Thomas Wendler

Longitudinal oncologic imaging poses a tracking challenge because lesions can split, merge, or transiently disappear, violating one-to-one correspondence assumptions. We propose spatio-temporal lesion graphs constructed via nearest-centroid matching across all previous time points for lineage assignment, with bidirectional matching between consecutive scans to classify splits, merges, and continuations without learning. Modality-agnostic matching naturally captures phenotypic switching across imaging different modalities. Evaluated on longitudinal PSMA-/FDG-PET/CT during ¹⁷⁷Lu-PSMA therapy (4 patients, 11-13 scans each), the graphs recovered 50 topology changes (22 splits, 28 merges) missed by forward-only matching and revealed persistently high intra-patient SUV_peak heterogeneity (median CV=0.74), demonstrating that aggregate metrics obscure substantial inter-lesion variation. The resulting graph provides a compact lesion-level representation for response assessment and potentially lesion-specific diagnostics and local therapy. The code and data are available at: https://github.com/lukasf98/spatio-temporal-graph.

Background: Accurate thyroid volume measurement is essential for diagnosing and monitoring thyroid disorders and for determining radioiodine therapy dosage. The ellipsoid method applied to two-dimensional B-mode ultrasound (Bmode-2D-US) is the most prevalent clinical approach, yet it is known to suffer from high observer dependence and limited accuracy. Tracked three-dimensional ultrasound (3D-US) is a promising radiation-free alternative, but direct comparisons across modalities under controlled conditions remain scarce. Methods: A custom-built anthropomorphic multi-modality phantom was constructed containing six anatomically realistic thyroid lobe samples molded from segmented MRI data, with ground truth volumes verified by the suspension method and 3D surface scanning. Volume measurements were performed by six observers of varying experience using Bmode-2D-US, electromagnetically tracked 3D-US (EM-3D-US), inertial-measurement-unit-tracked 3D-US (IMU-3D-US), and optically tracked 3D-US (Opt-3D-US), as well as computed tomography (CT) and magnetic resonance imaging (MRI). Inter- and intraobserver variability were assessed using modified Bland–Altman analysis. Results: All three 3D-US methods reduced inter- and intraobserver variability compared to Bmode-2D-US, achieving variability comparable to CT and lower than MRI. Mean accuracy was similar across 3D-US, CT, and MRI. Bmode-2D-US showed strong observer dependence, with operator experience having the most pronounced effect on this method. Among tracked methods, EM-3D-US and Opt-3D-US were least sensitive to operator movement quality, while IMU-3D-US showed somewhat higher sensitivity. Conclusions: Tracked 3D-US is a promising radiation-free alternative to conventional Bmode-2D-US for thyroid volumetry, offering improved reproducibility and accuracy across operators of varying experience in this phantom-based evaluation.

Background: Accurate thyroid volume measurement is essential for diagnosing and monitoring thyroid disorders and for determining radioiodine therapy dosage. The ellipsoid method applied to two-dimensional B-mode ultrasound (Bmode-2D-US) is the most prevalent clinical approach, yet it is known to suffer from high observer dependence and limited accuracy. Tracked three-dimensional ultrasound (3D-US) is a promising radiation-free alternative, but direct comparisons across modalities under controlled conditions remain scarce. Methods: A custom-built anthropomorphic multi-modality phantom was constructed containing six anatomically realistic thyroid lobe samples molded from segmented MRI data, with ground truth volumes verified by the suspension method and 3D surface scanning. Volume measurements were performed by six observers of varying experience using Bmode-2D-US, electromagnetically tracked 3D-US (EM-3D-US), inertial-measurement-unit tracked 3D-US (IMU-3D-US), and optically tracked 3D-US (Opt-3D-US), as well as computed tomography (CT) and magnetic resonance imaging (MRI). Inter- and intraobserver variability were assessed using modified Bland-Altman analysis. Results: All three 3D-US methods reduced inter- and intraobserver variability compared to Bmode-2D-US, achieving variability comparable to CT and lower than MRI. Mean accuracy was similar across 3D-US, CT, and MRI. Bmode-2D-US showed strong observer dependence, with operator experience having the most pronounced effect on this method. Among tracked methods, EM-3D-US and Opt-3D-US were least sensitive to operator movement quality, while IMU-3D-US showed somewhat higher sensitivity. Conclusion: Tracked 3D-US is a promising radiation-free alternative to conventional Bmode-2D-US for thyroid volumetry, offering improved reproducibility and accuracy across operators of varying experience.

Purpose: The introduction of the drop-in gamma probe has advanced intraoperative molecular imaging during prostate cancer surgery. We have been able to convert the sensor’s numeric readout to tomographic images, so-called robotic-SPECT ( _Robo SPECT) and investigate how this is impacted by radiopharmaceutical avidities and drop-in scan metrics. Methods: The gamma sensor readout was registered with its 3D position and orientation, allowing a custom reconstruction algorithm to generate _Robo SPECT images. Evaluations occurred in 21 patients; 10 sentinel node procedures (SN; primary prostate cancer) and 11 PSMA-radioguided surgery (recurrent prostate cancer). _Robo SPECT findings were related to respective pre- and intra-operative controls, including preoperative PSMA-PET/CT and/or SPECT/CT images and fluorescence detection (SN only). Results: _Robo SPECT proved to be safe and applicable in a range of conditions. In the SN-group, 26 SN-SPECT/CT lesions were successfully identified with SN- _Robo SPECT (100%); 3 were tumor positive (sensitivity 100%). Only 73% of SNs were surgically visible with fluorescence imaging. For the PSMA guided group, the 14 lesions identified on PSMA-PET/CT were all visualized with PSMA- _Robo SPECT (100%); 18 specimens were tumor positive (sensitivity 78% for both PSMA-PET/CT and PSMA- _Robo SPECT). Preoperative PSMA-SPECT/CT only identified 4 PSMA-lesions (29%). No false positives were seen for _robo SPECT and all final resection margins were clean. At 6-months 0% of the SN-patients and 20% of PSMA-patients showed biochemical recurrence. Conclusion: _Robo SPECT provides 3D context that extends the utility of drop-in gamma tracing and assists the alignment between pre- and intra-operative target perception. Here SN- _Robo SPECT clearly outperformed fluorescence SN imaging and PSMA- _Robo SPECT outperformed preoperative PSMA-SPECT/CT imaging.