Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation.

BACKGROUND: Automated segmentation of spinal magnetic resonance imaging (MRI) plays a vital role both scientifically and clinically. However, accurately delineating posterior spine structures is challenging. METHODS: This retrospective study, approved by the ethical committee, involved translating T1-weighted and T2-weighted images into computed tomography (CT) images in a total of 263 pairs of CT/MR series. Landmark-based registration was performed to align image pairs. We compared two-dimensional (2D) paired - Pix2Pix, denoising diffusion implicit models (DDIM) image mode, DDIM noise mode - and unpaired (SynDiff, contrastive unpaired translation) image-to-image translation using "peak signal-to-noise ratio" as quality measure. A publicly available segmentation network segmented the synthesized CT datasets, and Dice similarity coefficients (DSC) were evaluated on in-house test sets and the "MRSpineSeg Challenge" volumes. The 2D findings were extended to three-dimensional (3D) Pix2Pix and DDIM. RESULTS: 2D paired methods and SynDiff exhibited similar translation performance and DCS on paired data. DDIM image mode achieved the highest image quality. SynDiff, Pix2Pix, and DDIM image mode demonstrated similar DSC (0.77). For craniocaudal axis rotations, at least two landmarks per vertebra were required for registration. The 3D translation outperformed the 2D approach, resulting in improved DSC (0.80) and anatomically accurate segmentations with higher spatial resolution than that of the original MRI series. CONCLUSIONS: Two landmarks per vertebra registration enabled paired image-to-image translation from MRI to CT and outperformed all unpaired approaches. The 3D techniques provided anatomically correct segmentations, avoiding underprediction of small structures like the spinous process. RELEVANCE STATEMENT: This study addresses the unresolved issue of translating spinal MRI to CT, making CT-based tools usable for MRI data. It generates whole spine segmentation, previously unavailable in MRI, a prerequisite for biomechanical modeling and feature extraction for clinical applications. KEY POINTS: • Unpaired image translation lacks in converting spine MRI to CT effectively. • Paired translation needs registration with two landmarks per vertebra at least. • Paired image-to-image enables segmentation transfer to other domains. • 3D translation enables super resolution from MRI to CT. • 3D translation prevents underprediction of small structures.

[Migraine in childhood and adolescence-neurostimulation as a future innovative approach in terms of a multimodal treatment regimen]. / Migräne im Kindes- und Jugendalter ­ Ausblick auf innovative Behandlungsansätze im Rahmen multimodaler Therapiekonzepte.

Although migraine is a relevant health issue in children and adolescents, clinical care and research are still underrepresented and underfunded in this field. Quality of life can be significantly reduced when living with frequent episodes of pain. Due to the high level of vulnerability of the developing brain during adolescence, the risk of chronification and persistence into adulthood is high. In this narrative review, we describe the corner stones of a patient-centered, multimodular treatment regimen. Further, an update on the pathophysiology of migraine is given considering the concept of a periodically oscillating functional state of the brain in migraine patients ("migraine is a brain state"). Besides central mechanisms, muscular structures with the symptoms of muscular pain, tenderness, or myofascial trigger points play an important role. Against this background, the currently available nonpharmacological and innovative neuromodulating approaches are presented focusing on the method of repetitive peripheral magnetic stimulation.