Frontiers in nuclear medicine (Lausanne, Switzerland)最新文献

Background: The role of artificial intelligence and radiomics in prediction model development in cancer has been increasing every passing day. Cervical cancer is the 4th most common cancer in women worldwide, contributing to 6.5% of all cancer types. The treatment outcome of cervical cancer patients varies and individualized prediction of disease outcome is of paramount importance.

Purpose: The purpose of this study is to develop and validate the digital signature for 5-year overall survival prediction in cervical cancer using robust CT radiomic and clinical features.

Materials and methods: Pretreatment clinical features and CT radiomic features of 68 patients, who were treated with chemoradiation therapy in our hospital, were used in this study. Radiomic features were extracted using an in-house developed python script and pyradiomic package. Clinical features were selected by the recursive feature elimination technique. Whereas radiomic feature selection was performed using a multi-step process i.e., step-1: only robust radiomic features were selected based on our previous study, step-2: a hierarchical clustering was performed to eliminate feature redundancy, and step-3: recursive feature elimination was performed to select the best features for prediction model development. Four machine algorithms i.e., Logistic regression (LR), Random Forest (RF), Support vector classifier (SVC), and Gradient boosting classifier (GBC), were used to develop 24 models (six models using each algorithm) using clinical, radiomic and combined features. Models were compared based on the prediction score in the internal validation.

Results: The average prediction accuracy was found to be 0.65 (95% CI: 0.60-0.70), 0.72 (95% CI: 0.63-0.81), and 0.77 (95% CI: 0.72-0.82) for clinical, radiomic, and combined models developed using four prediction algorithms respectively. The average prediction accuracy was found to be 0.69 (95% CI: 0.62-0.76), 0.79 (95% CI: 0.72-0.86), 0.71 (95% CI: 0.62-0.80), and 0.72 (95% CI: 0.66-0.78) for LR, RF, SVC and GBC models developed on three datasets respectively.

Conclusion: Our study shows the promising predictive performance of a robust radiomic signature to predict 5-year overall survival in cervical cancer patients.

Intraosseous hibernoma (IOH) mimicking osseous metastasis is a rare and little-known pitfall in nuclear medicine and radiology. Referring to a clinical case, we show imaging features in FDG-PET and CT as well as pathological characteristics and discuss MRI and differential diagnoses. A 73-year-old woman was assigned for an FDG-PET/CT examination after the incidental finding of a suspicious pulmonary nodule. The FDG-PET/CT examination detected a small slightly FDG-avid pulmonary nodule suspicious for malignancy and a small slightly sclerotic lesion with mild FDG-uptake in the upper pubic bone. Histopathology revealed an intraosseous hibernoma, a rare benign soft-tissue tumor arising from brown fat. In the sparse literature available, intraosseous hibernomas may or may not be positive on bone scans. As in our case, most are slightly sclerotic on CT but lytic lesions have also been described. On MRI, they are T1 hypointense to subcutaneous fat and hyperintense to skeletal muscle; they are usually T2 hyperintense and may show peripheral contrast enhancement. According to the literature, IOHs are mostly incidental findings with solitary lesions in the spine, pelvis, ribs, or, very rarely, in the extremities with low to moderately increased glucose metabolism. IOHs present as painless tumors in general; a few painful cases could be successfully treated with radiofrequency ablation or surgery. Differential diagnoses include metastases, lymphoma, fibrous dysplasia, and non-ossifying fibroma among others. Intraosseous hibernoma is a rare benign tumor that can mimic metastases in FDG-PET, CT, bone scan, and MRI. IOHs might be indistinguishable from metastases or malignant lesions, which makes a biopsy or follow-up mandatory in clinically relevant cases. Given the benign nature of IOHs, radiofrequency ablation or surgery is only an option in symptomatic cases.

Introduction: The optimal strategy for differentiated thyroid cancer (DTC) patients treated with radioiodine (RAI) following thyroidectomy remains controversial. Multi-centre clinical studies are essential to identify strategies to improve patient outcomes while minimising treatment-induced toxicity.

Materials and methods: The INSPIRE clinical trial (ClinicalTrials.gov Identifier: NCT04391244) aims to investigate patient-specific dosimetry for DTC patients and to determine the range of absorbed doses delivered to target and non-target tissues and their relationship with treatment outcome and toxicity.

Results: We report here initial results of the first 30 patients enrolled onto the INSPIRE trial. A large range of absorbed doses are observed for both thyroid remnants and salivary glands, with median values of 4.8 Gy (Range 0.2 - 242 Gy) and 0.3 Gy (Range 0.1 to 1.7 Gy), respectively.

Discussion: The preliminary study results are encouraging and could help to improve our understanding of absorbed doses to thyroid remnants and normal organs following RAI therapy. Such knowledge could potentially enable patient-specific treatment planning with improved clinical outcomes and quality-of-life of patients.

Introduction: Islet xenotransplantation may be a therapeutic option in type 1 diabetes. Recent advances in generating genetically modified source pigs offer advantages as immune suppressants can potentially be eliminated after the transplantation. Therapy monitoring would greatly benefit from noninvasive methods for assessing the viability of transplanted islets. Peptide-based positron emission tomography (PET) targeting the glucagon-like peptide-1 receptor (GLP1R) expression on beta cells may offer a procedure that can directly be translated from an experimental setting to the clinic. The aim of this study was to establish the labeling of the GLP1R ligand [⁶⁸Ga]Ga-exendin-4, to demonstrate the feasibility of imaging porcine islet xenografts in vivo and to compare signal quality for three different transplantation sites in a mouse model.

Materials and methods: Mice with engrafted neonatal porcine islet cell clusters (NPICCs) under the kidney capsule, into the inguinal fold, or the lower hindlimb muscle were studied. After reaching normoglycemia, the mice were injected with [⁶⁸Ga]Ga-exendin-4 for PET data acquisition. Subsequent autoradiography (AR) was used for comparing ex vivo data with in vivo uptake.

Results: NPICCs in the lower right hindlimb muscle could be detected in vivo and in AR. Due to the high background in the kidney and urinary bladder, islets could not be detected in the PET data at transplantation sites close to these organs, while AR showed a clear signal for the islets in the inguinal fold.

Discussion: PET with [⁶⁸Ga]Ga-exendin-4 detects islets transplanted in the hindlimb muscle tissue of mice, offering the potential of longitudinal monitoring of viable porcine islets. Other sites are not suitable for in vivo imaging owing to high activity accumulation of Exendin-4 in kidney and bladder.

Introduction: Perfusion imaging strongly predicts coronary artery disease (CAD), whereas cardiac volumes and left ventricular ejection fraction (LVEF) strongly predict mortality. Compared to conventional Anger single-photon emission computed tomography (SPECT) cameras, cadmium-zinc-telluride (CZT) cameras provide higher resolution, resulting in different left ventricular volumes. The cadmium-zinc-telluride D-SPECT camera is commonly used to image in the upright position, which introduces changes in left ventricular loading conditions and potentially alters left ventricular volumes. However, little or no data exist on the predictive value of left ventricular volumes and ejection fraction when acquired in the upright position. We investigated models for the prediction of CAD and mortality, comparing upright and supine imaging.

Methods: A retrospective study of patients with upright/supine stress and rest imaging and coronary angiography within 3 months was performed. Univariate and multivariable analyses were performed to predict abnormal angiograms and all-cause mortality.

Results: Of the 392 patients, 210 (53.6%) had significant angiographic CAD; 78 (19.9%) patients died over 75 months. The best multivariable model for CAD included the supine summed stress score and supine stress LVEF, with an area under the receiver operating characteristic of 0.862, a sensitivity of 76.7%, and a specificity of 82.4%, but this model was not statistically superior to the best upright model. The best multivariable models for mortality included age, diabetes, history of cardiovascular disease, and end-systolic volume, with the upright and supine models being equivalent.

Discussion: Angiographic CAD was best predicted by the supine summed stress score and LVEF but was not statistically superior to the next-best upright model. Mortality was best predicted by end-systolic volume in combination with age, diabetes status, and cardiovascular disease status, with equivalent results from the upright and supine images.

Introduction: Conventional magnetic resonance imaging (MRI) has limitations in differentiating tumor recurrence (TR) from radionecrosis (RN) in high-grade gliomas (HGG), which can present with morphologically similar appearances. Multiparametric advanced MR sequences and Positron Emission Tomography (PET) with amino acid tracers can aid in diagnosing tumor metabolism. The role of both modalities on an individual basis and combined performances were investigated in the current study.

Materials and methods: Patients with HGG with MRI and PET within three weeks were included in the retrospective analysis. The multiparametric MRI included T1-contrast, T2-weighted sequences, perfusion, diffusion, and spectroscopy. MRI was interpreted by a neuroradiologist without using information from PET imaging. 18F-Fluoroethyl-Tyrosine (FET) uptake was calculated from the areas of maximum enhancement/suspicion, which was assessed by a nuclear medicine physician (having access to MRI to determine tumor-to-white matter ratio over a specific region). A definitive diagnosis of TR or RN was made based on the combination of multidisciplinary joint clinic decisions, histopathological examination, and clinic-radiological follow-up as applicable.

Results: 62 patients were included in the study between July 2018 and August 2021. The histology during initial diagnosis was glioblastoma, oligodendroglioma, and astrocytoma in 43, 7, and 6 patients, respectively, while in 6, no definitive histological characterization was available. The median time from radiation (RT) was 23 months. 46 and 16 patients had TR and RN recurrence, respectively. Sensitivity, specificity, and accuracy using MRI were 98, 77, and 94%, respectively. Using PET imaging with T/W cut-off of 2.65, sensitivity, specificity, and accuracy were 79, 84, and 80%, respectively. The best results were obtained using both imaging combined with sensitivity, specificity, and accuracy of 98, 100, and 98%, respectively.

Conclusion: Combined imaging with MRI and FET-PET offers multiparametric assessment of glioma recurrence that is correlative and complimentary, with higher accuracy and clinical value.

The primary goal of diagnostic nuclear medicine is to provide complete and accurate reports without equivocation or disclaimers. If specific clinical questions cannot be answered because of radiopharmaceutical extravasation, the imaging study may have to be repeated. The decision to reimage is based on several factors including the diagnostic quality of the images, additional patient radiation dose, patient burden, and administrative constraints. Through process improvement efforts, nuclear medicine departments can significantly reduce the frequency of extravasation and thereby also the need for reimaging. Communication with the patient is important any time extravasation may impact their immediate or future care. The circumstances and potential ramifications should be explained, and patient concerns should be addressed. Although recent arguments have been made in favor of investigating and addressing only those extravasations which result in serious patient injury, patients and their referring physicians deserve to know any time their nuclear medicine study may have been impacted.

Single-photon emission computed tomography (SPECT) systems with pinhole collimators are becoming increasingly important in clinical and preclinical nuclear medicine investigations as they can provide a superior resolution-sensitivity trade-off compared to conventional parallel-hole and fanbeam collimators. Previously, open-source software did not exist for reconstructing tomographic images from pinhole-SPECT datasets. A 3D SPECT system matrix modelling library specific for pinhole collimators has recently been integrated into STIR, an open-source software package for tomographic image reconstruction. The pinhole-SPECT library enables corrections for attenuation and the spatially variant collimator-detector response by incorporating their effects into the system matrix. Attenuation correction can be calculated with a simple single line of response or a full model. The spatially variant collimator-detector response can be modelled with a point spread function and depth of interaction corrections for increased system matrix accuracy. In addition, improvements to computational speed and memory requirements can be made with image masking. This work demonstrates the flexibility and accuracy of STIR's support for pinhole-SPECT datasets using measured and simulated single-pinhole SPECT data from which reconstructed images were analysed quantitatively and qualitatively. The extension of the open-source STIR project with advanced pinhole-SPECT modelling will enable the research community to study the impact of pinhole collimators in several SPECT imaging scenarios and with different scanners.

Introduction: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative, multisystem disorder. Its clinical presentation typically consists of progressive focal muscle atrophy and weakness. In addition to motor disorders, the association between ALS and cancer has been researched, such as frontotemporal dementia and progressive supranuclear palsy. The diagnosis is based primarily on the clinical history, physical examination, electrodiagnostic tests (with an EMG needle), and neuroimaging, such as MRI and ¹⁸F-FDG PET/CT.

Presentation of the case: A 67-year-old male patient was diagnosed with prostate adenocarcinoma with a clinical picture of muscle weakness in the lower limbs that caused falls and was associated with fasciculations in the thighs and arms, alterations in the tone of voice, poor memory, and difficulty articulating words. In the neurological assessment, he described walking supported by a walker with decreased strength in both lower limbs and sensitivity without alterations. The diagnoses of upper and lower motor neuron disease and probable ALS were integrated. Furthermore, the probable coexistence of frontotemporal dementia/disorder (FDD) with ALS was considered. The main findings in the ¹⁸F-FDG PET/CT study was hypometabolism in the cortex of the bilateral motor and premotor areas, the anterior cingulate, both caudate and putamen, a metabolic pattern compatible with ALS, and progressive supranuclear palsy.

Conclusion: Through the PET/CT studies, we demonstrated a case in which ALS, prostate cancer and progressive supranuclear palsy coexisted molecularly; it was clinically difficult to diagnose. Molecular imaging has potential in the diagnostic and prognostic evaluation of ALS. It is crucial to identify the disease early and reliably through metabolic patterns that allow us to confirm the disease or differentiate it from other pathologies.