MapFormer: Boosting Change Detection by Using Pre-change Information

Change detection in remote sensing imagery is essential for a variety of applications such as urban planning, disaster management, and climate research. However, existing methods for identifying semantically changed areas overlook the availability of semantic information in the form of existing maps describing features of the earth's surface. In this paper, we leverage this information for change detection in bi-temporal images. We show that the simple integration of the additional information via concatenation of latent representations suffices to significantly outperform state-of-the-art change detection methods. Motivated by this observation, we propose the new task of Conditional Change Detection, where pre-change semantic information is used as input next to bi-temporal images. To fully exploit the extra information, we propose MapFormer, a novel architecture based on a multi-modal feature fusion module that allows for feature processing conditioned on the available semantic information. We further employ a supervised, cross-modal contrastive loss to guide the learning of visual representations. Our approach outperforms existing change detection methods by an absolute 11.7% and 18.4% in terms of binary change IoU on DynamicEarthNet and HRSCD, respectively. Furthermore, we demonstrate the robustness of our approach to the quality of the pre-change semantic information and the absence pre-change imagery. The code will be made publicly available

C‐reactive protein flare‐response predicts long‐term efficacy to first‐line anti‐PD‐1‐based combination therapy in metastatic renal cell carcinoma

Objectives Immune checkpoint blockade (IO) has revolutionised the treatment of metastatic renal cell carcinoma (mRCC). Early C-reactive protein (CRP) kinetics, especially the recently introduced CRP flare-response phenomenon, has shown promising results to predict IO efficacy in mRCC, but has only been studied in second line or later. Here, we aimed to validate the predictive value of early CRP kinetics for 1st-line treatment of mRCC with αPD-1 plus either αCTLA-4 (IO+IO) or tyrosine kinase inhibitor (IO+TKI). Methods In this multicentre retrospective study, we investigated the predictive potential of early CRP kinetics during 1st-line IO therapy. Ninety-five patients with mRCC from six tertiary referral centres with either IO+IO (N = 59) or IO+TKI (N = 36) were included. Patients were classified as CRP flare-responders, CRP responders or non-CRP responders as previously described, and their oncological outcome was compared. Results Our data validate the predictive potential of early CRP kinetics in 1st-line immunotherapy in mRCC. CRP responders, especially CRP flare-responders, had significantly prolonged progression-free survival (PFS) compared with non-CRP responders (median PFS: CRP flare-responder: 19.2 months vs. responders: 16.2 vs. non-CRP responders: 5.6, P < 0.001). In both the IO+IO and IO+TKI subgroups, early CRP kinetics remained significantly associated with improved PFS. CRP flare-response was also associated with long-term response ≥ 12 months. Conclusions Early CRP kinetics appears to be a low-cost and easy-to-implement on-treatment biomarker to predict response to 1st-line IO combination therapy. It has potential to optimise therapy monitoring and might represent a new standard of care biomarker for immunotherapy in mRCC