Purpose Dopamine transporter imaging is routinely used in Parkinson’s disease (PD) and atypical parkinsonian syndromes (APS) diagnosis. While [11C]CFT PET is prevalent in Asia with a large APS database, Europe relies on [123I]FP-CIT SPECT with limited APS data. Our aim was to develop a deep learning-based method to convert [11C]CFT PET images to [123I]FP-CIT SPECT images, facilitating multicenter studies

Purpose Dual-energy (DE) CT enables material decomposition by using two different x-ray energies and may be combined with PET for improved multimodality imaging. However, this increases radiation dose and may require a hardware upgrade due to the added second x-ray CT scan. The recently proposed PET-enabled DECT method allows dual-energy imaging using a conventional PET/CT scanner without the need

Background To develop the extracellular matrix metalloproteinase inducer (CD147)-targeting therapeutic strategies, accurate detection of CD147 expression in tumors is crucial. Owing to their relatively low molecular weights and high affinities, nanobodies (Nbs) may be powerful candidates for cancer diagnosis and therapy. In this study, we developed a novel CD147-targeted nanobody radiotracer, [124I]I-NB147

Over the last 2 decades, significant progress has been made in our understanding of the genomics, tumor immune microenvironment, and immunogenicity of malignant melanoma. Historically, the prognosis for metastatic melanoma was poor because of limited treatment options. However, after multiple landmark clinical trials displaying the efficacy of combined BRAF/MEK inhibition for BRAF-mutant melanoma and

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Our laboratory recently developed [11C]PS13 as a PET radioligand to selectively measure cyclooxygenase-1 (COX-1). The cyclooxygenase enzyme family converts arachidonic acid into prostaglandins and thromboxanes, which mediate inflammation. The total brain uptake of [11C]PS13, which is composed of both specific binding and background uptake, can be accurately quantified with gold standard methods of

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Immuno-PET/CT imaging, a branch of molecular imaging, can noninvasively and specifically visualize biomarker expression across the body. Trophoblast cell surface antigen 2 (Trop2) is a pan-cancer biomarker and plays a crucial role in tumorigenesis through multiple signaling pathways. The study aims to develop and translate novel Trop2 single-domain antibody (sdAb) tracers for clinical use. Methods:

The VISION and TheraP trials introduced different PET-based criteria for patient selection for treatment with 177Lu-PSMA-617 (LuPSMA). TheraP used a higher prostate-specific membrane antigen (PSMA) uptake threshold than VISION and required 18F-FDG PET to exclude patients with discordant findings. Although the screen-failed patients had shorter overall survival (OS) than those treated with LuPSMA, it

177Lu-vipivotide tetraxetan prostate-specific membrane antigen (177Lu-PSMA) therapy is under current scientific investigation and aims to become established in the treatment of metastatic castration-resistant prostate cancer (mCRPC). However, real-world evidence in treatment comparison is scant. Methods: We relied on the FRAMCAP database and compared cabazitaxel versus 177Lu-PSMA therapy in mCRPC patients

Purpose While early diagnosis is crucial, as new treatments can significantly slow the progression of the disease, there is growing evidence on the application of novel imaging techniques for detecting transthyretin amyloidosis (ATTR) in pre-symptomatic stages. This study aimed to evaluate the utility of pre-symptomatic scintigraphic imaging cascade screening for early detection of ATTR. Methods During

Background and purpose Enhanced lesion detection in prostate cancer is observed with late [68 Ga]Ga-PSMA-11 PET/CT imaging compared to standard [68 Ga]Ga-PSMA-11 PET/CT imaging (50–100 min p.i.). However, the poor image quality of late imaging using short axial field of view (SAFOV) PET/CT has hindered its sole clinical adoption. Conversely, the image quality of late imaging with a long axial field

Purpose Somatostatin receptor (SSTR) antagonists have recently emerged as preferable radiotracers for SSTR-targeted imaging and therapy. This study aimed to design a novel SSTR antagonist, [18F]AlF-NOTA-Asp2-PEG2-JR11, and compare its preclinical performance with the previously reported antagonist, [18F]AlF-NOTA-JR11, and the agonist [68Ga]Ga-DOTA-TATE. Methods [18F]AlF-NOTA-Asp2-PEG2-JR11 was synthesized

Purpose This study by the EANM radiobiology working group aims to analyze the efficacy and toxicity of targeted radionuclide therapy (TRT) using radiopharmaceuticals approved by the EMA and FDA for neuroendocrine tumors and prostate cancer. It seeks to understand the correlation between physical parameters such as absorbed dose and TRT outcomes, alongside other biological factors. Methods We reviewed

Purpose Ultrasmall silver sulfide nanoparticles (Ag2S-NP) have been identified as promising contrast agents for a number of modalities and in particular for dual-energy mammography. These Ag2S-NP have demonstrated marked advantages over clinically available agents with the ability to generate higher contrast with high biocompatibility. However, current synthesis methods for inorganic nanoparticles

Purpose 177Lu-OncoFAP-23 is a novel FAP-targeted radioligand therapeutic (RLT) with high and prolonged tumor residence time and promising preclinical efficacy. In this work, we investigated the correlation between the injected molar dose and the in vivo tumor-to-organ ratios and tumor-targeting performance of 177Lu-OncoFAP-23. Methods We evaluated the quantitative biodistribution profile of 177Lu-OncoFAP-23

Surgical instrument segmentation is instrumental to minimally invasive surgeries and related applications. Most previous methods formulate this task as single-frame-based instance segmentation while ignoring the natural temporal and stereo attributes of a surgical video. As a result, these methods are less robust against the appearance variation through temporal motion and view change. In this work

In chest X-ray (CXR) image analysis, rule-based systems are usually employed to extract labels from reports for dataset releases. However, there is still room for improvement in label quality. These labelers typically output only presence labels, sometimes with binary uncertainty indicators, which limits their usefulness. Supervised deep learning models have also been developed for report labeling

In MRI studies, the aggregation of imaging data from multiple acquisition sites enhances sample size but may introduce site-related variabilities that hinder consistency in subsequent analyses. Deep learning methods for image translation have emerged as a solution for harmonizing MR images across sites. In this study, we introduce IGUANe (Image Generation with Unified Adversarial Networks), an original

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177Lu-PSMA-617 (LuPSMA) is a newly established treatment for patients with metastatic castration-resistant prostate cancer (mCRPC), but survival outcomes vary widely, and predictors of treatment responses are needed. This study investigated the role of total tumor volumes (TTVs) and new lesions (NLs) determined by LuPSMA SPECT/CT in early cycles to predict subsequent outcomes in a real-world practice

The diagnosis and surveillance of clear cell renal cell carcinoma (ccRCC) remains a clinical challenge. The high and specific expression of the cluster of differentiation 70 (CD70) in ccRCC makes it a potential diagnostic and therapeutic target. Methods: We detected and analyzed CD70 expression in various renal cell carcinomas (RCCs) and normal kidneys using immunohistochemical staining. Two novel

Baseline metabolic tumor volume (MTV) is a promising prognostic marker in diffuse large B-cell lymphoma (DLBCL). We assessed the prognostic value of 4 novel metabolic risk scores in a real-life DLBCL cohort and compared them with the revised international prognostic index (IPI). Methods: We included a consecutive series of untreated DLBCL, not otherwise specified cases that were diagnosed in our hospital

Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-based pancreatic segmentation is more established, MRI-based segmentation methods are understudied, largely due to a lack of publicly available datasets, benchmarking research efforts, and domain-specific deep learning methods. In this retrospective study

Colonoscopy screening is the gold standard procedure for assessing abnormalities in the colon and rectum, such as ulcers and cancerous polyps. Measuring the abnormal mucosal area and its 3D reconstruction can help quantify the surveyed area and objectively evaluate disease burden. However, due to the complex topology of these organs and variable physical conditions, for example, lighting, large homogeneous