Symmetry of the left and right tibial plafond; a comparison of 75 distal tibia pairs.

PURPOSE: Tibia plafond or pilon fractures present a high level of complexity, making their surgical management challenging. Three-Dimensional Virtual Planning (3DVP) can assist in preoperative planning to achieve optimal fracture reduction. This study aimed to assess the symmetry of the left and right tibial plafond and whether left-right mirroring can reliably be used. METHODS: Bilateral CT scans of the lower limbs of 75 patients without ankle problems or prior fractures of the lower limb were included. The CT images were segmented to create 3D surface models of the tibia. Subsequently, the left tibial models were mirrored and superimposed onto the right tibia models using a Coherent Point Drift surface matching algorithm. The tibias were then cut to create bone models of the distal tibia with a height of 30 mm, and correspondence points were established. The Euclidean distance was calculated between correspondence points and visualized in a boxplot and heatmaps. The articulating surface was selected as a region of interest. RESULTS: The median left-right difference was 0.57 mm (IQR, 0.38 - 0.85 mm) of the entire tibial plafond and 0.53 mm (IQR, 0.37 - 0.76 mm) of the articulating surface. The area with the greatest left-right differences were the medial malleoli and the anterior tubercle of the tibial plafond. CONCLUSION: The tibial plafond exhibits a high degree of bilateral symmetry. Therefore, the mirrored unfractured tibial plafond may be used as a template to optimize preoperative surgical reduction using 3DVP techniques in patients with pilon fractures.

Baseline ultrasound and FDG-PET/CT imaging in Merkel cell carcinoma.

BACKGROUND: Merkel cell carcinoma (MCC) is a cutaneous tumor with a high tendency to metastasize, and a significant proportion of patients have metastases at first presentation. This study aims to determine the value of baseline ultrasound (US) and 18 fluorodeoxyglucose-positron emission tomography/computed tomography (18 FDG-PET/CT) imaging in both patients with clinically localized MCC (Stage I/II) and patients who present with palpable lymph nodes (Stage III). METHODS: This retrospective cohort included 135 MCC patients who underwent baseline US (with fine needle aspiration cytology (FNAC)) and/or FDG-PET/CT imaging between 2015 and 2021. RESULTS: Of the 104 patients with clinically localized disease, 48% were upstaged to Stage III and 3% to Stage IV by imaging or sentinel lymph node biopsy (SLNB). FDG-PET/CT imaging identified regional metastases in 23%, while US with FNAC identified regional metastases in 19%. SLNB was performed in 56 patients, of whom 57% were upstaged to Stage III. Of the 31 patients who presented with palpable lymph nodes, 16% were upstaged to Stage IV by FDG-PET/CT imaging. CONCLUSION: Baseline imaging frequently upstages Stage I/II MCC patients to Stage III, both by US and FDG-PET/CT, Stage IV disease is rarely identified. Patients who present with palpable nodes are frequently upstaged to Stage IV by FDG-PET/CT imaging.

Pediatric Precursor B-Cell Lymphoblastic Malignancies: From Extramedullary to Medullary Involvement.

B-cell lymphoblastic lymphoma (BCP-LBL) and B-cell acute lymphoblastic leukemia (BCP-ALL) are the malignant counterparts of immature B-cells. BCP-ALL is the most common hematological malignancy in childhood, while BCP-LBL accounts for only 1% of all hematological malignancies in children. Therefore, BCP-ALL has been well studied and treatment protocols have changed over the last decades, whereas treatment for BCP-LBL has stayed roughly the same. Clinical characteristics of 364 pediatric patients with precursor B-cell malignancies were studied, consisting of BCP-LBL (n = 210) and BCP-ALL (n = 154) patients. Our results indicate that based on the clinical presentation of disease, B-cell malignancies probably represent a spectrum ranging from complete isolated medullary disease to apparent complete extramedullary disease. Hepatosplenomegaly and peripheral blood involvement are the most important discriminators, as both seen in 80% and 95% of the BCP-ALL patients and in 2% of the BCP-LBL patients, respectively. In addition, we show that the overall survival rates in this cohort differ significantly between BCP-LBL and BCP-ALL patients aged 1−18 years (p = 0.0080), and that the outcome for infants (0−1 years) with BCP-LBL is significantly decreased compared to BCP-LBL patients of all other pediatric ages (p < 0.0001).

A robust and semi-automatic quantitative measurement of patellofemoral instability based on four dimensional computed tomography.

Patellofemoral instability is a motion related disease, featured as the patella dislocating from the trochlear groove. Four dimensional computed tomography (4DCT) enables full assessment of the patellofemoral movement. Nevertheless, the quantitative measurements of patellofemoral instability are still under research and currently of limited practical use. The aim of this study is to develop a robust and semi-automatic workflow to quantitatively describe the patellofemoral movement in a patient group of eight suffering from patellofemoral instability. The initial results show agreement with manual observations of the tibial tubercle - trochlear groove (TT-TG) distance in routine practice, and the possibility to evaluate both TT-TG distance and patellar centre - trochlear groove (PC-TG) distance dynamically during active flexion-extension-flexion movement of the knee.

Computer-aided detection of fasciculations and other movements in muscle with ultrasound: Development and clinical application.

OBJECTIVE: To develop an automated algorithm for detecting fasciculations and other movements in muscle ultrasound videos. Fasciculation detection in muscle ultrasound is routinely performed online by observing the live videos. However, human observation limits the objective information gained. Automated detection of movement is expected to improved sensitivity and specificity and increase reliability. METHODS: We used 42 ultrasound videos from 11 neuromuscular patients for an iterative learning process between human observers and automated computer analysis, to identify muscle ultrasound movements. Two different datasets were selected from this, one to develop the algorithm and one to validate it. The outcome was compared to manual movement identification by clinicians. The algorithm also quantifies specific parameters of different movement types, to enable automated differentiation of events. RESULTS: The algorithm reliably detected fasciculations. With algorithm guidance, observers found more fasciculations compared to visual analysis alone, and prescreening the videos with the algorithm saved clinicians significant time compared to reviewing full video sequences. All videos also contained other movements, especially contraction pseudotremor, which confused human interpretation in some. CONCLUSIONS: Automated movement detection is a feasible and attractive method to screen for fasciculations in muscle ultrasound videos. SIGNIFICANCE: Our findings affirm the potential clinical usefulness of automated movement analysis in muscle ultrasound.