Nuclear Medicine

Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI.

OBJECTIVE: To obtain high-quality positron emission tomography (PET) image with low-dose tracer injection, this study attempts to predict the standard-dose PET (S-PET) image from both its low-dose PET (L-PET) counterpart and corresponding magnetic resonance imaging (MRI).

Comparison of Renal Function between Robot-Assisted and Open Partial Nephrectomy as Determined by Tc 99m-DTPA Renal Scintigraphy.

We compared postoperative renal function impairment between patients undergoing robot-assisted partial nephrectomy (RAPN) and those undergoing open partial nephrectomy (OPN) by using Tc-99m diethylenetriaminepentaacetic acid (DTPA) renal scintigraphy. Patients who underwent partial nephrectomy by a single surgeon between 2007 and 2013 were eligible and were matched by propensity score, based on ag...

Monitoring vascular normalization induced by antiangiogenic treatment with (18)F-fluoromisonidazole-PET.

BACKGROUND: Rationalization of antiangiogenics requires biomarkers. Vascular re-normalization is one widely accepted mechanism of action for this drug...

Progressive Multifocal Leukoencephalopathy with Negative JC Virus PCR following Treatment of Follicular Lymphoma: Implications for Biologics in the Era of Targeted Cancer Therapy.

Anticancer therapy predisposes patients to infections by the immunosuppression that results from treatment. Although 85% of patients with progressive ...

Endoscopic autologous cartilage injection for the patulous eustachian tube.

Patulous eustachian tube (PET) can have a significant negative impact on a patient's quality of life. Several methods of surgical management can be an...

Cytokine profiles in peritoneal dialysis effluent predicts the peritoneal solute transport rate in continuous ambulatory peritoneal dialysis patients.

Cytokine profiles in peritoneal dialysis effluent (PDE) vary among patients of continuous ambulatory peritoneal dialysis (CAPD), which may indicate th...

Clinical Usefulness of F-18 FDG PET/CT in Papillary Thyroid Cancer with Negative Radioiodine Scan and Elevated Thyroglobulin Level or Positive Anti-thyroglobulin Antibody.

PURPOSE: Elevated thyroglobulin (Tg) levels, along with a negative radioiodine scan, present a clinical problem for the diagnosis of recurrence in pap...

Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks.

Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in o...

Combined unsupervised-supervised classification of multiparametric PET/MRI data: application to prostate cancer.

Multiparametric medical imaging data can be large and are often complex. Machine learning algorithms can assist in image interpretation when reliable ...

Fully-automated synthesis of 16β-(18)F-fluoro-5α-dihydrotestosterone (FDHT) on the ELIXYS radiosynthesizer.

Noninvasive in vivo imaging of androgen receptor (AR) levels with positron emission tomography (PET) is becoming the primary tool in prostate cancer d...

Size Control in the Nanoprecipitation Process of Stable Iodine (¹²⁷I) Using Microchannel Reactor-Optimization by Artificial Neural Networks.

In this study, nanosuspension of stable iodine ((127)I) was prepared by nanoprecipitation process in microfluidic devices. Then, size of particles was...

Evaluation of extra virgin olive oil stability by artificial neural network.

The stability of extra virgin olive oil in polyethylene terephthalate bottles and tinplate cans stored for 6 months under dark and light conditions wa...

Prediction of revascularization after myocardial perfusion SPECT by machine learning in a large population.

OBJECTIVE: We aimed to investigate if early revascularization in patients with suspected coronary artery disease can be effectively predicted by integ...

Diagnostic performance of bone scintigraphy analyzed by three artificial neural network systems.

OBJECTIVE: The accuracy of bone scintigraphy analyzed by computer-assisted diagnosis (CAD) software involving multiple artificial neural network (ANN)...

Machine learning models for the differential diagnosis of vascular parkinsonism and Parkinson's disease using [(123)I]FP-CIT SPECT.

PURPOSE: The study's objective was to develop diagnostic predictive models using data from two commonly used [(123)I]FP-CIT SPECT assessment methods: ...

Robot-assisted therapy for improving social interactions and activity participation among institutionalized older adults: a pilot study.

INTRODUCTION: Animal-assisted therapy is gaining popularity as part of therapeutic activities for older adults in many long-term care facilities. Howe...

Weakly Supervised Pathology-Informed Representation Learning for PET-Based Content Retrieval of Intra-Tumour Heterogeneity

We propose a weakly supervised 18FFDG PET representation-learning framework for content based medical image retrieval, using H&E derived information d...

A novel unsupervised machine learning strategy to handle multimodal cardiac PET/MRI data

Arrhythmogenic left ventricular cardiomyopathy is a genetic myocardial disease difficult to diagnose due to the lack of gold standard criteria. Simult...

Efficient Computing for Medical Image Acquisition and Reconstruction

Medical imaging systems such as CT, MRI, PET, and SPECT do not directly acquire images. Instead, they measure physical signals that encode anatomical ...

FlowPET: Physics-Informed Symplectic Flow Matching for Low-Count PET Reconstruction

Low-count Positron Emission Tomography (PET) reconstruction is severely hindered by the dissipative nature of prevailing generative models, where the ...