Effect of tolvaptan on renal involvement in patients with autosomal dominant polycystic kidney disease according to different gene mutations.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is an inherited disorder caused by mutations in the polycystic kidney disease (PKD) gene. Although tolvaptan has benefits for renal involvement, the different effects depending on the gene mutation type are unknown. Thus, we explore the different effects of tolvaptan on the annual changes in total kidney volume (%TKV) and estimated glomerular filtration rate (eGFR) according to the gene mutation type in ADPKD patients. METHODS: In total, 135 ADPKD patients were screened, and 22 patients taking tolvaptan for at least a year were retrospectively studied at the Kurume University Hospital. We examined the decline in renal function and %TKV by computed tomography and analyzed the gene mutation. Patients were classified into the following four groups according to gene mutation type: PKD1-truncated, PKD1-non-truncated, PKD2, and mutation not found. Patients were treated with tolvaptan, and the effects of tolvaptan were analyzed according to the gene mutation type. RESULTS: Patients (age: 52.3 ± 11.2 years) were administered tolvaptan at a dose of 45 or 60 mg. No variation was observed in the annual changes in eGFR (%eGFR) (before: - 10.5% ± 13.9%, after: - 14.4% ± 8.1%, P = 0.139), whereas %TKV was significantly improved after the tolvaptan treatment (before: 14.9% ± 8.0%, after: - 5.4% ± 7.6%, P < 0.001). Unlike %eGFR, tolvaptan treatment significantly improved %TKV, regardless of the type of gene mutation. CONCLUSIONS: A year treatment with tolvaptan significantly improved %TKV in patients with ADPKD, regardless of the gene mutation type.

IgG4-Related Membranous Nephropathy with Acute Nephrotic Syndrome During Successful Steroid Maintenance Treatment for Type 1 Autoimmune Pancreatitis.

BACKGROUND Immunoglobulin G4 (IgG4)-related diseases (IgG4-RD) are systemic fibroinflammatory diseases that can develop asynchronously in multiple organs. IgG4-related kidney disease (IgG4-RKD) is generally characterized by tubulointerstitial nephritis but can also manifest as membranous nephropathy without tubulointerstitial nephritis. IgG4-related membranous nephropathy can present as a phenotype of systemic disorders, including autoimmune pancreatitis-associated diabetes mellitus; however, its clinical features remain unclear. CASE REPORT A 56-year-old Japanese man presented to our university hospital with bilateral edema of his lower legs. He had received a diagnosis of type 1 autoimmune pancreatitis and associated diabetes mellitus 16 months prior. He was successfully treated with oral glucocorticoids 25 mg/day of prednisolone as an initial dose, followed by titration down to a maintenance dose (5 mg/day), without recurrence of autoimmune pancreatitis. The pancreas showed atrophy and required basal-bolus insulin therapy owing to insulin insufficiency. Massive proteinuria and hypoalbuminemia with nephrotic syndrome on examination led to a renal biopsy to investigate the etiology and diagnosis of IgG4-RKD. Methylprednisolone and cyclosporine A were successfully administered to ameliorate the proteinuria and control systemic IgG4-RD with IgG4-related membranous nephropathy. CONCLUSIONS Ig4-RKD occurred despite maintenance treatment with prednisolone monotherapy and was controlled with methylprednisolone and cyclosporine A. Measurement of clinical parameters, including proteinuria, was important, and a renal biopsy finally established the diagnosis of IgG4-RKD. IgG4-RKD can present with progressive glomerular lesions and can be latent in cases diagnosed with diabetic kidney disease, particularly in patients with insulin insufficiency.

The need for application-based adaptation of deformable image registration.

PURPOSE: To utilize a deformable phantom to objectively evaluate the accuracy of 11 different deformable image registration (DIR) algorithms. METHODS: The phantom represents an axial plane of the pelvic anatomy. Urethane plastic serves as the bony anatomy and urethane rubber with three levels of Hounsfield units (HU) is used to represent fat and organs, including the prostate. A plastic insert is placed into the phantom to simulate bladder filling. Nonradiopaque markers reside on the phantom surface. Optical camera images of these markers are used to measure the positions and determine the deformation from the bladder insert. Eleven different DIR algorithms are applied to the full and empty-bladder computed tomography images of the phantom (fixed and moving volumes, respectively) to calculate the deformation. The algorithms include those from MIM Software (MIM) and Velocity Medical Solutions (VEL) and nine different implementations from the deformable image registration and adaptive radiotherapy toolbox for Matlab. These algorithms warp one image to make it similar to another, but must utilize a method for regularization to avoid physically unrealistic deformation scenarios. The mean absolute difference (MAD) between the HUs at the marker locations on one image and the calculated location on the other serves as a metric to evaluate the balance between image similarity and regularization. To demonstrate the effect of regularization on registration accuracy, an additional beta version of MIM was created with a variable smoothness factor that controls the emphasis of the algorithm on regularization. The distance to agreement between the measured and calculated marker deformations is used to compare the overall spatial accuracy of the DIR algorithms. This overall spatial accuracy is also utilized to evaluate the phantom geometry and the ability of the phantom soft-tissue heterogeneity to represent patient data. To evaluate the ability of the DIR algorithms to accurately transfer anatomical contours, the rectum is delineated on both the fixed and moving images. A Dice similarity coefficient is then calculated between the contour on the fixed image and that transferred, via the calculated deformation, from the moving to the fixed image. RESULTS: The phantom possesses sufficient soft-tissue heterogeneity to act as a proxy for patient data. Large discrepancies appear between the algorithms and the measured ground-truth deformation. VEL yields the smallest mean spatial error and a Dice coefficient of 0.90. MIM produces the lowest MAD value and the highest Dice coefficient of 0.96, but creates the largest spatial errors. Increasing the MIM smoothness factor above the default value improves the overall spatial accuracy, but the factor associated with the lowest mean error decreases the Dice coefficient to 0.85. CONCLUSIONS: Different applications of DIR require disparate balances between image similarity and regularization. A DIR algorithm that is optimized only for its ability to transfer anatomical contours will yield large deformation errors in homogeneous regions, which is problematic for dose mapping. For this reason, these algorithms must be tested for their overall spatial accuracy. The developed phantom is an objective tool for this purpose.