A review of 177Lu dosimetry workflows: how to reduce the imaging workloads?

radiopharmaceutical therapy is a standardized systemic treatment, with a typical dose of 7.4 GBq per injection, but its response varies from patient to patient. Dosimetry provides the opportunity to personalize treatment, but it requires multiple post-injection images to monitor the radiopharmaceutical's biodistribution over time.

An International Study of Factors Affecting Variability of Dosimetry Calculations, Part 3: Contribution from Calculating Absorbed Dose from Time-Integrated Activity.

Image-based dosimetry-guided radiopharmaceutical therapy has the potential to personalize treatment by limiting toxicity to organs at risk and maximizing the therapeutic effect. The Lu dosimetry challenge of the Society of Nuclear Medicine and Molecular Imaging consisted of 5 tasks assessing the variability in the dosimetry workflow. The fifth task investigated the variability associated with the last step, dose conversion, of the dosimetry workflow on which this study is based.

PET/CT-Based Absorbed Dose Maps in Y Selective Internal Radiation Therapy Correlate with Spatial Changes in Liver Function Derived from Dynamic MRI.

Functional liver parenchyma can be damaged from treatment of liver malignancies with Y selective internal radiation therapy (SIRT). Evaluating functional parenchymal changes and developing an absorbed dose (AD)-toxicity model can assist the clinical management of patients receiving SIRT. We aimed to determine whether there is a correlation between Y PET AD voxel maps and spatial changes in the nontumoral liver (NTL) function derived from dynamic gadoxetic acid-enhanced MRI before and after SIRT.

SPECT/CT Image-Derived Absorbed Dose to Red Marrow Correlates with Hematologic Toxicity in Patients Treated with [Lu]Lu-DOTATATE.

Hematologic toxicity, although often transient, is the most common limiting adverse effect during somatostatin peptide receptor radionuclide therapy. This study investigated the association between Monte Carlo-derived absorbed dose to the red marrow (RM) and hematologic toxicity in patients being treated for their neuroendocrine tumors. Twenty patients each receiving 4 treatment cycles of [Lu]Lu-DOTATATE were included.

Linear Boltzmann equation solver for voxel-level dosimetry in radiopharmaceutical therapy: Comparison with Monte Carlo and kernel convolution.

Background: With recent interest in patient-specific dosimetry for radiopharmaceutical therapy (RPT) and selective internal radiation therapy (SIRT), an increasing number of voxel-based algorithms are being evaluated. Monte Carlo (MC) radiation transport, generally considered to be the most accurate among different methods for voxel-level absorbed dose estimation, can be computationally inefficient for routine clinical use.

Purpose: This work demonstrates a recently implemented grid-based linear Boltzmann transport equation (LBTE) solver for fast and accurate voxel-based dosimetry in RPT and SIRT and benchmarks it against MC.

90Y SPECT scatter estimation and voxel dosimetry in radioembolization using a unified deep learning framework.

Purpose: 90Y SPECT-based dosimetry following radioembolization (RE) in liver malignancies is challenging due to the inherent scatter and the poor spatial resolution of bremsstrahlung SPECT. This study explores a deep-learning-based absorbed dose-rate estimation method for 90Y that mitigates the impact of poor SPECT image quality on dosimetry and the accuracy-efficiency trade-off of Monte Carlo (MC)-based scatter estimation and voxel dosimetry methods.

Methods: Our unified framework consists of three stages: convolutional neural network (CNN)-based bremsstrahlung scatter estimation, SPECT reconstruction with scatter correction (SC) and absorbed dose-rate map generation with a residual learning network (DblurDoseNet).

Single-Time-Point Imaging for Dosimetry After [Lu]Lu-DOTATATE: Accuracy of Existing Methods and Novel Data-Driven Models for Reducing Sensitivity to Time-Point Selection.

Estimation of the time-integrated activity (TIA) for dosimetry from imaging at a single time point (STP) facilitates the clinical translation of dosimetry-guided radiopharmaceutical therapy. However, the accuracy of the STP methods for TIA estimation varies on the basis of time-point selection. We constructed patient data-driven regression models to reduce the sensitivity to time-point selection and to compare these new models with commonly used STP methods.

Accuracy and uncertainty analysis of reduced time point imaging effect on time-integrated activity for Lu-DOTATATE PRRT in patients and clinically realistic simulations.

Background: Dosimetry promises many advantages for radiopharmaceutical therapies but repeat post-therapy imaging for dosimetry can burden both patients and clinics. Recent applications of reduced time point imaging for time-integrated activity (TIA) determination for internal dosimetry following Lu-DOTATATE peptide receptor radionuclide therapy have shown promising results that allow for the simplification of patient-specific dosimetry. However, factors such as scheduling can lead to sub-optimal imaging time points, but the resulting impact on dosimetry accuracy is still under investigation.

The predictive value of pretherapy [Ga]Ga-DOTA-TATE PET and biomarkers in [Lu]Lu-PRRT tumor dosimetry.

Purpose: Metastatic neuroendocrine tumors (NETs) overexpressing type 2 somatostatin receptors are the target for peptide receptor radionuclide therapy (PRRT) through the theragnostic pair of Ga/Lu-DOTATATE. The main purpose of this study was to develop machine learning models to predict therapeutic tumor dose using pre therapy Ga -PET and clinicopathological biomarkers.

Methods: We retrospectively analyzed 90 segmented metastatic NETs from 25 patients (M14/F11, age 63.

Accuracy and uncertainty analysis of reduced time point imaging effect on time-integrated activity for 177Lu-DOTATATE PRRT in clinical patients and realistic simulations.

Dosimetry promises many advantages for radiopharmaceutical therapies but repeat post-therapy imaging for dosimetry can burden both patients and clinics. Recent applications of reduced time point imaging for time-integrated activity (TIA) determination for internal dosimetry following Lu-DOTATATE peptide receptor radionuclide therapy have shown promising results that allow for the simplification of patient-specific dosimetry. However, factors such as scheduling can lead to undesirable imaging time points, but the resulting impact on dosimetry accuracy is unknown.

Physics-Guided Deep Scatter Estimation by Weak Supervision for Quantitative SPECT.

Accurate scatter estimation is important in quantitative SPECT for improving image contrast and accuracy. With a large number of photon histories, Monte-Carlo (MC) simulation can yield accurate scatter estimation, but is computationally expensive. Recent deep learning-based approaches can yield accurate scatter estimates quickly, yet full MC simulation is still required to generate scatter estimates as ground truth labels for all training data.

An International Study of Factors Affecting Variability of Dosimetry Calculations, Part 2: Overall Variabilities in Absorbed Dose.

Dosimetry for personalized radiopharmaceutical therapy has gained considerable attention. Many methods, tools, and workflows have been developed to estimate absorbed dose (AD). However, standardization is still required to reduce variability of AD estimates across centers.

Training End-to-End Unrolled Iterative Neural Networks for SPECT Image Reconstruction.

Training end-to-end unrolled iterative neural networks for SPECT image reconstruction requires a memory-efficient forward-backward projector for efficient backpropagation. This paper describes an open-source, high performance Julia implementation of a SPECT forward-backward projector that supports memory-efficient backpropagation with an exact adjoint. Our Julia projector uses only ~5% of the memory of an existing Matlab-based projector.

177Lu-DOTATATE Theranostics: Predicting Renal Dosimetry From Pretherapy 68Ga-DOTATATE PET and Clinical Biomarkers.

Purpose: Pretreatment predictions of absorbed doses can be especially valuable for patient selection and dosimetry-guided individualization of radiopharmaceutical therapy. Our goal was to build regression models using pretherapy 68Ga-DOTATATE PET uptake data and other baseline clinical factors/biomarkers to predict renal absorbed dose delivered by 177Lu-DOTATATE peptide receptor radionuclide therapy (177Lu-PRRT) for neuroendocrine tumors. We explore the combination of biomarkers and 68Ga PET uptake metrics, hypothesizing that they will improve predictive power over univariable regression.

Stereotactic body radiation therapy (SBRT) following Yttrium-90 (Y) selective internal radiation therapy (SIRT): a feasibility planning study usingY delivered dose.

.Y selective internal radiation therapy (SIRT) treatment of hepatocellular carcinoma (HCC) can potentially underdose lesions, as identified on post-therapy PET/CT imaging. This study introduces a methodology and explores the feasibility for selectively treating SIRT-underdosed HCC lesions, or lesion subvolumes, with stereotactic body radiation therapy (SBRT) following post-SIRT dosimetry.

SPECT reconstruction with a trained regularizer using CT-side information: Application to Lu SPECT imaging.

Improving low-count SPECT can shorten scans and support pre-therapy theranostic imaging for dosimetry-based treatment planning, especially with radionuclides like Lu known for low photon yields. Conventional methods often underperform in low-count settings, highlighting the need for trained regularization in model-based image reconstruction. This paper introduces a trained regularizer for SPECT reconstruction that leverages segmentation based on CT imaging.

Intra- and inter-operator variability in MRI-based manual segmentation of HCC lesions and its impact on dosimetry.

Purpose: The aim was to quantify inter- and intra-observer variability in manually delineated hepatocellular carcinoma (HCC) lesion contours and the resulting impact on radioembolization (RE) dosimetry.

Methods: Ten patients with HCC lesions treated with Y-90 RE and imaged with post-therapy Y-90 PET/CT were selected for retrospective analysis. Three radiologists contoured 20 lesions manually on baseline multiphase contrast-enhanced MRIs, and two of the radiologists re-contoured at two additional sessions.

A Multicenter Study on Observed Discrepancies Between Vendor-Stated and PET-Measured Y Activities for Both Glass and Resin Microsphere Devices.

Dosimetry-guided treatment planning in selective internal radiation therapy relies on accurate and reproducible measurement of administered activity. This 4-center, 5-PET-device study compared the manufacturer-declared Y activity in vials with quantitative Y PET/CT assessment of the same vials. We compared Y PET-measured activity (A) for 56 Y-labeled glass and 18 Y-labeled resin microsphere vials with the calibrated activity specified by the manufacturer (A).

Advanced imaging and theranostics in thyroid cancer.

Purpose Of Review: Thyroid cancers are endocrine neoplasms with diverse gene expression and behavior, for which constantly evolving anatomic and functional imaging/theranostic agents have an essential role for diagnosis, staging, and treatment.

Recent Findings: To achieve definitive diagnosis, neck ultrasound and associated risk stratification systems, notably Thyroid Imaging Reporting and Data System (TI-RADS), allow improved thyroid nodule characterization and management guidance. Radioactive iodine-131 (RAI) has long played a role in management of differentiated thyroid cancer (DTC), with recent literature emphasizing its effectiveness for intermediate-high risk cancers, exploring use of dosimetry for personalized medicine, and potential for retreatment with RAI following tumor redifferentiation.

Experimental validation of Monte Carlo dosimetry for therapeutic beta emitters with radiochromic film in a 3D-printed phantom.

Purpose: Validation of dosimetry software, such as Monte Carlo (MC) radiation transport codes used for patient-specific absorbed dose estimation, is critical prior to their use in clinical decision making. However, direct experimental validation in the clinic is generally not performed for low/medium-energy beta emitters used in radiopharmaceutical therapy (RPT) due to the challenges of measuring energy deposited by short-range particles. Our objective was to design a practical phantom geometry for radiochromic film (RF)-based absorbed dose measurements of beta-emitting radionuclides and perform experiments to directly validate our in-house developed Dose Planning Method (DPM) MC code dedicated to internal dosimetry.

Differences in tumor-to-normal organ SUV ratios measured with 68 Ga-DOTATATE PET compared with 177 Lu-DOTATATE SPECT in patients with neuroendocrine tumors.

Background: Our goal is to quantitatively compare radiotracer biodistributions within tumors and major normal organs on pretherapy 68 Ga-DOTATATE PET to post-therapy 177 Lu-DOTATATE single-photon emission computed tomography (SPECT) in patients receiving peptide receptor radionuclide therapy (PRRT).

Methods: PET/CT at ~ 60 min postinjection of Ga-68 DOTATATE and research 177 Lu-SPECT/CT imaging ~ at 4 h (SPECT1) and ~ 24 h (SPECT2) post-cycle#1 were available. Manual contours of lesions on baseline CT or MRI were applied to co-registered SPECT/CT and PET/CT followed by deep learning-based CT auto-segmentation of organs.

A Pipeline for Automated Voxel Dosimetry: Application in Patients with Multi-SPECT/CT Imaging After Lu-Peptide Receptor Radionuclide Therapy.

Patient-specific dosimetry in radiopharmaceutical therapy (RPT) is impeded by the lack of tools that are accurate and practical for the clinic. Our aims were to construct and test an integrated voxel-level pipeline that automates key components (organ segmentation, registration, dose-rate estimation, and curve fitting) of the RPT dosimetry process and then to use it to report patient-specific dosimetry in Lu-DOTATATE therapy. An integrated workflow that automates the entire dosimetry process, except tumor segmentation, was constructed.