[89Zr]Zr-girentuximab for PET-CT imaging of clear-cell renal cell carcinoma: a prospective, open-label, multicentre, phase 3 trial.

BACKGROUND: With limitations of conventional imaging and biopsy, accurate, non-invasive techniques to detect clear-cell renal cell carcinoma in patients with renal masses remain an unmet need. 89Zr-labelled monoclonal antibody ([89Zr]Zr-girentuximab) has high affinity for carbonic anhydrase 9, a tumour antigen highly expressed in clear-cell renal cell carcinoma. We aimed to evaluate [89Zr]Zr-girentuximab PET-CT imaging for detection and characterisation of clear-cell renal cell carcinoma. METHODS: ZIRCON was a prospective, open-label, multicentre, phase 3 trial conducted at 36 research hospitals and practices across nine countries (the USA, Australia, Canada, the UK, Türkiye, Belgium, the Netherlands, Spain, and France). Patients aged 18 years or older with an indeterminate renal mass 7 cm or smaller (cT1) suspicious for clear-cell renal cell carcinoma and scheduled for nephrectomy received a single dose of [89Zr]Zr-girentuximab (37 MBq ±10%; 10 mg girentuximab) intravenously followed by abdominal PET-CT imaging 5 days (±2 days) later. Surgery was performed no later than 90 days after administration of [89Zr]Zr-girentuximab. Blinded central review, conducted by three independent readers, determined the histology from surgical samples. The coprimary endpoints, determined for each individual reader, were the sensitivity and specificity of [89Zr]Zr-girentuximab PET-CT imaging to detect clear-cell renal cell carcinoma, with histopathological confirmation as standard of truth. Analyses were on the full analysis set of patients, defined as patients who had evaluable PET-CT imaging and a confirmed histopathological diagnosis. The trial is registered with ClinicalTrials.gov, NCT03849118, and EUDRA Clinical Trials Register, 2018-002773-21, and is closed to enrolment. FINDINGS: Between Aug 14, 2019, and July 8, 2022, 371 patients were screened for eligibility, 332 of whom were enrolled. 300 patients received [89Zr]Zr-girentuximab (214 [71%] male and 86 [29%] female). 284 (95%) evaluable patients were included in the primary analysis. The mean sensitivity was 85·5% (95% CI 81·5-89·6) and mean specificity was 87·0% (81·0-93·1). No safety signals were observed. Most adverse events were not or were unlikely to be related to [89Zr]Zr-girentuximab, with most (193 [74%] of 261 events) occurring during or after surgery. The most common grade 3 or worse adverse events were post-procedural haemorrhage (in six [2%] of 261 patients), urinary retention (three [1%]), and hypertension (three [1%]). In 25 (8%) of 300 patients, 52 serious adverse events were reported, of which 51 (98%) occurred after surgery. There were no treatment-related deaths. INTERPRETATION: Our results suggest that [89Zr]Zr-girentuximab PET-CT has a favourable safety profile and is a highly accurate, non-invasive imaging modality for the detection and characterisation of clear-cell renal cell carcinoma, which has the potential to be practice changing. FUNDING: Telix Pharmaceuticals.

A differential cell capture assay for evaluating antibody interactions with cell surface targets.

Many biological and biomedical laboratory assays require the use of antibodies and antibody fragments that strongly bind to their cell surface targets. Conventional binding assays, such as the enzyme-linked immunosorbent assay (ELISA) and flow cytometry, have many challenges, including capital equipment requirements, labor intensiveness, and large reagent and sample consumption. Although these techniques are successful in mainstream biology, there is an unmet need for a tool to quickly ascertain the relative binding capabilities of antibodies/antibody fragments to cell surface targets on the benchtop at low cost. We describe a novel cell capture assay that enables several candidate antibodies to be evaluated quickly as to their relative binding efficacies to their cell surface targets. We used chimeric rituximab and murine anti-CD20 monoclonal antibodies as cell capture agents on a functionalized microscope slide surface to assess their relative binding affinities based on how well they capture CD20-expressing mammalian cells. We found that these antibodies' concentration-dependent cell capture profiles correlate with their relative binding affinities. A key observation of this assay involved understanding how differences in capture surfaces affect the assay results. This approach can find utility when an antibody or antibody fragment against a known cell line needs to be selected for targeting studies.

A registration framework for the comparison of mammogram sequences.

In this paper, we present a two-stage algorithm for mammogram registration, the geometrical alignment of mammogram sequences. The rationale behind this paper stems from the intrinsic difficulties in comparing mammogram sequences. Mammogram comparison is a valuable tool in national breast screening programs as well as in frequent monitoring and hormone replacement therapy (HRT). The method presented in this paper aims to improve mammogram comparison by estimating the underlying geometric transformation for any mammogram sequence. It takes into consideration the various temporal changes that may occur between successive scans of the same woman and is designed to overcome the inconsistencies of mammogram image formation.

Extracting and visualizing physiological parameters using dynamic contrast-enhanced magnetic resonance imaging of the breast.

An analysis procedure is presented that enables the acquisition and visualization of physiologically relevant parameters using dynamic contrast-enhanced magnetic resonance imaging. The first stage of the process involves the use of a signal model that relates the measured magnetic resonance signal to the contrast agent concentration. Since the model requires knowledge of the longitudinal relaxation time T(1), a novel optimization scheme is presented which ensures a reliable measurement. Pharmacokinetic modelling of the observed contrast agent uptake is then performed to obtain physiological parameters relating to microvessel leakage permeability and volume fraction and the assumptions made in the derivation of these parameters are discussed. A simple colour representation is utilized that enables the relevant physiological information to be conveyed to the clinician in a visually efficient and meaningful manner. A second representation, based on vector maps, is also devised and it is demonstrated how this can be used for malignant tumour segmentation. Finally, the procedure is applied to 14 pre- and post-chemotherapy breast cases to demonstrate the clinical value of the technique. In particular, the apparent improved representation of tissue vascularity when compared to conventional methods and the implications for this in treatment assessment are discussed.

A shape-space-based approach to tracking myocardial borders and quantifying regional left-ventricular function applied in echocardiography.

This paper presents a new semi-automatic method for quantifying regional heart function from two-dimensional echocardiography. In the approach, we first track the endocardial and epicardial boundaries using a new variant of the dynamic snake approach. The tracked borders are then decomposed into clinically meaningful regional parameters, using a novel interpretational shape-space motivated by the 16-segment model used in clinical practice for qualitative assessment of heart function. We show how a quantitative and automatic scoring scheme for the endocardial excursion and myocardial thickening can be derived from this. Results illustrating our approach on apical long-axis two-chamber-view data from a patient with a myocardial infarct in the apical anterior/inferior region of the heart are presented. In a case study (five patients, nine data sets) the performance of the tracking and interpretation techniques are compared with manual delineations of borders using a number of quantitative measures of regional comparison.

Fusion of contrast-enhanced breast MR and mammographic imaging data.

Increasing use is being made of Gd-DTPA contrast-enhanced magnetic resonance imaging for breast cancer assessment since it provides 3D functional information via pharmacokinetic interaction between contrast agent and tumour vascularity, and because it is applicable to women of all ages as well as patients with post-operative scarring. Contrast-enhanced MRI (CE-MRI) is complementary to conventional X-ray mammography, since it is a relatively low-resolution functional counterpart of a comparatively high-resolution 2D structural representation. However, despite the additional information provided by MRI, mammography is still an extremely important diagnostic imaging modality, particularly for several common conditions such as ductal carcinoma in situ (DCIS) where it has been shown that there is a strong correlation between microcalcification clusters and malignancy. Pathological indicators such as calcifications and fine spiculations are not visible in CE-MRI and therefore there is clinical and diagnostic value in fusing the high-resolution structural information available from mammography with the functional data acquired from MRI imaging. This paper presents a novel data fusion technique whereby medial-lateral oblique (MLO) and cranial-caudal (CC) mammograms (2D data) are registered to 3D contrast-enhanced MRI volumes. We utilise a combination of pharmacokinetic modelling, projection geometry, wavelet-based landmark detection and thin-plate spline non-rigid 'warping' to transform the coordinates of regions of interest (ROIs) from the 2D mammograms to the spatial reference frame of the contrast-enhanced MRI volume. Of key importance is the use of a flexible wavelet-based feature extraction technique that enables feature correspondences to be robustly determined between the very different image characteristics of X-ray mammography and MRI. An evaluation of the fusion framework is demonstrated with a series of clinical cases and a total of 14 patient examples.

A mammographic image analysis method to detect and measure changes in breast density.

We present an image analysis method that can detect and measure breast density from digitised mammograms. We present initial results on applying our method to characterise breast changes, in particular, changes due to Hormone Replacement Therapy (HRT). It has been established that long-term use of certain hormone replacement therapies can increase the risk of breast cancer, a fact that encourages the notion that objective measures of tissue density can be an important development in breast cancer image analysis. A set of 59 temporal pairs of mammograms of patients undergoing HRT (two images per patient) were used. The clinician's assessment of density changes constituted the ground truth for evaluating the proposed quantitative measures of density change. The measures we developed are based on the Standard Mammogram Form (SMF) representation of interesting tissue and their performance (agreement with the expert's description) is also compared to the "interactive thresholding" method that has been used in the past to characterise mammographic density. The results clearly indicate that present methods for measuring mammographic density fail to characterise temporal changes while the proposed measures have the potential to aid the radiologist in assessing temporal density changes both on a global and a local basis.