The status of nuclear medicine in China: the first official national survey.

AIM/INTRODUCTION: The National Nuclear Medicine Quality Control Center of China conducted the first official survey to investigate the nationwide situation of nuclear medicine in 2020. The survey aimed to unveil the current nuclear medicine situation and its quality control in China. MATERIALS AND METHODS: The web-based survey was conducted and the data was collected via the National Clinical Improvement System (NCIS) of China from 1st April to 31st May 2021. RESULTS: A total of 808 institutes across 30 provinces responded to the national survey. For human resources, there are 4460 physicians, 3077 technologists, 339 physicists, and 309 radiochemists. There are 887 single-photon imaging instruments, including 823 SPECT or SPECT/CT, and 365 PET instruments including 314 PET/CT. Six hundred twenty-four institutes perform SPECT examinations and 319 institutes perform PET examinations. 60% of SPECT scans are bone scintigraphy. A total of 97% of PET scans use an [18F]F-FDG tracer. Furthermore, 587 institutes provide radionuclide therapy services but only 280 institutes have admission rooms. The top three radionuclide therapies are [131I] therapy of hyperthyroidism with 546 institutes, [89Sr] therapy of bone metastasis with 400 institutes, and [131I] therapy of differentiated thyroid cancer with 286 institutes. Finally, for the frequency of equipment quality control per year, there are about 67 times self-test within the department for SPECT instruments and 111 times for PET instruments on average in each province. There are about three failures of SPECT and five failures of PET on average per year in each province. There are 408 institutes (of 624 SPECT institutes) performing quality control of SPECT radiopharmaceuticals, 216 (of 319) for PET radiopharmaceuticals, and 373 (of 587) for radionuclide therapy. CONCLUSION: These results of the first official survey towards current status of nuclear medicine in China are the foundation for the establishment of the quality control management system.

Deep learning model for automatic image quality assessment in PET.

BACKGROUND: A variety of external factors might seriously degrade PET image quality and lead to inconsistent results. The aim of this study is to explore a potential PET image quality assessment (QA) method with deep learning (DL). METHODS: A total of 89 PET images were acquired from Peking Union Medical College Hospital (PUMCH) in China in this study. Ground-truth quality for images was assessed by two senior radiologists and classified into five grades (grade 1, grade 2, grade 3, grade 4, and grade 5). Grade 5 is the best image quality. After preprocessing, the Dense Convolutional Network (DenseNet) was trained to automatically recognize optimal- and poor-quality PET images. Accuracy (ACC), sensitivity, specificity, receiver operating characteristic curve (ROC), and area under the ROC Curve (AUC) were used to evaluate the diagnostic properties of all models. All indicators of models were assessed using fivefold cross-validation. An image quality QA tool was developed based on our deep learning model. A PET QA report can be automatically obtained after inputting PET images. RESULTS: Four tasks were generated. Task2 showed worst performance in AUC,ACC, specificity and sensitivity among 4 tasks, and task1 showed unstable performance between training and testing and task3 showed low specificity in both training and testing. Task 4 showed the best diagnostic properties and discriminative performance between poor image quality (grade 1, grade 2) and good quality (grade 3, grade 4, grade 5) images. The automated quality assessment of task 4 showed ACC = 0.77, specificity = 0.71, and sensitivity = 0.83, in the train set; ACC = 0.85, specificity = 0.79, and sensitivity = 0.91, in the test set, respectively. The ROC measuring performance of task 4 had an AUC of 0.86 in the train set and 0.91 in the test set. The image QA tool could output basic information of images, scan and reconstruction parameters, typical instances of PET images, and deep learning score. CONCLUSIONS: This study highlights the feasibility of the assessment of image quality in PET images using a deep learning model, which may assist with accelerating clinical research by reliably assessing image quality.

Preclinical and pilot clinical evaluation of a small-molecule carbonic anhydrase IX targeting PET tracer in clear cell renal cell carcinoma.

PURPOSE: Clear cell renal cell carcinoma (ccRCC) highly expresses carbonic anhydrase IX (CAIX). The purpose of this study was to evaluate 68Ga-NY104, a small-molecule CAIX-targeting PET agent, in tumor models of ccRCC and patients diagnosed with confirmed, or suspicious, ccRCC. METHODS: The in vivo and ex vivo biodistribution of 68Ga-NY104 was investigated in CAIX-positive OS-RC-2 xenograft-bearing models. The binding of the tracer was further validated using autoradiography for human ccRCC samples. In addition, three patients with confirmed or suspicious ccRCC were studied. RESULTS: NY104 can be labeled with high radiochemical yield and purity. It quickly cleared through kidney with α-half-life of 0.15 h. Discernible uptake is noted in the heart, lung, liver, stomach, and kidney. The OS-RC-2 xenograft demonstrated intense uptake 5 min after injection and gradually increased until 3 h after injection with ID%/g of 29.29 ± 6.82. Significant binding was detected using autoradiography on sections of human ccRCC tumor. In the three patients studied, 68Ga-NY104 was well-tolerated and no adverse events were reported. Substantial accumulation was observed in both primary and metastatic lesions in patient 1 and 2 with SUVmax of 42.3. Uptake in the stomach, pancreas, intestine, and choroid plexus was noted. The lesion in third patient was correctly diagnosed as non-metastatic for negative 68Ga-NY104 uptake. CONCLUSION: 68Ga-NY104 can efficiently and specifically bind to CAIX. Given the pilot nature of our study, future clinical studies are warranted to evaluate 68Ga-NY104 for detection of CAIX-positive lesions in patients with ccRCC. TRIAL REGISTRATION: The clinical evaluation part of this study was retrospectively registered at ClinicalTrial.gov (NCT05728515) as NYPILOT on 6 Feb, 2023.

A quantitative clinical evaluation of simultaneous reconstruction of attenuation and activity in time-of-flight PET.

BACKGROUND: The maximum likelihood activity and attenuation (MLAA) reconstruction algorithm has been proposed to jointly estimate tracer activity and attenuation at the same time, and proven to be a promising solution to the CT attenuation correction (CT-AC) artifacts in PET images. This study aimed to perform a quantitative evaluation and clinical validation of the MLAA method. METHODS: A uniform cylinder phantom filled with 18F-FDG solution was scanned to optimize the reconstruction parameters for the implemented MLAA algorithm. 67 patients who underwent whole-body 18F-FDG PET/CT scan were retrospectively recruited. PET images were reconstructed using MLAA and clinical standard OSEM algorithm with CT-AC (CT-OSEM). The mean and maximum standardized uptake values (SUVmean and SUVmax) in regions of interest (ROIs) of organs, high uptake lesions and areas affected by metal implants and respiration motion artifacts were quantitatively analyzed. RESULTS: In quantitative analysis, SUVs in patient's organ ROIs between two methods showed R2 ranging from 0.91 to 0.98 and k ranging from 0.90 to 1.06, and the average SUVmax and SUVmean differences between two methods were within 10% range, except for the lung ROI, which was 10.5% and 16.73% respectively. The average SUVmax and SUVmean differences of a total of 117 high uptake lesions were 7.25% and 7.10% respectively. 20 patients were identified to have apparent respiration motion artifacts in the liver in CT-OSEM images, and the SUVs differences between two methods measured at dome of the liver were significantly larger than measured at middle part of the liver. 10 regions with obvious metal artifacts were identified in CT-OSEM images and the average SUVmean and SUVmax differences in metal implants affected regions were reported to be 52.90% and 56.20% respectively. CONCLUSIONS: PET images reconstructed using MLAA are clinically acceptable in terms of image quality as well as quantification and it is a useful tool in clinical practice, especially when CT-AC may cause respiration motion and metal artifacts. Moreover, this study also provides technical reference and data support for the future iteration and development of PET reconstruction technology of SUV accurate quantification.

Clinical effect of mitomycin C combined with operation in the treatment of hyperplastic scar of auricle. / æ‰‹æœ¯åˆ‡é™¤è”åˆä¸è£‚éœ‰ç´ C治疗耳廓增生性瘢痕的临床疗效.

OBJECTIVES: To observe the clinical effect and recurrence rate of mitomycin C combined with operation in the treatment of hyperplastic scar of auricle with different diameters. METHODS: A total of 53 patients (67 ears) collected from January 2011 to June 2019 were randomly divided into a combined treatment group (31 ears) and a control group (36 ears). The recurrence rate was observed from one year to three years after operation. RESULTS: The recurrence rate was 52.8% in the control group and 16.1% in the combined treatment group, respectively. For the hyperplastic scar of auricle with diameter from >1.0 cm to 3.0 cm, the recurrence rate was significantly lower in the combined treatment group than that in the control group (χ2=10.804, P<0.05). But there was no significant difference for the hyperplastic scar of auricle with diameter less than 1.0 cm or more than 3.0 cm (both P>0.05). CONCLUSIONS: Mitomycin C combined with surgery can significantly reduce or delay the recurrence rate of middle diameter of hyperplastic scar of auricle, but it does not affect the hyperplastic scar of auricle with too large or too small diameter.