 58.71%, P=0.038), and the positivity rates of stageⅠA1, ⅠA2 and ⅠA3 lung cancers were 33.33%, 48.96% and 69.23%, respectively, showing an increasing trend (P=0.005). The sensitivity and specificity of the combined detection of six tumor markers in the diagnosis of stage ⅠA lung cancer were 74.00% and 56.30%, respectively, and the area under the curve (AUC) was 0.541. The sensitivity and specificity of the combined detection of six serum tumor markers with CT in the diagnosis of stage ⅠA lung cancer were 83.0% and 78.3%, respectively, and the AUC was 0.721. Conclusions: For stage ⅠA lung cancer, the positivity rates of commonly used clinical tumor markers are generally low. The combined detection of six markers can increase the positivity rate. The positivity rate of markers tends to be higher in poorly differentiated lung cancer, squamous cell carcinoma, or solid nodules. Tumor markers combined with thin-slice CT showed limited improvement in diagnostic efficiency for early lung cancer.
Humans ; Lung Neoplasms/diagnostic imaging* ; Biomarkers, Tumor ; Retrospective Studies ; Antigens, Neoplasm ; Keratin-19 ; Carcinoembryonic Antigen ; Adenocarcinoma/diagnostic imaging* ; Carcinoma, Squamous Cell/diagnostic imaging* ; Phosphopyruvate Hydratase ; Tomography, X-Ray Computed

Objective: To investigate the diagnostic efficiency of conventional serum tumor markers and their combination with chest CT for stage ⅠA lung cancer. Methods: A total of 1 155 patients with stage ⅠA lung cancer and 200 patients with benign lung lesions (confirmed by surgery) treated at the Cancer Hospital, Chinese Academy of Medical Sciences from January 2016 to October 2020 were retrospectively enrolled in this study. Six conventional serum tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), squamous cell carcinoma associated antigen (SCCA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and gastrin-releasing peptide precursor (ProGRP)] and chest thin-slice CT were performed on all patients one month before surgery. Pathology was taken as the gold standard to analyze the difference of positivity rates of tumor markers between the lung cancer group and the benign group, the moderate/poor differentiation group and the well differentiation group, the adenocarcinoma group and the squamous cell carcinoma group, the lepidic and non-lepidic predominant adenocarcinoma groups, the solid nodule group and the subsolid nodule group based on thin-slice CT, and subgroups of ⅠA1 to ⅠA3 lung cancers. The diagnostic performance of tumor markers and tumor markers combined with chest CT was analyzed using the receiver operating characteristic curve. Results: The positivity rates of six serum tumor markers in the lung cancer group and the benign group were 2.32%-20.08% and 0-13.64%, respectively; only the SCCA positivity rate in the lung cancer group was higher than that in the benign group (10.81% and 0, P=0.022). There were no significant differences in the positivity rates of other serum tumor markers between the two groups (all P>0.05). The combined detection of six tumor markers showed that the positivity rate of the lung cancer group was higher than that of the benign group (40.93% and 18.18%, P=0.004), and the positivity rate of the adenocarcinoma group was lower than that of the squamous cell carcinoma group (35.66% and 47.41%, P=0.045). The positivity rates in the poorly differentiated group and moderately differentiated group were higher than that in the well differentiated group (46.48%, 43.75% and 22.73%, P=0.025). The positivity rate in the non-lepidic adenocarcinoma group was higher than that in lepidic adenocarcinoma group (39.51% and 21.74%, P=0.001). The positivity rate of subsolid nodules was lower than that of solid nodules (30.01% vs 58.71%, P=0.038), and the positivity rates of stageⅠA1, ⅠA2 and ⅠA3 lung cancers were 33.33%, 48.96% and 69.23%, respectively, showing an increasing trend (P=0.005). The sensitivity and specificity of the combined detection of six tumor markers in the diagnosis of stage ⅠA lung cancer were 74.00% and 56.30%, respectively, and the area under the curve (AUC) was 0.541. The sensitivity and specificity of the combined detection of six serum tumor markers with CT in the diagnosis of stage ⅠA lung cancer were 83.0% and 78.3%, respectively, and the AUC was 0.721. Conclusions: For stage ⅠA lung cancer, the positivity rates of commonly used clinical tumor markers are generally low. The combined detection of six markers can increase the positivity rate. The positivity rate of markers tends to be higher in poorly differentiated lung cancer, squamous cell carcinoma, or solid nodules. Tumor markers combined with thin-slice CT showed limited improvement in diagnostic efficiency for early lung cancer.
Humans ; Lung Neoplasms/diagnostic imaging* ; Biomarkers, Tumor ; Retrospective Studies ; Antigens, Neoplasm ; Keratin-19 ; Carcinoembryonic Antigen ; Adenocarcinoma/diagnostic imaging* ; Carcinoma, Squamous Cell/diagnostic imaging* ; Phosphopyruvate Hydratase ; Tomography, X-Ray Computed

Objective: To construct the diagnostic model of superficial esophageal squamous cell carcinoma (ESCC) and precancerous lesions in endoscopic images based on the YOLOv5l model by using deep learning method of artificial intelligence to improve the diagnosis of early ESCC and precancerous lesions under endoscopy. Methods: 13, 009 endoscopic esophageal images of white light imaging (WLI), narrow band imaging (NBI) and lugol chromoendoscopy (LCE) were collected from June 2019 to July 2021 from 1, 126 patients at the Cancer Hospital, Chinese Academy of Medical Sciences, including low-grade intraepithelial neoplasia, high-grade intraepithelial neoplasia, ESCC limited to the mucosal layer, benign esophageal lesions and normal esophagus. By computerized random function method, the images were divided into a training set (11, 547 images from 1, 025 patients) and a validation set (1, 462 images from 101 patients). The YOLOv5l model was trained and constructed with the training set, and the model was validated with the validation set, while the validation set was diagnosed by two senior and two junior endoscopists, respectively, to compare the diagnostic results of YOLOv5l model and those of the endoscopists. Results: In the validation set, the accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the YOLOv5l model in diagnosing early ESCC and precancerous lesions in the WLI, NBI and LCE modes were 96.9%, 87.9%, 98.3%, 88.8%, 98.1%, and 98.6%, 89.3%, 99.5%, 94.4%, 98.2%, and 93.0%, 77.5%, 98.0%, 92.6%, 93.1%, respectively. The accuracy in the NBI model was higher than that in the WLI model (P<0.05) and lower than that in the LCE model (P<0.05). The diagnostic accuracies of YOLOv5l model in the WLI, NBI and LCE modes for the early ESCC and precancerous lesions were similar to those of the 2 senior endoscopists (96.9%, 98.8%, 94.3%, and 97.5%, 99.6%, 91.9%, respectively; P>0.05), but significantly higher than those of the 2 junior endoscopists (84.7%, 92.9%, 81.6% and 88.3%, 91.9%, 81.2%, respectively; P<0.05). Conclusion: The constructed YOLOv5l model has high accuracy in diagnosing early ESCC and precancerous lesions in endoscopic WLI, NBI and LCE modes, which can assist junior endoscopists to improve diagnosis and reduce missed diagnoses.
Artificial Intelligence ; Endoscopy/methods* ; Esophageal Neoplasms/pathology* ; Esophageal Squamous Cell Carcinoma/diagnostic imaging* ; Humans ; Narrow Band Imaging ; Precancerous Conditions/diagnostic imaging* ; Sensitivity and Specificity

OBJECTIVE: To establish an animal model with malignant tumor in the skull base-infratemporal region, and to explore the role of iodine staining technique in identifying tumor tissues with Micro-CT data. METHODS: Sedation anesthesia was carried out on 12 BABL/c nude mice using inhaled isoflurane, and then WSU-HN6 cells that cultured and immortalized from human tongue squamous cell carcinoma were injected into the right infratemporal fossa via the submandibular area. The procedure was carried out under ultrasonographic guidance. The nude mice were sacrificed after 3 weeks observation. The head specimens were fixed and scanned by Micro-CT, and repeated scans were performed after staining with 3.75% compound iodine solution. Following decalcification in 20% EDTA for 2-4 weeks, the head specimens were embedded and sectioned. Hematoxylin and eosin staining and Pan-Keratin immunohistochemical staining were carried out. Bright-field microscopy and stereomicroscopy were used to visualize. The Micro-CT data were analyzed using iPlan software (Brainlab). RESULTS: Non-traumatic ultrasonography was used to guide HN-6 cells injection and confirm skull-base tumor formation in all the animals. Ultrasonographic guidance reduced the risk of cervical vessel injury when transferring tumor cells into the skull base space. An obvious asymmetrical appearance was detected via ultrasonography 3 weeks after tumor cell injection. The Micro-CT analysis showed that the bone was obviously damaged on the right side of the skull base, but the soft tissue image was unrecognizable. After four days staining with compound iodine solution, the morphology of the tumor and surrounding soft tissue could be clearly identified. Hematoxylin and eosin staining showed the tumor formation of the right infratemporal fossa region accompanied by bone destruction. Human keratin immunohistochemical staining showed that the tumor tissue originated from human squamous cell carcinoma, and the polynuclear osteoclasts could be seen at the margin of the skull base bone resorption. CONCLUSION The animal model with malignant tumor in the skull base-infratemporal region could be successfully established via submandibular injection under ultrasound-guidance. Bone changes of the skull were easily observed on Micro-CT, but the tumor counter was not able to be distinguished from surrounding soft tissue. The 3.75% compound iodine staining of the head specimen could help discern the tumor and surrounding soft tissue in more details.
Animals ; Carcinoma, Squamous Cell/diagnostic imaging* ; Infratemporal Fossa ; Iodine ; Mice ; Mice, Nude ; Skull Base ; Staining and Labeling ; Tongue Neoplasms ; X-Ray Microtomography

Head and Neck Neoplasms/diagnostic imaging* ; Humans ; Molecular Imaging ; Squamous Cell Carcinoma of Head and Neck

OBJECTIVE: To evaluate the diagnostic performance of a non-invasive, non-radiating, economical and convenient infrared thermal imaging in the detection of oral squamous cell carcinoma (OSCC) cervical lymph node metastasis, and evaluate its applicability via parallel test and series test. METHODS: This study was a prospective clinical study which passed the ethical review by the Biomedical Ethics Committee, Hospital of Stomatology, Peking University, and had been submitted for clinical trial registration. Totally 74 OSCC patients who were to undergo a neck dissection were included in this study. The inclusion criteria were patients who: (1) were pathologically diagnosed as malignant tumors and planned to undergo surgical treatment including neck dissection; (2) agreed to participate in this study. The exclusion criteria were those who: (1) had undergone surgeries at head and neck previously; (2) with a history of systemic tumor adjuvant therapies such as radiotherapy or chemotherapy etc; (3) were unwilling or unable to cooperate. Basal information as well as clinical examination results were collected, such as physical examination and contradictive enhanced CT. Besides, infrared thermal imaging was done ahead of surgery. Analysis of the diagnostic power of infrared thermal imaging followed the principles of diagnostic test. The positive signs of infrared thermal imaging were: (1) asymmetric thermographic pattern including vascular pattern in ROI; (2) thickening image of unilateral facial artery/vein, submental artery/vein or external carotid artery; (3) surface temperature of ROI raised over 1 °C compared with the opposite side; (4) changes of neck profile with abnormal temperature pattern. The gold standard of this diagnostic test was pathology diagnosis of cervical lymph nodes. RESULTS: The sensitivity of infrared thermal imaging was 75.0%, while the specificity was 69.0%, accuracy was 71.6%, positive predictive value was 64.9% and negative predictive value was 78.4%. The sensitivity of parallel test which stood for the combination of infrared thermal imaging and conventional clinical examinations was 87.9% while the specificity of series test was 97.6%. CONCLUSION Infrared thermal imaging is a promising non-invasive, non-radiating and economical tool in the detection of cervical lymph node metastasis from OSCC when combined with conventional pre-operative examination.
Carcinoma, Squamous Cell/diagnostic imaging* ; Diagnostic Tests, Routine ; Head and Neck Neoplasms ; Humans ; Infrared Rays ; Lymph Nodes ; Mouth Neoplasms/diagnostic imaging* ; Prospective Studies ; Sensitivity and Specificity

Radioimmunotherapy (RIT) is a therapy that takes advantage of the “cross-fire” effect of emitted radiation by radionuclides conjugated to tumor-directed monoclonal antibodies (mAb) (including those fragments) or peptides. While RIT has been successfully employed for the treatment of lymphoma, mostly with radiolabeled antibodies against CD20 [⁹⁰yttrium (⁹⁰Y)-ibritumomab tiuxetan; Zevalin® and (131)iodine ((131)I)-tositumomab; Bexxar®], its use in solid tumors is more challenging, so far. Immuno-PET, a tool for tracking and quantification of mAbs with PET in vivo, is an exciting novel option to improve diagnostic imaging and guide mAbbased therapy. RIT in solid tumors including head and neck cancer may be an alternative treatment with advances in various biological, chemical, and treatment procedures, and it may help to reduce unnecessary exposure and enhance the therapeutic efficacy. Also, immuno-PET based on RIT might play an important role in cancer staging, in patients or targets selection of targeted therapeutics and in monitoring the response of targeted therapeutics as precision medicine. In this review, fundamentals of RIT/immune-PET and current knowledge of the preclinical/clinical trials in RIT for solid tumor including head and neck cancer are reviewed.
Antibodies ; Antibodies, Monoclonal ; Carcinoma, Squamous Cell ; Diagnostic Imaging ; Head and Neck Neoplasms* ; Head* ; Humans ; Lymphoma ; Neoplasm Staging ; Peptides ; Precision Medicine ; Radioimmunotherapy* ; Radioisotopes