Neurologic Symptoms After 177Lu-Prostate-Specific-Membrane Antigen-617 Therapy: A Single-Center Experience.

Treatment with 177Lu-prostate-specific membrane antigen (PSMA)-617 (177Lu-vipivotide tetraxetan [Pluvicto]) prolongs both progression-free and overall survival in advanced PSMA-positive metastatic castration-resistant prostate cancer. Data examining specifically neurologic symptoms after 177Lu-PSMA-617 treatment are scarce. In this study, we aimed to review the neurologic findings in a large cohort of metastatic castration-resistant prostate cancer patients undergoing 177Lu-PSMA-617 therapy. Methods: The clinical records and imaging data of patients who received their initial dose of 177Lu-PSMA-617 between March 2022 and November 2022 were retrospectively reviewed. All patients presenting for medical evaluation, regardless of specific specialty appointments, with new or worsening neurologic symptoms were included in the study. Results: A total of 185 patients underwent 177Lu-PSMA-617 therapy. The median age was 70 y (range, 58-90 y). The mean follow-up time was 12.04 ± 2.87 mo. Fifty-five new or worsening neurologic symptoms were observed in 50 patients (27%, 50/185). Of these, 27 (11.9%, 27/185) reported altered taste. Eleven patients (6%, 11/185) experienced dizziness with no other clear etiology; 2 of these patients were admitted to the emergency department (ED). Paresthesia symptoms were reported in 6 patients (3.2%, 6/185). Five patients (2.7%, 5/185) reported headaches, 3 of these patients were admitted to the ED because of the severity of the symptoms. Two patients (1.08%, 2/185) presented with extremity weakness. Two patients (1.08%, 2/185) had an ischemic stroke and were admitted to the ED. One patient (0.05%, 1/185) exhibited gait disturbances. In total, 7 patients (3.78%, 7/185) were admitted to the ED because of neurologic symptoms. None of the patients discontinued or failed to complete the 177Lu-PSMA-617 therapy because of neurologic symptoms. Conclusion: After 177Lu-PSMA-617 treatment, the most common neurologic symptoms were dysgeusia and dizziness. In this study, our follow-up period and population size might not have been sufficient to detect delayed or uncommon neurologic symptoms. In patients without neurologic symptoms or central nervous system metastases before treatment, we found the development of severe neurologic problems to be rare and unlikely to require discontinuation of treatment.

Performance of ChatGPT-4 and Bard chatbots in responding to common patient questions on prostate cancer 177Lu-PSMA-617 therapy.

Background: Many patients use artificial intelligence (AI) chatbots as a rapid source of health information. This raises important questions about the reliability and effectiveness of AI chatbots in delivering accurate and understandable information. Purpose: To evaluate and compare the accuracy, conciseness, and readability of responses from OpenAI ChatGPT-4 and Google Bard to patient inquiries concerning the novel 177Lu-PSMA-617 therapy for prostate cancer. Materials and methods: Two experts listed the 12 most commonly asked questions by patients on 177Lu-PSMA-617 therapy. These twelve questions were prompted to OpenAI ChatGPT-4 and Google Bard. AI-generated responses were distributed using an online survey platform (Qualtrics) and blindly rated by eight experts. The performances of the AI chatbots were evaluated and compared across three domains: accuracy, conciseness, and readability. Additionally, potential safety concerns associated with AI-generated answers were also examined. The Mann-Whitney U and chi-square tests were utilized to compare the performances of AI chatbots. Results: Eight experts participated in the survey, evaluating 12 AI-generated responses across the three domains of accuracy, conciseness, and readability, resulting in 96 assessments (12 responses x 8 experts) for each domain per chatbot. ChatGPT-4 provided more accurate answers than Bard (2.95 ± 0.671 vs 2.73 ± 0.732, p=0.027). Bard's responses had better readability than ChatGPT-4 (2.79 ± 0.408 vs 2.94 ± 0.243, p=0.003). Both ChatGPT-4 and Bard achieved comparable conciseness scores (3.14 ± 0.659 vs 3.11 ± 0.679, p=0.798). Experts categorized the AI-generated responses as incorrect or partially correct at a rate of 16.6% for ChatGPT-4 and 29.1% for Bard. Bard's answers contained significantly more misleading information than those of ChatGPT-4 (p = 0.039). Conclusion: AI chatbots have gained significant attention, and their performance is continuously improving. Nonetheless, these technologies still need further improvements to be considered reliable and credible sources for patients seeking medical information on 177Lu-PSMA-617 therapy.

Theranostics and artificial intelligence: new frontiers in personalized medicine.

The field of theranostics is rapidly advancing, driven by the goals of enhancing patient care. Recent breakthroughs in artificial intelligence (AI) and its innovative theranostic applications have marked a critical step forward in nuclear medicine, leading to a significant paradigm shift in precision oncology. For instance, AI-assisted tumor characterization, including automated image interpretation, tumor segmentation, feature identification, and prediction of high-risk lesions, improves diagnostic processes, offering a precise and detailed evaluation. With a comprehensive assessment tailored to an individual's unique clinical profile, AI algorithms promise to enhance patient risk classification, thereby benefiting the alignment of patient needs with the most appropriate treatment plans. By uncovering potential factors unseeable to the human eye, such as intrinsic variations in tumor radiosensitivity or molecular profile, AI software has the potential to revolutionize the prediction of response heterogeneity. For accurate and efficient dosimetry calculations, AI technology offers significant advantages by providing customized phantoms and streamlining complex mathematical algorithms, making personalized dosimetry feasible and accessible in busy clinical settings. AI tools have the potential to be leveraged to predict and mitigate treatment-related adverse events, allowing early interventions. Additionally, generative AI can be utilized to find new targets for developing novel radiopharmaceuticals and facilitate drug discovery. However, while there is immense potential and notable interest in the role of AI in theranostics, these technologies do not lack limitations and challenges. There remains still much to be explored and understood. In this study, we investigate the current applications of AI in theranostics and seek to broaden the horizons for future research and innovation.

Evaluation of Neurodegenerative Disorders with Amyloid-ß, Tau, and Dopaminergic PET Imaging: Interpretation Pitfalls.

Antiamyloid therapies for Alzheimer disease recently entered clinical practice, making imaging biomarkers for Alzheimer disease even more relevant to guiding patient management. Amyloid and tau PET are valuable tools that can provide objective evidence of Alzheimer pathophysiology in living patients and will increasingly be used to complement 18F-FDG PET in the diagnostic evaluation of cognitive impairment and dementia. Parkinsonian syndromes, also common causes of dementia, can likewise be evaluated with a PET imaging biomarker,18F-DOPA, allowing in vivo assessment of the presynaptic dopaminergic neurons. Understanding the role of these PET biomarkers will help the nuclear medicine physician contribute to the appropriate diagnosis and management of patients with cognitive impairment and dementia. To successfully evaluate brain PET examinations for neurodegenerative diseases, knowledge of the necessary protocol details for obtaining a reliable imaging study, inherent limitations for each PET radiopharmaceutical, and pitfalls in image interpretation is critical. This review will focus on underlying concepts for interpreting PET examinations, important procedural details, and guidance for avoiding potential interpretive pitfalls for amyloid, tau, and dopaminergic PET examinations.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning.

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Clinical practice in prostate PET imaging.

Positron emission tomography (PET) imaging in prostate cancer has advanced significantly in the past decade with prostate cancer targeted radiopharmaceuticals now playing a growing role in diagnosis, staging, and treatment. This narrative review focuses on the most commonly used PET radiopharmaceuticals in the USA: prostate-specific membrane antigen (PSMA), fluciclovine, and choline. 18F-fluorodeoxyglucose (FDG) is used in many other malignancies, but rarely in prostate cancer. Previous literature is discussed regarding each radiopharmaceutical's utility in the settings of screening/diagnosis, initial staging, biochemical recurrence, advanced disease, and evaluation prior to targeted radiopharmaceutical therapy and radiation therapy. PET imaging has demonstrated utility over traditional imaging in various scenarios; however, there are few head-to-head studies comparing PET radiopharmaceuticals. PSMA radiopharmaceuticals are the newest tracers developed and have unique properties and uses, especially at low prostate-specific antigen (PSA) levels. However, each PET radiopharmaceutical has different properties which can affect image interpretation. Choline and fluciclovine have minimal urinary activity, whereas PSMA agents can have high urinary activity which may affect locoregional disease evaluation. Of the three radiopharmaceuticals, only PSMA is approved for both diagnostic and therapeutic indications with 177Lu-PSMA. A variety of diagnostic PET radiotracers for prostate cancer allows for increased flexibility, especially in the setting of supply chain and medication shortages. For the time being, keeping a diverse group of PET radiopharmaceuticals for prostate cancer is justifiable.

Anti-LGI1 Autoimmune Epilepsy.

ABSTRACT: Leucine-rich glioma inactivated 1 autoimmune encephalitis is a treatable cause of autoimmune epilepsy associated with faciobrachial dystonic seizures-a rare form of epilepsy with frequent brief seizures primarily affecting the arm and face. We report a case with characteristic imaging findings. 18 F-FDG PET/CT demonstrated severe hypometabolism in the left basal ganglia, a regional abnormality associated with leucine-rich glioma inactivated 1 encephalitis.

PET and SPECT Imaging of ALS: An Educational Review.

Amyotrophic lateral sclerosis (ALS) is a disease leading to progressive motor degeneration and ultimately death. It is a complex disease that can take a significantly long time to be diagnosed, as other similar pathological conditions must be ruled out for a definite diagnosis of ALS. Noninvasive imaging of ALS has shed light on disease pathology and altered biochemistry in the ALS brain. Other than magnetic resonance imaging (MRI), two types of functional imaging, positron emission tomography (PET) and single photon emission computed tomography (SPECT), have provided valuable data about what happens in the brain of ALS patients compared to healthy controls. PET imaging has revealed a specific pattern of brain metabolism through [18F]FDG, while other radiotracers have uncovered neuroinflammation, changes in neuronal density, and protein aggregation. SPECT imaging has shown a general decrease in regional cerebral blood flow (rCBF) in ALS patients. This educational review summarizes the current state of ALS imaging with various PET and SPECT radiopharmaceuticals to better understand the pathophysiology of ALS.

A Review of Theranostics: Perspectives on Emerging Approaches and Clinical Advancements.

Theranostics is the combination of two approaches-diagnostics and therapeutics-applied for decades in cancer imaging using radiopharmaceuticals or paired radiopharmaceuticals to image and selectively treat various cancers. The clinical use of theranostics has increased in recent years, with U.S. Food and Drug Administration (FDA) approval of lutetium 177 (177Lu) tetraazacyclododecane tetraacetic acid octreotate (DOTATATE) and 177Lu-prostate-specific membrane antigen vector-based radionuclide therapies. The field of theranostics has imminent potential for emerging clinical applications. This article reviews critical areas of active clinical advancement in theranostics, including forthcoming clinical trials advancing FDA-approved and emerging radiopharmaceuticals, approaches to dosimetry calculations, imaging of different radionuclide therapies, expanded indications for currently used theranostic agents to treat a broader array of cancers, and emerging ideas in the field. Keywords: Molecular Imaging, Molecular Imaging-Cancer, Molecular Imaging-Clinical Translation, Molecular Imaging-Target Development, PET/CT, SPECT/CT, Radionuclide Therapy, Dosimetry, Oncology, Radiobiology © RSNA, 2023.

Absent Stapedial Tendon: Imaging Features of an Underrecognized Entity : Clinical Neuroradiology.

PURPOSE: Congenital absence of the stapedial tendon is a rare entity with characteristic imaging findings, which can go unrecognized due the scarcity of the diagnosis and limited previous description in the imaging literature. We aim to characterize the imaging features of this entity. METHODS: A series of 9 cases with surgical confirmation of stapedial tendon absence were retrospectively reviewed and the most common abnormalities on high resolution computed tomography (CT) of the temporal bone described. RESULTS: Congenital fixation of the stapes footplate was present in nearly all cases of stapedial tendon absence (n = 8, 89%), a clinically important association because the stapes footplate abnormality was not detectable on preoperative CT. Absence or hypoplasia of the pyramidal eminence and aperture was identified in almost all cases (n = 8, 89%), which may be the sole imaging finding to suggest stapedial tendon absence and associated stapes footplate fixation prior to surgery. CONCLUSION: The most reliable indicator of stapedial muscle absence on temporal bone CT is the absence or hypoplasia of the pyramidal eminence and aperture. Importantly, most patients had congenital stapes footplate fixation confirmed intraoperatively with a normal stapes footplate on CT, meaning the pyramidal eminence/aperture abnormality was the only preoperative imaging finding that could have suggested the footplate fixation.

Infrapedicular approach to CT-guided thermal ablation in the thoracic spine.

OBJECTIVES: The aim of this study is to introduce the infrapedicular approach to CT-guided spine interventions, a specialized technique that can safely expand the scope of spine lesions amenable to treatment, and to document the feasibility in a variety of procedural scenarios to the extent possible with a retrospective case series. METHODS: Data from 24 cases performed at a single institution over a 10-year period were retrospectively reviewed to assess the technical feasibility and safety profile of the technique. RESULTS: The infrapedicular approach enabled a technically satisfactory procedural result in 24 cases (mean age 63.9 years, range 35-83 years). Two peri-procedural complications occurred, including a small pneumothorax and a cerebrospinal fluid leak, both of which resolved with conservative treatment. No lasting injurious effects or additional complications were identified. The infrapedicular approach was found to be particularly useful in multiple technically challenging scenarios: it facilitates access to lesions in the inferior vertebral body, allows biopsy, cement augmentation, or ablation of high thoracic lesions difficult to treat due to limitations of steep angulation of fluoroscopy and CT scanners, and enables treatment of large lesions by using multiple overlapping probes.

PET Imaging of Dementia: Update 2022.

ABSTRACT: PET imaging plays an essential role in achieving earlier and more specific diagnoses of dementia syndromes, important for clinical prognostication and optimal medical management. This has become especially vital with the recent development of pathology-specific disease-modifying therapy for Alzheimer disease, which will continue to evolve and require methods to select appropriate treatment candidates. Techniques that began as research tools such as amyloid and tau PET have now entered clinical use, making nuclear medicine physicians and radiologists essential members of the care team. This review discusses recent changes in the understanding of dementia and examines the roles of nuclear medicine imaging in clinical practice. Within this framework, multiple cases will be shown to illustrate a systematic approach of FDG PET interpretation and integration of PET imaging of specific molecular pathology including dopamine transporters, amyloid, and tau. The approach presented here incorporates contemporary understanding of both common and uncommon dementia syndromes, intended as an updated practical guide to assist with the sophisticated interpretation of nuclear medicine examinations in the context of this rapidly and continually developing area of imaging.

The Overlap Index as a Means of Evaluating Early Tau PET Signal Reliability.

In tau PET, a reliable method to detect early tau accumulation in the brain is crucial. Noise, artifacts, and off-target uptake impede detection of subtle true-positive ligand binding. We hypothesize that identifying voxels with stable activity over time can enhance detection of true-positive tau. Methods: In total, 339 participants in the clinical spectrum ranging from clinically unimpaired to Alzheimer disease dementia underwent at least 2 serial tau PET scans with flortaucipir. The overlap index (OI) method was proposed to detect spatially identical, voxelwise SUV ratio (SUVR) elevation when seen sequentially in serial tau PET scans. The association of OI with tau accumulation, clinical diagnosis, and cognitive findings was evaluated. Results: OI showed good dynamic range in the low-SUVR window. Only OI was able to identify subgroups with increasing tau PET signal in low-SUVR meta-region-of-interest (ROI) groups. OI showed improved association with early clinical disease progression and cognitive scores versus meta-ROI SUVR measures. Conclusion: OI was more sensitive to tau signal elevation and longitudinal change than standard ROI measures, suggesting it is a more sensitive method for detecting early, subtle deposition of neurofibrillary tangles.

Deep learning-based brain age prediction in normal aging and dementia.

Brain aging is accompanied by patterns of functional and structural change. Alzheimer's disease (AD), a representative neurodegenerative disease, has been linked to accelerated brain aging. Here, we developed a deep learning-based brain age prediction model using a large collection of fluorodeoxyglucose positron emission tomography and structural magnetic resonance imaging and tested how the brain age gap relates to degenerative syndromes including mild cognitive impairment, AD, frontotemporal dementia and Lewy body dementia. Occlusion analysis, performed to facilitate the interpretation of the model, revealed that the model learns an age- and modality-specific pattern of brain aging. The elevated brain age gap was highly correlated with cognitive impairment and the AD biomarker. The higher gap also showed a longitudinal predictive nature across clinical categories, including cognitively unimpaired individuals who converted to a clinical stage. However, regions generating brain age gaps were different for each diagnostic group of which the AD continuum showed similar patterns to normal aging.

Time-crystalline eigenstate order on a quantum processor.

Quantum many-body systems display rich phase structure in their low-temperature equilibrium states1. However, much of nature is not in thermal equilibrium. Remarkably, it was recently predicted that out-of-equilibrium systems can exhibit novel dynamical phases2-8 that may otherwise be forbidden by equilibrium thermodynamics, a paradigmatic example being the discrete time crystal (DTC)7,9-15. Concretely, dynamical phases can be defined in periodically driven many-body-localized (MBL) systems via the concept of eigenstate order7,16,17. In eigenstate-ordered MBL phases, the entire many-body spectrum exhibits quantum correlations and long-range order, with characteristic signatures in late-time dynamics from all initial states. It is, however, challenging to experimentally distinguish such stable phases from transient phenomena, or from regimes in which the dynamics of a few select states can mask typical behaviour. Here we implement tunable controlled-phase (CPHASE) gates on an array of superconducting qubits to experimentally observe an MBL-DTC and demonstrate its characteristic spatiotemporal response for generic initial states7,9,10. Our work employs a time-reversal protocol to quantify the impact of external decoherence, and leverages quantum typicality to circumvent the exponential cost of densely sampling the eigenspectrum. Furthermore, we locate the phase transition out of the DTC with an experimental finite-size analysis. These results establish a scalable approach to studying non-equilibrium phases of matter on quantum processors.