Squamous cell carcinoma arising in a below-knee stump of a patient with chronic lymphocytic leukemia.

We report a case of localized squamous cell carcinoma arising in the ulceration at the site of a below-knee amputation in a patient with chronic lymphocytic leukemia on treatment with ibrutinib. The patient underwent local excision of the skin and soft tissue with histopathology showing a small focus of well-differentiated squamous cell carcinoma in the specimen. This case highlights the importance of clinical evaluation and histopathological review for underlying malignancy in the setting of amputation stump ulceration.

Deformable motion compensation in interventional cone-beam CT with a context-aware learned autofocus metric.

PURPOSE: Interventional Cone-Beam CT (CBCT) offers 3D visualization of soft-tissue and vascular anatomy, enabling 3D guidance of abdominal interventions. However, its long acquisition time makes CBCT susceptible to patient motion. Image-based autofocus offers a suitable platform for compensation of deformable motion in CBCT, but it relies on handcrafted motion metrics based on first-order image properties and that lack awareness of the underlying anatomy. This work proposes a data-driven approach to motion quantification via a learned, context-aware, deformable metric, VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ , that quantifies the amount of motion degradation as well as the realism of the structural anatomical content in the image. METHODS: The proposed VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ was modeled as a deep convolutional neural network (CNN) trained to recreate a reference-based structural similarity metric-visual information fidelity (VIF). The deep CNN acted on motion-corrupted images, providing an estimation of the spatial VIF map that would be obtained against a motion-free reference, capturing motion distortion, and anatomic plausibility. The deep CNN featured a multi-branch architecture with a high-resolution branch for estimation of voxel-wise VIF on a small volume of interest. A second contextual, low-resolution branch provided features associated to anatomical context for disentanglement of motion effects and anatomical appearance. The deep CNN was trained on paired motion-free and motion-corrupted data obtained with a high-fidelity forward projection model for a protocol involving 120 kV and 9.90 mGy. The performance of VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ was evaluated via metrics of correlation with ground truth VIF ${\bm{VIF}}$ and with the underlying deformable motion field in simulated data with deformable motion fields with amplitude ranging from 5 to 20 mm and frequency from 2.4 up to 4 cycles/scan. Robustness to variation in tissue contrast and noise levels was assessed in simulation studies with varying beam energy (90-120 kV) and dose (1.19-39.59 mGy). Further validation was obtained on experimental studies with a deformable phantom. Final validation was obtained via integration of VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ on an autofocus compensation framework, applied to motion compensation on experimental datasets and evaluated via metric of spatial resolution on soft-tissue boundaries and sharpness of contrast-enhanced vascularity. RESULTS: The magnitude and spatial map of VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ showed consistent and high correlation levels with the ground truth in both simulation and real data, yielding average normalized cross correlation (NCC) values of 0.95 and 0.88, respectively. Similarly, VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ achieved good correlation values with the underlying motion field, with average NCC of 0.90. In experimental phantom studies, VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ properly reflects the change in motion amplitudes and frequencies: voxel-wise averaging of the local VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ across the full reconstructed volume yielded an average value of 0.69 for the case with mild motion (2 mm, 12 cycles/scan) and 0.29 for the case with severe motion (12 mm, 6 cycles/scan). Autofocus motion compensation using VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ resulted in noticeable mitigation of motion artifacts and improved spatial resolution of soft tissue and high-contrast structures, resulting in reduction of edge spread function width of 8.78% and 9.20%, respectively. Motion compensation also increased the conspicuity of contrast-enhanced vascularity, reflected in an increase of 9.64% in vessel sharpness. CONCLUSION: The proposed VI F D L ${\bm{VI}}{{\bm{F}}}_{DL}$ , featuring a novel context-aware architecture, demonstrated its capacity as a reference-free surrogate of structural similarity to quantify motion-induced degradation of image quality and anatomical plausibility of image content. The validation studies showed robust performance across motion patterns, x-ray techniques, and anatomical instances. The proposed anatomy- and context-aware metric poses a powerful alternative to conventional motion estimation metrics, and a step forward for application of deep autofocus motion compensation for guidance in clinical interventional procedures.

Vessel-targeted compensation of deformable motion in interventional cone-beam CT.

The present standard of care for unresectable liver cancer is transarterial chemoembolization (TACE), which involves using chemotherapeutic particles to selectively embolize the arteries supplying hepatic tumors. Accurate volumetric identification of intricate fine vascularity is crucial for selective embolization. Three-dimensional imaging, particularly cone-beam CT (CBCT), aids in visualization and targeting of small vessels in such highly variable anatomy, but long image acquisition time results in intra-scan patient motion, which distorts vascular structures and tissue boundaries. To improve clarity of vascular anatomy and intra-procedural utility, this work proposes a targeted motion estimation and compensation framework that removes the need for any prior information or external tracking and for user interaction. Motion estimation is performed in two stages: (i) a target identification stage that segments arteries and catheters in the projection domain using a multi-view convolutional neural network to construct a coarse 3D vascular mask; and (ii) a targeted motion estimation stage that iteratively solves for the time-varying motion field via optimization of a vessel-enhancing objective function computed over the target vascular mask. The vessel-enhancing objective is derived through eigenvalues of the local image Hessian to emphasize bright tubular structures. Motion compensation is achieved via spatial transformer operators that apply time-dependent deformations to partial angle reconstructions, allowing efficient minimization via gradient backpropagation. The framework was trained and evaluated in anatomically realistic simulated motion-corrupted CBCTs mimicking TACE of hepatic tumors, at intermediate (3.0 mm) and large (6.0 mm) motion magnitudes. Motion compensation substantially improved median vascular DICE score (from 0.30 to 0.59 for large motion), image SSIM (from 0.77 to 0.93 for large motion), and vessel sharpness (0.189 mm-1 to 0.233 mm-1 for large motion) in simulated cases. Motion compensation also demonstrated increased vessel sharpness (0.188 mm-1 before to 0.205 mm-1 after) and reconstructed vessel length (median increased from 37.37 to 41.00 mm) on a clinical interventional CBCT. The proposed anatomy-aware motion compensation framework presented a promising approach for improving the utility of CBCT for intra-procedural vascular imaging, facilitating selective embolization procedures.

Effects of intestine-specific deletion of FGF15 on the development of fatty liver disease with vertical sleeve gastrectomy.

BACKGROUND: Vertical sleeve gastrectomy (SGx) is a type of bariatric surgery to treat morbid obesity and metabolic dysfunction-associated steatotic liver disease (MASLD). The molecular mechanisms of SGx to improve MASLD are unclear, but increased bile acids (BAs) and FGF19 (mouse FGF15) were observed. FGF15/19 is expressed in the ileum in response to BAs and is critical in not only suppressing BA synthesis in the liver but also promoting energy expenditure. We hypothesized the reduction of obesity and resolution of MASLD by SGx may be mediated by FGF15/19. METHODS: First, we conducted hepatic gene expression analysis in obese patients undergoing SGx, with the results showing increased expression of FGF19 in obese patients' livers. Next, we used wild-type and intestine-specific Fgf15 knockout mice (Fgf15ile-/-) to determine the effects of FGF15 deficiency on improving the metabolic effects. RESULTS: SGx improved metabolic endpoints in both genotypes, evidenced by decreased obesity, improved glucose tolerance, and reduced MASLD progression. However, Fgf15ile-/- mice showed better improvement compared to wild-type mice after SGx, suggesting that other mediators than FGF15 are also responsible for the beneficial effects of FGF15 deficiency. Further gene expression analysis in brown adipose tissue suggests increased thermogenesis. CONCLUSIONS: FGF15 deficiency, the larger BA pool and higher levels of secondary BAs may increase energy expenditure in extrahepatic tissues, which may be responsible for improved metabolic functions following SGx.

Highly Invasive Biliary Cancer Presenting as Multiple Extrabiliary Lesions Masquerading as Abscesses.

Carcinosarcomas of the biliary tract are an extremely rare type of malignancy and may be low on a differential when presenting as multiple metastatic masses. In this case report, we report a case of a female who presented with an aggressive late-stage disease whose initial workup did not indicate a malignant process. Further complicating her care, biopsy samples taken from extra-hepatic masses were culture-positive for Lactobacillus rhamnosu. Given the late stage of the patient's disease, hospice care was initiated. The patient passed away four months after the initial presentation.