FDG-PET/CT finding of benign metastasizing leiomyoma of the lung

We report a case of multiple benign metastasizing leiomyoma (BML) lung nodules showing faint or non-avid uptake of F-18 fluorodeoxyglucose (FDG) (respective 1-hour early and 2-hour delayed maximum standardized uptake values; 1.3 or less and 1.2 or less) in a 50-year-old woman with a history of hysterectomy for uterine leiomyoma at the age of 38 years. When multiple lung nodules show faint or non-avid FDG uptake in a patient with a history of hysterectomy for uterine leiomyoma, BML should be included in the differential diagnosi

Recent topics of the clinical utility of PET/MRI in oncology and neuroscience

Since the inline positron emission tomography (PET)/magnetic resonance imaging (MRI) system appeared in clinical, more than a decade has passed. In this article, we have reviewed recently-published articles about PET/MRI. There have been articles about staging in rectal and breast cancers by PET/MRI using fluorodeoxyglucose (FDG) with higher diagnostic performance in oncology. Assessing possible metastatic bone lesions is considered a proper target by FDG PET/MRI. Other than FDG, PET/MRI with prostate specific membrane antigen (PSMA)-targeted tracers or fibroblast activation protein inhibitor have been reported. Especially, PSMA PET/MRI has been reported to be a promising tool for determining appropriate sites in biopsy. Independent of tracers, the clinical application of artificial intelligence (AI) for images obtained by PET/MRI is one of the current topics in this field, suggesting clinical usefulness for differentiating breast lesions or grading prostate cancer. In addition, AI has been reported to be helpful for noise reduction for reconstructing images, which would be promising for reducing radiation exposure. Furthermore, PET/MRI has a clinical role in neuroscience, including localization of the epileptogenic zone. PET/MRI with new PET tracers could be useful for differentiation among neurological disorders. Clinical applications of integrated PET/MRI in various fields are expected to be reported in the future

Additional file 3 of Short-time-window Patlak imaging using a population-based arterial input function and optimized Bayesian penalized likelihood reconstruction: a feasibility study

Additional file 3. Figure S3. Correlations of the Ki-mean between the reference images and the population-based Ki IF images. For both readers, significant strong and positive correlations (all p < 0.001) for Ki-mean were noted between the reference images and Ki-350 (a reader 1, r = 0.91; b reader 2; r = 0.89), Ki-700 (c reader 1, r = 0.94; d reader 2, r = 0.95) and Ki-1000 images (e reader 1, r = 0.95; f reader 2, r = 0.96)

Additional file 1 of Short-time-window Patlak imaging using a population-based arterial input function and optimized Bayesian penalized likelihood reconstruction: a feasibility study

Additional file 1. Figure S1. The correlation between IDIF and Ao-50 among the 12 patients. There is a significantly high correlation between IDIF and Ao-50 (Y = 113.76 + 97.16x; r = 0.98, p < 0.001)

Additional file 2 of Short-time-window Patlak imaging using a population-based arterial input function and optimized Bayesian penalized likelihood reconstruction: a feasibility study

Additional file 2. Figure S2. Correlations of the Ki-max between the reference images and the population-based IF Ki images. For both readers, significant strong and positive correlations (all p < 0.001) for Ki-max were noted between the reference images and Ki-350 (a reader 1, r = 0.93; b reader 2, r = 0.90), Ki-700 (c reader 1, r = 0.94; d reader 2, r = 0.94), and Ki-1000 images (e reader 1, r = 0.95; f reader 2, r = 0.96)

Additional file 4 of Short-time-window Patlak imaging using a population-based arterial input function and optimized Bayesian penalized likelihood reconstruction: a feasibility study

Additional file 4. Figure S4. Correlations of the Ki-volume between the reference images and population-based Ki images. For both readers, significant and positive correlations (all p < 0.001) for Ki-volume were noted between the reference images and Ki-350 (a reader 1, r = 0.84; b reader 2, r = 0.75), Ki-700 (c reader 1, r = 0.82; d reader 2, r = 0.73) and Ki-1000 images (e reader 1, r = 0.87; f reader 2, r = 0.78)