Molecular Imaging and Precision Medicine: PET/Computed Tomography and Therapy Response Assessment in Oncology

Development of Dual Receptor Enhanced Pre-Targeting Strategy-A Novel Promising Technology for Immuno-Positron Emission Tomography Imaging

PET imaging has become an important diagnostic tool in the era of precise medicine. Various pre-targeting systems have been reported to address limitations associated with traditional immuno-PET. However, the application of these mono-receptor based pre-targeting (MRPT) strategies is limited to non-internalizable antibodies, and the tumor uptake is usually much lower than that in the corresponding immuno-PET. To circumvent these limitations, we develop the first Dual-Receptor Pre-Targeting (DRPT) system through entrapping the tumor-receptor-specific radioligand by the pre-administered antibody. Besides the similar ligation pathway happens in MRPT, incorporation of a tumor-receptor-specific peptide into the radioligand in DRPT enhances both concentration and retention of the radioligand on tumor, promoting its ligation with pre-administered mAb on cell-surface and/or internalized into tumor-cells. In this study, 64Cu based DRPT shows superior performance over corresponding MRPT and immuno-PET using internalizable antibodies. Besides, the compatibility of DRPT with short-lived and generator-produced 68Ga is demonstrated, leveraging its advantage in reducing radio-dose exposure. Furthermore, the feasibility of reducing the amount of the pre-administered antibody is confirmed, indicating the cost saving potential of DRPT. In summary, synergizing advantages of dual-receptor targeting and pre-targeting, we expect that this DRPT strategy can become a breakthrough technology in the field of antibody-based molecular imaging.

Applications of artificial intelligence in oncologic 18F-FDG PET/CT imaging: a systematic review

Artificial intelligence (AI) is a growing field of research that is emerging as a promising adjunct to assist physicians in detection and management of patients with cancer. ¹⁸F-FDG PET imaging helps physicians in detection and management of patients with cancer. In this study we discuss the possible applications of AI in ¹⁸F-FDG PET imaging based on the published studies. A systematic literature review was performed in PubMed on early August 2020 to find the relevant studies. A total of 65 studies were available for review against the inclusion criteria which included studies that developed an AI model based on 18F-FDG PET data in cancer to diagnose, differentiate, delineate, stage, assess response to therapy, determine prognosis, or improve image quality. Thirty-two studies met the inclusion criteria and are discussed in this review. The majority of studies are related to lung cancer. Other studied cancers included breast cancer, cervical cancer, head and neck cancer, lymphoma, pancreatic cancer, and sarcoma. All studies were based on human patients except for one which was performed on rats. According to the included studies, machine learning (ML) models can help in detection, differentiation from benign lesions, segmentation, staging, response assessment, and prognosis determination. Despite the potential benefits of AI in cancer imaging and management, the routine implementation of AI-based models and ¹⁸F-FDG PET-derived radiomics in clinical practice is limited at least partially due to lack of standardized, reproducible, generalizable, and precise techniques.

It's About Quality, Not Quantity: Qualitative FDG PET/CT Criteria for Therapy Response Assessment in Clinical Practice

OBJECTIVE. FDG PET/CT has emerged as an effective tool for the timely accurate assessment of how tumors respond to therapy. To standardize interpretation and reporting, numerous response criteria have been developed. This article will review the evolution of these criteria along with their strengths and weaknesses. CONCLUSION. Several qualitative assessments applicable to common malignancies have been developed in recent years that solve many of the challenges faced by their quantitative predecessors. These are reviewed, and information is provided regarding individual treatment efficacy and prognosis.

RESISTing the Need to Quantify: Putting Qualitative FDG-PET/CT Tumor Response Assessment Criteria into Daily Practice

Tumor response assessments are essential to evaluate cancer treatment efficacy and prognosticate survival in patients with cancer. Response criteria have evolved over multiple decades, including many imaging modalities and measurement schema. Advances in FDG-PET/CT have led to tumor response criteria that harness the power of metabolic imaging. Qualitative PET/CT assessment schema are easy to apply clinically, are reproducible, and yield good prognostic results. We present 3 such criteria, namely, the Lugano classification for lymphoma, the Hopkins criteria, and the Neck Imaging Reporting and Data Systems criteria for head and neck cancers. When comparing baseline PET/CTs with interim or end-of-treatment PET/CTs, radiologists can classify the tumor response as complete metabolic response, partial metabolic response, no metabolic response, or progressive disease, which has important implications in directing further cancer management and long-term patient prognosis. The purpose of this article is to review the progression of tumor response assessments from CT- and PET/CT-based quantitative and semi-quantitative systems to PET/CT-based qualitative systems; introduce the classification schema for these systems; and describe how to use these rapid, powerful, and qualitative PET/CT-based systems in daily practice through illustrative cases.

Feasibility of 18F-FDG Dose Reductions in Breast Cancer PET/MRI

The goal of this study was to determine the level of clinically acceptable ¹⁸F-FDG dose reduction in time-of-flight PET/MRI in patients with breast cancer. Methods: Twenty-six consecutive women with histologically proven breast cancer were analyzed (median age, 51 y; range, 34-83 y). Simulated dose-reduced PET images were generated by unlisting the list-mode data on PET/MRI. The acquired 20-min PET frame was reconstructed in 5 ways: a reconstruction of the first 2 min with 3 iterations and 28 subsets for reference, and reconstructions simulating 100%, 20%, 10%, and 5% of the original dose. General image quality and artifacts, image sharpness, image noise, and lesion detectability were analyzed using a 4-point scale. Qualitative parameters were compared using the nonparametric Friedman test for multiple samples and the Wilcoxon signed-rank test for paired samples. Different groups of independent samples were compared using the Mann-Whitney U test. Results: Overall, 355 lesions (71 lesions with 5 different reconstructions each) were evaluated. The 20-min reconstruction with 100% injected dose showed the best results in all categories. For general image quality and artifacts, image sharpness, and noise, the reconstructions with a simulated dose of 20% and 10% were significantly better than the 2-min reconstructions (P ≤ 0.001). Furthermore, 20%, 10%, and 5% reconstructions did not yield results different from those of the 2-min reconstruction for detectability of the primary lesion. For 10% of the injected dose, a calculated mean dose of 22.6 ± 5.5 MBq (range, 17.9-36.9 MBq) would have been applied, resulting in an estimated whole-body radiation burden of 0.5 ± 0.1 mSv (range, 0.4-0.7 mSv). Conclusion: Ten percent of the standard dose of ¹⁸F-FDG (reduction of ≤90%) results in clinically acceptable PET image quality in time-of-flight PET/MRI. The calculated radiation exposure would be comparable to the effective dose of a single digital mammogram. A reduction of radiation burden to this level might justify partial-body examinations with PET/MRI for dedicated indications.

Automated One-pot Radiosynthesis of [11C]S-adenosyl Methionine

BACKGROUND

Glycine N-methyltransferase is an enzyme overexpressed in some neoplastic tissues. It catalyses the methylation of glycine using S-adenosyl methionine (SAM or AdoMet) as substrate. SAM is involved in a great variety of biochemical processes, including transmethylation reactions. Thus, [11C]SAM could be used to evaluate transmethylation activity in tumours. The only method reported for [11C]SAM synthesis is an enzymatic process with several limitations. We propose a new chemical method to obtain [11C]SAM, through a one-pot synthesis.

METHOD

The optimization of [11C]SAM synthesis was carried out in the automated TRACERlab® FX C Pro module. Different labelling conditions were performed varying methylating agent, precursor amount, temperature and reaction time. The compound was purified using a semipreparative HPLC. Radiochemical stability, lipophilicity and plasma protein binding were evaluated.

RESULTS

The optimum labelling conditions were [11C]CH3OTf as the methylating agent, 5 mg of precursor dissolved in formic acid at 60 °C for 1 minute. [11C]SAM was obtained as a diastereomeric mixture. Three batches were produced and quality control was performed according to specifications. [11C]SAM was stable in final formulation and in plasma. Log POCT obtained for [11C]SAM was (-2,01 ± 0,07) (n=4), and its value for plasma protein binding was low.

CONCLUSION

A new chemical method to produce [11C]SAM was optimized. The radiotracer was obtained as a diastereomeric mixture with a 53:47 [(R,S)-isomer: (S,S)-isomer] ratio. The compound was within the quality control specifications. In vitro stability was verified. This compound is suitable to perform preclinical and clinical evaluations.

EDB Fibronectin-Specific SPECT Probe 99mTc-HYNIC-ZD2 for Breast Cancer Detection

Extradomain-B fibronectin (EDB-FN), an oncofetal isoform of FN, is a promising diagnostic and therapeutic target of tumors, including breast cancer. Many EDB-FN-targeted drugs have been developed and have shown therapeutic effects in clinical trials. Molecular imaging to visualize EDB-FN-positive cancers may help select the right patients who will be benefit from EDB-FN-targeted therapy. Although a few EDB-FN-targeted imaging probes have been developed, the complicated manufacturing procedure and expensive material and equipment required limit their application for large-scale screening of EDB-FN-positive cancer patients. Thus, more simple and economic EDB-FN-targeted imaging probes are still urgently needed. Previously, we have identified a breast cancer-targeted peptide, CTVRTSADC. Coincidently, it was later identified as an EDB-FN-targeted peptide and named ZD2. In this study, we found a positive correlation between the binding activity of the ZD2 phage and the expression level of EDB-FN in breast cancer cells. Moreover, we observed the colocalization of the ZD2 peptide with EDB-FN in breast cancer cells. Furthermore, in vivo tumor targeting of the ZD2 phage, near-infrared fluorescence imaging, and flow cytometry showed tumor-specific homing of the ZD2 peptide in mice bearing EDB-FN-positive breast cancers. Importantly, on the basis of this EDB-FN-targeted ZD2 peptide, we developed a kit-formulated probe, ^99mTc-HYNIC-ZD2, for single-photon-emission computed tomography (SPECT) imaging of breast cancer. The high tumor uptake of ^99mTc-HYNIC-ZD2 demonstrated its feasibility for use in visualizing EDB-FN-positive breast cancers in vivo. This kit-formulated EDB-FN-targeted SPECT probe has potential clinical applications for precision screening of EDB-FN-positive cancer patients who may benefit from EDB-FN-targeted therapy.