Hepatocellular carcinoma response to transcatheter arterial chemoembolisation using automatically generated pre-therapeutic tumour volumes by a random forest-based segmentation protocol.

AIM: To demonstrate the feasibility of correlating pre-therapeutic volumes and residual liver volume (RLV) with clinical outcomes: time to progression (TTP) and overall survival (OS) in hepatocellular carcinoma (HCC) treated with transcatheter arterial chemoembolisation (TACE). MATERIALS AND METHODS: TTP was calculated from a database of 105 patients, receiving first-line treatment with TACE. TTP cut-off for stratifying patients into responders and non-responders was 28 weeks. Pre-treatment tumour and liver volumes were correlated with the TTP and OS following treatment. Univariate cox-regression model was used to assess whether these volumes could predict TTP and/or OS. Kaplan-Meier analysis with log-rank test was used to compare the TTP between high and low volume groups for viable, necrotic, and total tumour. Kaplan-Meier analysis was performed comparing the OS of 10 patients with the longest TTP (mean=122 weeks) in the responder group and 10 patients with the shortest TTP (mean=7 weeks) in the non-responder group. RESULTS: HCC in high tumour volume groups had a shorter TTP than lesions in low tumour volume groups (p=0.05, p=0.04, p=0.02, for enhancing, non-enhancing, total tumour groups, respectively). A negative (correlation coefficient [CC] 0.3) linear correlation between TTP and tumour volumes, and a positive linear correlation between TTP and residual liver volumes were also demonstrated (CC 0.3). Patients with the longest TTP had a higher OS than with the shortest TTP (p=0.03). CONCLUSION: This demonstrates the feasibility of predicting treatment response of HCC to TACE using volumetric measurements of pre-treatment lesion and the feasibility of correlating RLV with TACE outcome data in HCC patients.

Machine learning-based texture analysis for differentiation of large adrenal cortical tumours on CT.

AIM: To compare the efficacy of computed tomography (CT) texture analysis and conventional evaluation by radiologists for differentiation between large adrenal adenomas and carcinomas. MATERIALS AND METHODS: Quantitative CT texture analysis was used to evaluate 54 histopathologically proven adrenal masses (mean size=5.9 cm; range=4.1-10 cm) from 54 patients referred to Anderson Cancer Center from January 2002 through April 2014. The patient group included 32 women (mean age at mass evaluation=59 years) and 22 men (mean age at mass evaluation=61 years). Adrenal lesions seen on precontrast and venous-phase CT images were labelled by three different readers, and the labels were used to generate intensity- and geometry-based textural features. The textural features and the attenuation values were considered as input values for a random forest-based classifier. Similarly, the adrenal lesions were classified by two different radiologists based on morphological criteria. Prediction accuracy and interobserver agreement were compared. RESULTS: The textural predictive model achieved a mean accuracy of 82%, whereas the mean accuracy for the radiologists was 68.5% (p<0.0001). The interobserver agreements between the predictive model and radiologists 1 and 2 were 0.44 (p<0.0005; 95% confidence interval [CI]: 0.25-0.62) and 0.47 (p<0.0005; 95% CI: 0.28-0.66), respectively. The Dice similarity coefficient between the readers' image labels was 0.875±0.04. CONCLUSION: CT texture analysis of large adrenal adenomas and carcinomas is likely to improve CT evaluation of adrenal cortical tumours.

Correlation between the temperature dependence of intrinsic MR parameters and thermal dose measured by a rapid chemical shift imaging technique.

In order to investigate simultaneous MR temperature imaging and direct validation of tissue damage during thermal therapy, temperature-dependent signal changes in proton resonance frequency (PRF) shifts, R(2)* values, and T1-weighted amplitudes are measured from one technique in ex vivo tissue. Using a multigradient echo acquisition and the Stieglitz-McBride algorithm, the temperature sensitivity coefficients of these parameters are measured in each tissue at high spatiotemporal resolutions (1.6 x 1.6 x 4 mm 3,≤ 5sec) at the range of 25-61 °C. Non-linear changes in MR parameters are examined and correlated with an Arrhenius rate dose model of thermal damage. Using logistic regression, the probability of changes in these parameters is calculated as a function of thermal dose to determine if changes correspond to thermal damage. Temperature sensitivity of R(2)* and, in some cases, T1-weighted amplitudes are statistically different before and after thermal damage occurred. Significant changes in the slopes of R(2)* as a function of temperature are observed. Logistic regression analysis shows that these changes could be accurately predicted using the Arrhenius rate dose model (Ω = 1.01 ± 0.03), thereby showing that the changes in R(2)* could be direct markers of protein denaturation. Overall, by using a chemical shift imaging technique with simultaneous temperature estimation, R(2)* mapping and T1-W imaging, it is shown that changes in the sensitivity of R(2)* and, to a lesser degree, T1-W amplitudes are measured in ex vivo tissue when thermal damage is expected to occur. These changes could possibly be used for direct validation of thermal damage in contrast to model-based predictions.

Magnetic resonance temperature imaging validation of a bioheat transfer model for laser-induced thermal therapy.

PURPOSE: Magnetic resonance-guided laser-induced thermal therapy (MRgLITT) is currently undergoing initial safety and feasibility clinical studies for the treatment of intracranial lesions in humans. As studies progress towards evaluation of treatment efficacy, predictive computational models may play an important role for prospective 3D treatment planning. The current work critically evaluates a computational model of laser induced bioheat transfer against retrospective multiplanar MR thermal imaging (MRTI) in a canine model of the MRgLITT procedure in the brain. METHODS: A 3D finite element model of the bioheat transfer that couples Pennes equation to a diffusion theory approximation of light transport in tissue is used. The laser source is modelled conformal with the applicator geometry. Dirichlet boundary conditions are used to model the temperature of the actively cooled catheter. The MRgLITT procedure was performed on n = 4 canines using a 1-cm diffusing tip 15-W diode laser (980 nm). A weighted L2norm is used as the metric of comparison between the spatiotemporal MR-derived temperature estimates and model prediction. RESULTS: The normalised error history between the computational models and MRTI was within 1-4 standard deviations of MRTI noise. Active cooling models indicate that the applicator temperature has a strong effect on the maximum temperature reached, but does not significantly decrease the tissue temperature away from the active tip. CONCLUSIONS: Results demonstrate the computational model of the bioheat transfer may provide a reasonable approximation of the laser-tissue interaction, which could be useful for treatment planning, but cannot readily replace MR temperature imaging in a complex environment such as the brain.

Estimating Local Cellular Density in Glioma Using MR Imaging Data.

BACKGROUND AND PURPOSE: Increased cellular density is a hallmark of gliomas, both in the bulk of the tumor and in areas of tumor infiltration into surrounding brain. Altered cellular density causes altered imaging findings, but the degree to which cellular density can be quantitatively estimated from imaging is unknown. The purpose of this study was to discover the best MR imaging and processing techniques to make quantitative and spatially specific estimates of cellular density. MATERIALS AND METHODS: We collected stereotactic biopsies in a prospective imaging clinical trial targeting untreated patients with gliomas at our institution undergoing their first resection. The data included preoperative MR imaging with conventional anatomic, diffusion, perfusion, and permeability sequences and quantitative histopathology on biopsy samples. We then used multiple machine learning methodologies to estimate cellular density using local intensity information from the MR images and quantitative cellular density measurements at the biopsy coordinates as the criterion standard. RESULTS: The random forest methodology estimated cellular density with R 2 = 0.59 between predicted and observed values using 4 input imaging sequences chosen from our full set of imaging data (T2, fractional anisotropy, CBF, and area under the curve from permeability imaging). Limiting input to conventional MR images (T1 pre- and postcontrast, T2, and FLAIR) yielded slightly degraded performance (R2 = 0.52). Outputs were also reported as graphic maps. CONCLUSIONS: Cellular density can be estimated with moderate-to-strong correlations using MR imaging inputs. The random forest machine learning model provided the best estimates. These spatially specific estimates of cellular density will likely be useful in guiding both diagnosis and treatment.

Imaging-Based Algorithm for the Local Grading of Glioma.

BACKGROUND AND PURPOSE: Gliomas are highly heterogeneous tumors, and optimal treatment depends on identifying and locating the highest grade disease present. Imaging techniques for doing so are generally not validated against the histopathologic criterion standard. The purpose of this work was to estimate the local glioma grade using a machine learning model trained on preoperative image data and spatially specific tumor samples. The value of imaging in patients with brain tumor can be enhanced if pathologic data can be estimated from imaging input using predictive models. MATERIALS AND METHODS: Patients with gliomas were enrolled in a prospective clinical imaging trial between 2013 and 2016. MR imaging was performed with anatomic, diffusion, permeability, and perfusion sequences, followed by image-guided stereotactic biopsy before resection. An imaging description was developed for each biopsy, and multiclass machine learning models were built to predict the World Health Organization grade. Models were assessed on classification accuracy, Cohen κ, precision, and recall. RESULTS: Twenty-three patients (with 7/9/7 grade II/III/IV gliomas) had analyzable imaging-pathologic pairs, yielding 52 biopsy sites. The random forest method was the best algorithm tested. Tumor grade was predicted at 96% accuracy (κ = 0.93) using 4 inputs (T2, ADC, CBV, and transfer constant from dynamic contrast-enhanced imaging). By means of the conventional imaging only, the overall accuracy decreased (89% overall, κ = 0.79) and 43% of high-grade samples were misclassified as lower-grade disease. CONCLUSIONS: We found that local pathologic grade can be predicted with a high accuracy using clinical imaging data. Advanced imaging data improved this accuracy, adding value to conventional imaging. Confirmatory imaging trials are justified.

A compressed sensing approach to immobilized nanoparticle localization for superparamagnetic relaxometry.

Superparamagnetic relaxometry (SPMR) exploits the unique magnetic properties of targeted superparamagnetic iron oxide nanoparticles (SPIOs) to detect small numbers of cancer cells. Reconstruction of the spatial distribution of cancer-bound nanoparticles requires solving an ill-posed inverse problem. The current method, multiple source analysis (MSA), uses a least-squares fit to determine the strength and location of a pre-determined number of magnetic dipoles. In this proof-of-concept study, we propose the application of a sparsity averaged reweighting algorithm (SARA) for volumetric reconstruction of immobilized nanoparticle distributions. We first calibrate the parameters that define the location of the sensors in the forward model of measurement physics. Using this optimized model, we evaluated the performance of the algorithms on various configurations of single and multiple point-source phantoms. We investigated the effect of the data fidelity parameter, voxel size, and iterative reweighting on the reconstruction produced by SARA. We found that the calibrated physics model can predict the detected field values within 5% of the measured data. When only a single source was present, both algorithms were able to detect as little as 0.5 µg of immobilized particles. However, when two sources were measured simultaneously, MSA failed to detect sources containing as much as 10 µg of particles, while SARA detected all of the sources containing at least 5 µg of particles. We show that a suitable data fidelity parameter can be selected objectively, and the total magnitude and location of a point source reconstructed by SARA is not sensitive to voxel size. Detection and localization of multiple small clusters of nanoparticles is a crucial step in SPMR-based diagnostic applications. Our algorithm overcomes the need to know the number of dipoles before reconstruction and improves the sensitivity of the reconstruction when multiple sources are present.

Dynamic Data-Driven Finite Element Models for Laser Treatment of Cancer.

Elevating the temperature of cancerous cells is known to increase their susceptibility to subsequent radiation or chemotherapy treatments, and in the case in which a tumor exists as a well-defined region, higher intensity heat sources may be used to ablate the tissue. These facts are the basis for hyperthermia based cancer treatments. Of the many available modalities for delivering the heat source, the application of a laser heat source under the guidance of real-time treatment data has the potential to provide unprecedented control over the outcome of the treatment process [7, 18]. The goals of this work are to provide a precise mathematical framework for the real-time finite element solution of the problems of calibration, optimal heat source control, and goal-oriented error estimation applied to the equations of bioheat transfer and demonstrate that current finite element technology, parallel computer architecture, data transfer infrastructure, and thermal imaging modalities are capable of inducing a precise computer controlled temperature field within the biological domain.

Performance Assessment for Brain MR Imaging Registration Methods.

BACKGROUND AND PURPOSE: Clinical brain MR imaging registration algorithms are often made available by commercial vendors without figures of merit. The purpose of this study was to suggest a rational performance comparison methodology for these products. MATERIALS AND METHODS: Twenty patients were imaged on clinical 3T scanners by using 4 sequences: T2-weighted, FLAIR, susceptibility-weighted angiography, and T1 postcontrast. Fiducial landmark sites (n = 1175) were specified throughout these image volumes to define identical anatomic locations across sequences. Multiple registration algorithms were applied by using the T2 sequence as a fixed reference. Euclidean error was calculated before and after each registration and compared with a criterion standard landmark registration. The Euclidean effectiveness ratio is the fraction of Euclidean error remaining after registration, and the statistical effectiveness ratio is similar, but accounts for dispersion and noise. RESULTS: Before registration, error values for FLAIR, susceptibility-weighted angiography, and T1 postcontrast were 2.07 ± 0.55 mm, 2.63 ± 0.62 mm, and 3.65 ± 2.00 mm, respectively. Postregistration, the best error values for FLAIR, susceptibility-weighted angiography, and T1 postcontrast were 1.55 ± 0.46 mm, 1.34 ± 0.23 mm, and 1.06 ± 0.16 mm, with Euclidean effectiveness ratio values of 0.493, 0.181, and 0.096 and statistical effectiveness ratio values of 0.573, 0.352, and 0.929 for rigid mutual information, affine mutual information, and a commercial GE registration, respectively. CONCLUSIONS: We demonstrate a method for comparing the performance of registration algorithms and suggest the Euclidean error, Euclidean effectiveness ratio, and statistical effectiveness ratio as performance metrics for clinical registration algorithms. These figures of merit allow registration algorithms to be rationally compared.

Accelerated magnetic resonance thermometry in the presence of uncertainties.

A model-based information theoretic approach is presented to perform the task of magnetic resonance (MR) thermal image reconstruction from a limited number of observed samples on k-space. The key idea of the proposed approach is to optimally detect samples of k-space that are information-rich with respect to a model of the thermal data acquisition. These highly informative k-space samples can then be used to refine the mathematical model and efficiently reconstruct the image. The information theoretic reconstruction was demonstrated retrospectively in data acquired during MR-guided laser induced thermal therapy (MRgLITT) procedures. The approach demonstrates that locations with high-information content with respect to a model-based reconstruction of MR thermometry may be quantitatively identified. These information-rich k-space locations are demonstrated to be useful as a guide for k-space undersampling techniques. The effect of interactively increasing the predicted number of data points used in the subsampled model-based reconstruction was quantified using the L2-norm of the distance between the subsampled and fully sampled reconstruction. Performance of the proposed approach was also compared with uniform rectilinear subsampling and variable-density Poisson disk subsampling techniques. The proposed subsampling scheme resulted in accurate reconstructions using a small fraction of k-space points, suggesting that the reconstruction technique may be useful in improving the efficiency of thermometry data temporal resolution.

Correlation between dynamic MRI and outcome in patients with malignant gliomas.

We assessed the correlation between dynamic MRI results and clinical outcomes in patients with malignant gliomas. Rapid serial MRIs were obtained after bolus injection of gadolinium that resulted in an initial fast uptake followed by a slow uptake of contrast. The maximum rate of uptake and delayed rate of uptake were correlated with survival and prognostic covariates such as age and histology. In 121 subjects, higher maximum uptake rates, 3.6 signal intensity units per second or greater, were associated with shorter survival (p = 0.0066). The correlation of delayed rate of uptake with survival was less significant. After adjusting for age, histology, and Karnofsky performance score, the maximum rate of uptake remained more significantly correlated with survival than the delayed rate of uptake. Thirty-one patients had surgery within 1 month of dynamic MRI, and those with glioblastoma multiforme or anaplastic gliomas had higher maximum rates of uptake than those with pure necrosis or mixed tumor and necrosis (p = 0.022). No correlation between delayed rate of uptake and histology was seen in this group of patients. Our results suggest that the maximum rate of uptake in dynamic MRI can be a prognostic measure for patients with malignant gliomas. Further prospective study is needed to assess the utility of this technique for evaluating brain tumors.

Dosimetry characteristics of four fast neutron generators involved in RTOG interinstitutional clinical trials.

PURPOSE: To demonstrate the consistency of dosimetry data used for four fast neutron generators involved in inter-institutional clinical trials. METHODS AND MATERIALS: Central-axis dosimetry characteristics (field size dependence, percentage depth dose, beam modifier factors) at four institutions were measured by independent physicists from the Radiological Physics Center. These measurements were made in water with a single set of dosimetry equipment using tissue equivalent ionization chambers. Measurements were made with the chamber cavities filled with stationary air and flowing tissue-equivalent gas. All measurements were performed using techniques developed by the Radiological Physics Center for conventional radiotherapy equipment. The results of our measurements were compared to the data used by the institution to determine the consistency of patient doses reported to the Radiation Therapy Oncology Group. RESULTS: The agreement of the Radiological Physics Center and institution data is similar to what is typically found with conventional radiotherapy equipment. CONCLUSIONS: The doses reported by these institutions to the Fast Neutron Working Group of the Radiation Therapy Oncology Group are consistent, within accepted clinical criteria.

Quality assurance for intraoperative electron radiotherapy clinical trials: ionization chamber and mailable thermoluminescent dosimeter results.

Ionization chamber and thermoluminescent dosimeter measurements were made to verify the dosimetry data provided to the Radiation Therapy Chart Review office of interinstitutional electron intraoperative radiotherapy clinical trials. The ionization measurements included intraoperative radiotherapy applicator output and depth dose measurements made at the stated 80% and 50% depths at 14 different radiotherapy facilities. Mailable thermoluminescent dosimeter measurements, including output and depth dose measurements were made at 16 institutions. The mailable thermoluminescent dosimeter results show similar inter-institutional agreement, both for output and depth dose comparison, with the corresponding ion chamber results for intraoperative radiotherapy applicators. These results are compared to similar measurements made for conventional electron applicators.

Therapeutic dosimetry for Cf-252 neutron brachytherapy of pelvic cancer.

252Cf (Cf) was used to treat tumors of the cervix and uterus with neutron brachytherapy (NT) in an ongoing clinical trial. Tandem and ovoids insertions were used and combinations of single and multiple applications along with high dose whole pelvic irradiation. Dosimetric analysis of treated cases for patterns of tissue dose were carried out. Tissue dose for Cf-NT was, in general, high for neutron components in the central pelvis only, and fell off rapidly with distance from the applicators. The majority and balance of therapeutic dose was contributed by low linear energy transfer (LET) high energy photon beam radiation to the whole pelvis. Comparison with fast neutron beam therapy (NBT) isodose curves showed that much more homogeneous neutron dose was delivered to the pelvic tumor and organs by NBT. Complication frequency has been reported to be higher for neutron beam therapy than for Cf-NT. It appears that the higher integral neutron biological dose to normal tissues for NBT compared to intracavitary Cf-NT probably contributed to the frequency of side effects.

Intraoperative electron beam radiation therapy: technique, dosimetry, and dose specification: report of task force 48 of the Radiation Therapy Committee, American Association of Physicists in Medicine.

Intraoperative radiation therapy (IORT) is a treatment modality whereby a large single dose of radiation is delivered to a surgically open, exposed cancer site. Typically, a beam of megavoltage electrons is directed at an exposed tumor or tumor bed through a specially designed applicator system. In the last few years, IORT facilities have proliferated around the world. The IORT technique and the applicator systems used at these facilities vary greatly in sophistication and design philosophy. The IORT beam characteristics vary for different designs of applicator systems. It is necessary to document the existing techniques of IORT, to detail the dosimetry data required for accurate delivery of the prescribed dose, and to have a uniform method of dose specification for cooperative clinical trials. The specific charge to the task group includes the following: (a) identify the multidisciplinary IORT team, (b) outline special considerations that must be addressed by an IORT program, (c) review currently available IORT techniques, (d) describe dosimetric measurements necessary for accurate delivery of prescribed dose, (e) describe dosimetric measurements necessary in documenting doses to the surrounding normal tissues, (f) recommend quality assurance procedures for IORT, (g) review methods of treatment documentation and verification, and (h) recommend methods of dose specification and recording for cooperative clinical trials.

Comparative ultraviolet action spectra (254-320 nm) of five "wild-type" eukaryotic microorganisms and Escherichia coli.

The action spectra of five eukaryotic organisms and the prokaryote, Escherichia coli, were examined over the wavelength range, 254-320 nm. Both the repair competent and three repair defective strains (E. coli, Caenorhabditis elegans, Saccharomyces) were examined. Tetrahymena pyriformis action spectra were performed with and without the excision repair inhibitor caffeine present. Others have observed that lethality, mutation, and the production of pyrimidine dimers show much the same wavelength dependence as DNA absorption. The results presented here demonstrate several action spectra which deviate from the DNA absorption spectra. Ultraviolet sensitization ratios (repair competent/repair defective) were also examined and were shown to change over the wavelength range. These findings suggest that DNA may not be the only important chromophore leading to cell death in the uv wavelength range studied. Since uv-B is of major importance in solar uv damage, these findings may also yield important implications for solar uv studies.

Evaluation of helical computed tomography scan parameters for vascular imaging.

Helical x-ray computed tomography (hCT) is the volume acquisition of image data in which the data set represents a series of projections obtained in a helical spatial distribution. Data acquisition times and spatial resolution are determined largely by two user defined parameters--collimation and pitch. Each combination of pitch and collimation results in a slice profile which can be considered as the apparent slice thickness. Careful selection of pitch and collimation allows the acquisition of up to 20 cm of axial data in a breathold or first pass of bolus contrast material. This makes helical CT an excellent technique for angiographic (CTA) studies. Additionally, slices can be reconstructed at any interval to reduce partial volume averaging, minimizing the beading artifacts seen in maximum intensity projections (MIP) when interslice resolution is poor. We have evaluated a range of collimation and pitches for clinical CTA. Additionally, three reconstruction filters were included to determine the optimal frequency (spatial) properties for these techniques. Objective and subjective analyses were performed. We found pitches of up to 1.5:1 to be acceptable for all collimations. For a given scan length (z direction), selection of thinner collimation and higher pitch resulted in better SNR and observer scoring for angiographic presentations.

Results of photon absorbed-dose measurements using the AAPM TG-21 protocol for accelerating potentials up to 26 MV.

The AAPM Task Group 21 protocol for the calibration of high-energy photon and electron beams was produced to accomplish essentially two goals: (1) incorporate the latest physical data available for calculating absorbed dose from ionization measurements and (2) to eliminate inconsistencies in absorbed dose measurements made with various ion chamber and phantom combinations. The ability of the protocol was assessed to consistently determine x-ray absorbed dose from measurements made with four Farmer-type chambers and one parallel-plate chamber in water, polystyrene, and acrylic phantoms. The measurements were performed using seven high-energy x-ray beams from 60Co to 26-MV nominal accelerating potential. The absorbed dose to water calculated from measurements made with the various chamber and phantom combinations were found to be consistent. The doses calculated for the two most common phantom materials, water and polystyrene, were found to be in excellent agreement. This resolved a 1.6% discrepancy in the absorbed dose determined from the two phantoms using the SCRAD protocol. The doses for acrylic phantoms were found to be approximately 1.2%, low for nominal accelerating potentials less than 8.8 MV. For accelerating potentials of 8.8 MV or greater the agreement was considerably better. The mean dose determined for the parallel-plate chamber from measurements in polystyrene was found to be within 0.7% of the mean dose determined using Farmer-type ion chambers in all phantom materials.

Performance analysis of a new semiorthogonal spline wavelet compression algorithm for tonal medical images.

Lossy image compression is thought to be a necessity as radiology moves toward a filmless environment. Compression algorithms based on the discrete cosine transform (DCT) are limited due to the infinite support of the cosine basis function. Wavelets, basis functions that have compact or nearly compact support, are mathematically better suited for decorrelating medical image data. A lossy compression algorithm based on semiorthogonal cubic spline wavelets has been implemented and tested on six different image modalities (magnetic resonance, x-ray computed tomography, single photon emission tomography, digital fluoroscopy, computed radiography, and ultrasound). The fidelity of the reconstructed wavelet images was compared to images compressed with a DCT algorithm for compression ratios of up to 40:1. The wavelet algorithm was found to have generally lower average error metrics and higher peak-signal-to-noise ratios than the DCT algorithm.

Electron beam central axis depth dose measurements.

Central axis depth dose measurements were made by the Radiological Physics Center on over 70 electron-producing machines used in radiation therapy. These data were consistent for each machine model and nominal energy. However, the data show that depth dose relations can vary significantly among different machine models for electron beams having the same nominal energy. Analysis shows that both the method used to achieve beam flatness and the mean incident electron energy determine the central axis depth dose curve past the depth of maximum dose. A linear relation of depth dose versus mean incident electron energy is used to predict depth dose to within 2 mm for most electron beams used clinically at depths greater than d95.