Feasibility of Image Reconstruction from Triple Modality Data of Yttrium-90

The recent implementation of the first clinical triple modality scanner in STIR enables investigation of the possibility of triple modality image reconstruction. Such a tool represents an important step toward the improvement of dosimetry for theranostics, where the exploitation of multi-modality imaging can have an impact on treatment planning and follow-up. To give a demonstration of triple modality image reconstruction we used data from a NEMA phantom that was filled with Yttrium-90 (90Y), which emits Bremsstrahlung photons detectable with SPECT as well as gamma rays that can go through pair production, therefore creating positrons that make PET acquisition possible. The data were acquired with the Mediso AnyScan SPECT/PET/CT. Different ways of including multiple side information using the kernelised expectation maximisation (KEM) and the Hybrid KEM (HKEM) were used and investigated in terms of ROI activity and noise suppression. This work presents an example of application with 90Y but it can be extended to any other radionuclide combination used in Theranostic applications

Improved identification of abdominal aortic aneurysm using the Kernelized Expectation Maximization algorithm

Abdominal aortic aneurysm (AAA) monitoring and risk of rupture is currently assumed to be correlated with the aneurysm diameter. Aneurysm growth, however, has been demonstrated to be unpredictable. Using PET to measure uptake of [18F]-NaF in calcified lesions of the abdominal aorta has been shown to be useful for identifying AAA and to predict its growth. The PET low spatial resolution, however, can affect the accuracy of the diagnosis. Advanced edge-preserving reconstruction algorithms can overcome this issue. The kernel method has been demonstrated to provide noise suppression while retaining emission and edge information. Nevertheless, these findings were obtained using simulations, phantoms and a limited amount of patient data. In this study, the authors aim to investigate the usefulness of the anatomically guided kernelized expectation maximization (KEM) and the hybrid KEM (HKEM) methods and to judge the statistical significance of the related improvements. Sixty-one datasets of patients with AAA and 11 from control patients were reconstructed with ordered subsets expectation maximization (OSEM), HKEM and KEM and the analysis was carried out using the target-to-blood-pool ratio, and a series of statistical tests. The results show that all algorithms have similar diagnostic power, but HKEM and KEM can significantly recover uptake of lesions and improve the accuracy of the diagnosis by up to 22% compared to OSEM. The same improvements are likely to be obtained in clinical applications based on the quantification of small lesions, like for example cancer

The NeST (Neoadjuvant systemic therapy in breast cancer) study: National Practice Questionnaire of United Kingdom multi-disciplinary decision making

Abstract: Background: Neoadjuvant systemic therapy (NST) is increasingly used in the treatment of breast cancer, yet it is clear that there is significant geographical variation in its use in the UK. This study aimed to examine stated practice across UK breast units, in terms of indications for use, radiological monitoring, pathological reporting of treatment response, and post-treatment surgical management. Methods: Multidisciplinary teams (MDTs) from all UK breast units were invited to participate in the NeST study. A detailed questionnaire assessing current stated practice was distributed to all participating units in December 2017 and data collated securely usingREDCap. Descriptive statistics were calculated for each questionnaire item. Results: Thirty-nine MDTs from a diverse range of hospitals responded. All MDTs routinely offered neoadjuvant chemotherapy (NACT) to a median of 10% (range 5–60%) of patients. Neoadjuvant endocrine therapy (NET) was offered to a median of 4% (range 0–25%) of patients by 66% of MDTs. The principal indication given for use of neoadjuvant therapy was for surgical downstaging. There was no consensus on methods of radiological monitoring of response, and a wide variety of pathological reporting systems were used to assess tumour response. Twenty-five percent of centres reported resecting the original tumour footprint, irrespective of clinical/radiological response. Radiologically negative axillae at diagnosis routinely had post-NACT or post-NET sentinel lymph node biopsy (SLNB) in 73.0 and 84% of centres respectively, whereas 16% performed SLNB pre-NACT. Positive axillae at diagnosis would receive axillary node clearance at 60% of centres, regardless of response to NACT. Discussion: There is wide variation in the stated use of neoadjuvant systemic therapy across the UK, with general low usage of NET. Surgical downstaging remains the most common indication of the use of NAC, although not all centres leverage the benefits of NAC for de-escalating surgery to the breast and/or axilla. There is a need for agreed multidisciplinary guidance for optimising selection and management of patients for NST. These findings will be corroborated in phase II of the NeST study which is a national collaborative prospective audit of NST utilisation and clinical outcomes

Validation of SPECT-CT image reconstruction for the Mediso AnyScan SCP scanner in STIR

Single photon emission tomography (SPECT) is widely used in clinical practice for a large number of diagnostic applications. However, different hospitals might use different scanners containing different hardware and software technologies, therefore making reproducibility of results a hard task. The aim of this work is to establish the basis for a tool able to include different clinical scanner models to facilitate inter-comparison of activity measurements across different institutions. We used the open source software for tomographic image reconstruction (STIR) and implemented functionalities to read, process and reconstruct the data from the Mediso AnyScan SCP scanner. In particular, the triple energy window method for scatter estimation, a method to re-scale the CT Hounsfield units in attenuation coefficient units (cm -1 ), SPECT normalisation functionalities and list mode (LM) functionalities were implemented and tested. 3D printed phantom data, with organ inserts filled with 177 Lu, and a 99m Tc clinical bone study were reconstructed using the implemented corrections and different anatomically-guided algorithms. The effect of the aforementioned correction was studied using ROI analysis and line profiles, whereas visual comparison was carried out between the reconstructed images with the vendor software and with STIR. Moreover, we demonstrated the feasibility of SPECT image reconstruction using the CT and iterative SPECT image estimates as prior information. Finally, a run time performance study showed that, when using multiple cores, an acceleration of a factor 2.7 is achieved for OSEM and around 2 for the other algorithms which involved more image-based operations. The availability of such tool will make SPECT research applications more accessible and reproducible