Toward PET/MRI as one-stop shop for radiotherapy planning in cervical cancer patients

Precision matters: the value of PET/CT and PET/MRI in the clinical management of cervical cancer

The incidence of cervical cancer has been increasing recently, becoming an essential factor threatening patients' health. Positron emission computed tomography (PET/CT) and positron emission tomography/magnetic resonance imaging (PET/MRI) are multimodal molecular imaging methods that combine functional imaging (PET) and anatomical imaging (CT) with MRI fusion technology. They play an important role in the clinical management of patients with cervical cancer. Precision radiotherapy refers to the use of advanced intensive modulated radiotherapy (IMRT) to give different doses of radiation to different treatment areas to achieve the purpose of killing tumors and protecting normal tissues to the greatest extent. At present, pelvic target delineation is mostly based on CT and MRI, but these mostly provide anatomical morphological information, which is difficult to show the internal metabolism of tumors. PET/CT and PET/MRI combine information on biological function, metabolism and anatomical structure, thereby more accurately distinguishing the boundaries between tumor and non-tumor tissues and playing a positive guiding role in improving radiotherapy planning (RTP) for cervical cancer and evaluating treatment effect.

Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic resonance only radiotherapy

Synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI) can serve as a substitute for planning CT in radiation therapy (RT), thereby removing registration uncertainties associated with multi-modality imaging pairing, reducing costs and patient radiation exposure. CE/FDA-approved sCT solutions are nowadays available for pelvis, brain, and head and neck, while more complex deep learning (DL) algorithms are under investigation for other anatomic sites. The main challenge in achieving a widespread clinical implementation of sCT lies in the absence of consensus on sCT commissioning and quality assurance (QA), resulting in variation of sCT approaches across different hospitals. To address this issue, a group of experts gathered at the ESTRO Physics Workshop 2022 to discuss the integration of sCT solutions into clinics and report the process and its outcomes. This position paper focuses on aspects of sCT development and commissioning, outlining key elements crucial for the safe implementation of an MRI-only RT workflow.

Improved Positron Emission Tomography Quantification: Evaluation of a Maximum-Likelihood Scatter Scaling Algorithm

Incorrect scatter scaling of positron emission tomography (PET) images can lead to halo artifacts, quantitative bias, or reconstruction failure. Tail-fitted scatter scaling (TFSS) possesses performance limitations in multiple cases. This study aims to investigate a novel method for scatter scaling: maximum-likelihood scatter scaling (MLSS) in scenarios where TFSS tends to induce artifacts or are observed to cause reconstruction abortion. [68Ga]Ga-RGD PET scans of nine patients were included in cohort 1 in the scope of investigating the reduction of halo artifacts relative to the scatter estimation method. PET scans of 30 patients administrated with [68Ga]Ga-uPAR were included in cohort 2, used for an evaluation of the robustness of MLSS in cases where TFSS-integrated reconstructions are observed to fail. A visual inspection of MLSS-corrected images scored higher than TFSS-corrected reconstructions of cohort 1. The quantitative investigation near the bladder showed a relative difference in tracer uptake of up to 94.7%. A reconstruction of scans included in cohort 2 resulted in failure in 23 cases when TFSS was used. The lesion uptake values of cohort 2 showed no significant difference. MLSS is suggested as an alternative scatter-scaling method relative to TFSS with the aim of reducing halo artifacts and a robust reconstruction process.

Locally advanced squamous cervical carcinoma (M0): management and emerging therapeutic options in the precision radiotherapy era

Squamous cervical carcinoma (SCC) requires particular attention in diagnostic and clinical management. New diagnostic tools, such as (positron emission tomography-magnetic resonance imaging) PET-MRI, consent to ameliorate clinical staging accuracy. The availability of new technologies in radiation therapy permits to deliver higher dose lowering toxicities. In this clinical scenario, new surgical concepts could aid in general management. Lastly, new targeted therapies and immunotherapy will have more room in this setting. The aim of this narrative review is to focus both on clinical management and new therapies in the precision radiotherapy era.

The use of PET/MRI in radiotherapy

Positron emission tomography/magnetic resonance imaging (PET/MRI) is a hybrid imaging technique that quantitatively combines the metabolic and functional data from positron emission tomography (PET) with anatomical and physiological information from MRI. As PET/MRI technology has advanced, its applications in cancer care have expanded. Recent studies have demonstrated that PET/MRI provides unique advantages in the field of radiotherapy and has become invaluable in guiding precision radiotherapy techniques. This review discusses the rationale and clinical evidence supporting the use of PET/MRI for radiation positioning, target delineation, efficacy evaluation, and patient surveillance.Critical relevance statement This article critically assesses the transformative role of PET/MRI in advancing precision radiotherapy, providing essential insights into improved radiation positioning, target delineation, efficacy evaluation, and patient surveillance in clinical radiology practice.Key points• The emergence of PET/MRI will be a key bridge for precise radiotherapy.• PET/MRI has unique advantages in the whole process of radiotherapy.• New tracers and nanoparticle probes will broaden the use of PET/MRI in radiation.• PET/MRI will be utilized more frequently for radiotherapy.

Evaluating a radiotherapy deep learning synthetic CT algorithm for PET-MR attenuation correction in the pelvis

BACKGROUND

Positron emission tomography-magnetic resonance (PET-MR) attenuation correction is challenging because the MR signal does not represent tissue density and conventional MR sequences cannot image bone. A novel zero echo time (ZTE) MR sequence has been previously developed which generates signal from cortical bone with images acquired in 65 s. This has been combined with a deep learning model to generate a synthetic computed tomography (sCT) for MR-only radiotherapy. This study aimed to evaluate this algorithm for PET-MR attenuation correction in the pelvis.

METHODS

Ten patients being treated with ano-rectal radiotherapy received a [Formula: see text]F-FDG-PET-MR in the radiotherapy position. Attenuation maps were generated from ZTE-based sCT (sCTAC) and the standard vendor-supplied MRAC. The radiotherapy planning CT scan was rigidly registered and cropped to generate a gold standard attenuation map (CTAC). PET images were reconstructed using each attenuation map and compared for standard uptake value (SUV) measurement, automatic thresholded gross tumour volume (GTV) delineation and GTV metabolic parameter measurement. The last was assessed for clinical equivalence to CTAC using two one-sided paired t tests with a significance level corrected for multiple testing of [Formula: see text]. Equivalence margins of [Formula: see text] were used.

RESULTS

Mean whole-image SUV differences were -0.02% (sCTAC) compared to -3.0% (MRAC), with larger differences in the bone regions (-0.5% to -16.3%). There was no difference in thresholded GTVs, with Dice similarity coefficients [Formula: see text]. However, there were larger differences in GTV metabolic parameters. Mean differences to CTAC in [Formula: see text] were [Formula: see text] (± standard error, sCTAC) and [Formula: see text] (MRAC), and [Formula: see text] (sCTAC) and [Formula: see text] (MRAC) in [Formula: see text]. The sCTAC was statistically equivalent to CTAC within a [Formula: see text] equivalence margin for [Formula: see text] and [Formula: see text] ([Formula: see text] and [Formula: see text]), whereas the MRAC was not ([Formula: see text] and [Formula: see text]).

CONCLUSION

Attenuation correction using this radiotherapy ZTE-based sCT algorithm was substantially more accurate than current MRAC methods with only a 40 s increase in MR acquisition time. This did not impact tumour delineation but did significantly improve the accuracy of whole-image and tumour SUV measurements, which were clinically equivalent to CTAC. This suggests PET images reconstructed with sCTAC would enable accurate quantitative PET images to be acquired on a PET-MR scanner.

Metabolic Imaging for Radiation Therapy Treatment Planning: The Role of Hybrid PET/MR Imaging

The use of hybrid PET/MR imaging for radiotherapy treatment planning has the potential to reduce tumor and organ displacements caused by different scan times and setup changes. Although with mixed results mainly due to single-center studies with small sample size, PET/MR imaging could provide better target delineation, especially by reducing coregistration discrepancies on computed tomography simulation scan and offering better soft tissue contrast. The main limitation to drive stronger conclusions is due to the relatively low availability of hybrid PET/MR imaging systems, mainly limited to large academic centers.

Update on Positron Emission Tomography/Magnetic Resonance Imaging: Cancer and Inflammation Imaging in the Clinic

Hybrid PET/MRI is highly valuable, having made significant strides in overcoming technical challenges and offering unique advantages such as reduced radiation, precise data coregistration, and motion correction. Growing evidence highlights the value of PET/MRI in broad clinical aspects, including inflammatory and oncological imaging in adults, pregnant women, and pediatrics, potentially surpassing PET/CT. This newly integrated solution may be preferred over PET/CT in many clinical conditions. However, further technological advancements are required to facilitate its broader adoption as a routine diagnostic modality.

A review of PET attenuation correction methods for PET-MR

Despite being thirteen years since the installation of the first PET-MR system, the scanners constitute a very small proportion of the total hybrid PET systems installed. This is in stark contrast to the rapid expansion of the PET-CT scanner, which quickly established its importance in patient diagnosis within a similar timeframe. One of the main hurdles is the development of an accurate, reproducible and easy-to-use method for attenuation correction. Quantitative discrepancies in PET images between the manufacturer-provided MR methods and the more established CT- or transmission-based attenuation correction methods have led the scientific community in a continuous effort to develop a robust and accurate alternative. These can be divided into four broad categories: (i) MR-based, (ii) emission-based, (iii) atlas-based and the (iv) machine learning-based attenuation correction, which is rapidly gaining momentum. The first is based on segmenting the MR images in various tissues and allocating a predefined attenuation coefficient for each tissue. Emission-based attenuation correction methods aim in utilising the PET emission data by simultaneously reconstructing the radioactivity distribution and the attenuation image. Atlas-based attenuation correction methods aim to predict a CT or transmission image given an MR image of a new patient, by using databases containing CT or transmission images from the general population. Finally, in machine learning methods, a model that could predict the required image given the acquired MR or non-attenuation-corrected PET image is developed by exploiting the underlying features of the images. Deep learning methods are the dominant approach in this category. Compared to the more traditional machine learning, which uses structured data for building a model, deep learning makes direct use of the acquired images to identify underlying features. This up-to-date review goes through the literature of attenuation correction approaches in PET-MR after categorising them. The various approaches in each category are described and discussed. After exploring each category separately, a general overview is given of the current status and potential future approaches along with a comparison of the four outlined categories.

Current Update on PET/MRI in Gynecological Malignancies-A Review of the Literature

Early detection of gynecological malignancies is vital for patient management and prolonging the patient's survival. Molecular imaging, such as positron emission tomography (PET)/computed tomography, has been increasingly utilized in gynecological malignancies. PET/magnetic resonance imaging (MRI) enables the assessment of gynecological malignancies by combining the metabolic information of PET with the anatomical and functional information from MRI. This article will review the updated applications of PET/MRI in gynecological malignancies.

Artificial intelligence in multi-parametric magnetic resonance imaging: A review

Multi-parametric magnetic resonance imaging (mpMRI) is an indispensable tool in the clinical workflow for the diagnosis and treatment planning of various diseases. Machine learning-based artificial intelligence (AI) methods, especially those adopting the deep learning technique, have been extensively employed to perform mpMRI image classification, segmentation, registration, detection, reconstruction, and super-resolution. The current availability of increasing computational power and fast-improving AI algorithms have empowered numerous computer-based systems for applying mpMRI to disease diagnosis, imaging-guided radiotherapy, patient risk and overall survival time prediction, and the development of advanced quantitative imaging technology for magnetic resonance fingerprinting. However, the wide application of these developed systems in the clinic is still limited by a number of factors, including robustness, reliability, and interpretability. This survey aims to provide an overview for new researchers in the field as well as radiologists with the hope that they can understand the general concepts, main application scenarios, and remaining challenges of AI in mpMRI. This article is protected by copyright. All rights reserved.

A deep learning-based whole-body solution for PET/MRI attenuation correction

BACKGROUND

Deep convolutional neural networks have demonstrated robust and reliable PET attenuation correction (AC) as an alternative to conventional AC methods in integrated PET/MRI systems. However, its whole-body implementation is still challenging due to anatomical variations and the limited MRI field of view. The aim of this study is to investigate a deep learning (DL) method to generate voxel-based synthetic CT (sCT) from Dixon MRI and use it as a whole-body solution for PET AC in a PET/MRI system.

MATERIALS AND METHODS

Fifteen patients underwent PET/CT followed by PET/MRI with whole-body coverage from skull to feet. We performed MRI truncation correction and employed co-registered MRI and CT images for training and leave-one-out cross-validation. The network was pretrained with region-specific images. The accuracy of the AC maps and reconstructed PET images were assessed by performing a voxel-wise analysis and calculating the quantification error in SUV obtained using DL-based sCT (PET_sCT) and a vendor-provided atlas-based method (PET_Atlas), with the CT-based reconstruction (PET_CT) serving as the reference. In addition, region-specific analysis was performed to compare the performances of the methods in brain, lung, liver, spine, pelvic bone, and aorta.

RESULTS

Our DL-based method resulted in better estimates of AC maps with a mean absolute error of 62 HU, compared to 109 HU for the atlas-based method. We found an excellent voxel-by-voxel correlation between PET_CT and PET_sCT (R² = 0.98). The absolute percentage difference in PET quantification for the entire image was 6.1% for PET_sCT and 11.2% for PET_Atlas. The regional analysis showed that the average errors and the variability for PET_sCT were lower than PET_Atlas in all regions. The largest errors were observed in the lung, while the smallest biases were observed in the brain and liver.

CONCLUSIONS

Experimental results demonstrated that a DL approach for whole-body PET AC in PET/MRI is feasible and allows for more accurate results compared with conventional methods. Further evaluation using a larger training cohort is required for more accurate and robust performance.

Multi-parametric PET/MRI for enhanced tumor characterization of patients with cervical cancer

Aim

The concept of personalized medicine has brought increased awareness to the importance of inter- and intra-tumor heterogeneity for cancer treatment. The aim of this study was to explore simultaneous multi-parametric PET/MRI prior to chemoradiotherapy for cervical cancer for characterization of tumors and tumor heterogeneity.

Methods

Ten patients with histologically proven primary cervical cancer were examined with multi-parametric 68Ga-NODAGA-E[c(RGDyK)]2-PET/MRI for radiation treatment planning after diagnostic 18F-FDG-PET/CT. Standardized uptake values (SUV) of RGD and FDG, diffusion weighted MRI and the derived apparent diffusion coefficient (ADC), and pharmacokinetic maps obtained from dynamic contrast-enhanced MRI with the Tofts model (iAUC60, Ktrans, ve, and kep) were included in the analysis. The spatial relation between functional imaging parameters in tumors was examined by a correlation analysis and joint histograms at the voxel level. The ability of multi-parametric imaging to identify tumor tissue classes was explored using an unsupervised 3D Gaussian mixture model-based cluster analysis.

Results

Functional MRI and PET of cervical cancers appeared heterogeneous both between patients and spatially within the tumors, and the relations between parameters varied strongly within the patient cohort. The strongest spatial correlation was observed between FDG uptake and ADC (median r =  − 0.7). There was moderate voxel-wise correlation between RGD and FDG uptake, and weak correlations between all other modalities. Distinct relations between the ADC and RGD uptake as well as the ADC and FDG uptake were apparent in joint histograms. A cluster analysis using the combination of ADC, FDG and RGD uptake suggested tissue classes which could potentially relate to tumor sub-volumes.

Conclusion

A multi-parametric PET/MRI examination of patients with cervical cancer integrated with treatment planning and including estimation of angiogenesis and glucose metabolism as well as MRI diffusion and perfusion parameters is feasible. A combined analysis of functional imaging parameters indicates a potential of multi-parametric PET/MRI to contribute to a better characterization of tumor heterogeneity than the modalities alone. However, the study is based on small patient numbers and further studies are needed prior to the future design of individually adapted treatment approaches based on multi-parametric functional imaging.

Developing quality assurance tests for simultaneous Positron Emission Tomography - Magnetic Resonance imaging for radiotherapy planning

Background and purpose Simultaneous Positron Emission Tomography - Magnetic Resonance (PET-MR) imaging can potentially improve radiotherapy by enabling more accurate tumour delineation and dose painting. The use of PET-MR imaging for radiotherapy planning requires a comprehensive Quality Assurance (QA) programme to be developed. This study aimed to develop the QA tests required and assess their repeatability and stability. Materials and methods QA tests were developed for: MR image quality, MR geometric accuracy, electromechanical accuracy, PET-MR alignment accuracy, Diffusion Weighted (DW)-MR Apparent Diffusion Coefficient (ADC) accuracy and PET Standard Uptake Value (SUV) accuracy. Each test used a dedicated phantom and was analysed automatically or semi-automatically, with in-house software. Repeatability was evaluated by three same-day measurements with independent phantom positions. Stability was assessed through 12 monthly measurements. Results The repeatability Standard Deviations (SDs) of distortion for the MR geometric accuracy test were ⩽ 0.7 mm . The repeatability SDs in ADC difference from reference were ⩽ 3 % for the DW-MR accuracy test. The PET SUV difference from reference repeatability SD was 0.3 % . The stability SDs agreed within 0.6 mm , 1 percentage point and 1.4 percentage points of the repeatability SDs for the geometric, ADC and SUV accuracy tests respectively. There were no monthly trends apparent. These results were representative of the other tests. Conclusions QA Tests for radiotherapy planning PET-MR have been developed. The tests appeared repeatable and stable over a 12-month period. The developed QA tests could form the basis of a QA programme that enables high-quality, robust PET-MR imaging for radiotherapy planning.

Significance of Magnetic Resonance Imaging Combining with Detection of Serum HE4, TSGF, and CD105 Levels in Diagnosis and Treatment of Moderate to Advanced Cervical Cancer

Objective

To explore the significance of magnetic resonance imaging (MRI) combining with detection of serum HE4, TSGF, and CD105 levels in diagnosis and treatment of moderate to advanced cervical cancer.

Methods

By means of retrospective study, 50 patients diagnosed with moderate to advanced cervical cancer by cervix biopsy pathology examination in our hospital from October 2018 to October 2019 were selected as the study group, and another 50 healthy individuals who did not have cervical cancer after routine gynecological examination and conventional ultrasound examination in the same period were selected as the control group. At the time of enrollment and 3 months after treatment, all study subjects received MRI examination and serological examination, and their HE4 and TSGF levels were measured by the enzyme-linked immunosorbent assay (ELISA) and chromatography method, respectively, and additionally, the immunohistochemistry SP method was adopted for patients in the study group to measure the microvessel density (MVD) marked by CD105. The relationship between MRI staging and FIGO staging was assessed, the efficacy of combining MRI with detection of serum HE4, TSGF, and CD105 levels in diagnosing moderate to advanced cervical cancer was calculated by plotting the ROC curve, and the imaging changes and serological changes of tumor tissue before and after treatment were analyzed.

Results

There were 3 of 4 patients in stage IIa and 14 of 15 patients in stage IIIb presenting MRI findings compatible with clinical examinations; 26 patients in stage IIb and 5 patients in stage IVb presenting MRI findings totally compatible with clinical examination. Before treatment, MRI finding of cervical lesion was irregular soft tissue mass, T1WI appeared isointensity or hyperintensity, and obvious lesion enhancement could be seen by enhanced scan. T2WI appeared mixed signal intensity or hyperintensity, with necrotic tissue and fat suppression being hyperintensity. After treatment, lesions shrunk, originally abnormal signals in 5 patients disappeared, and T1WI and T2WI signals in 45 patients presented no difference compared to before treatment. After T1WI enhancement, mild enhancement could be seen in 41 cases and no enhancement in 4 cases. The CD105-MVD of the study group was (68.98 ± 5.23); before and after treatment, the differences in HE4 and TSGF levels between the study group and the control group were significant (P < 0.001). The sensitivity, specificity, and accuracy rate of diagnosis of MRI diagnosis were respectively 82.0% (41/50), 90.0% (45/50), and 86.0% (86/100), and for the diagnosis combining with serum HE4, TSGF, and CD105 levels, they were 96.0% (48/50), 96.0% (48/50), and 96.0% (96/100), respectively, and AUC (95% CI) = 0.960 (0.908-1.000).

Conclusion

MRI staging is objective and accurate and has higher sensitivity when combined with serum HE4, TSGF, and CD105 levels in diagnosing moderate to advanced cervical cancer. All MRI, HE4, and TSGF can reflect the treatment effect of patients and are of great importance to efficacy assessment.