Blood derived treatment from two allogeneic sources for severe dry eye associated to keratopathy: a multicentre randomised cross over clinical trial

AIM

To compare the efficacy of cord blood and peripheral adult donor blood serum eyedrops, controlled for growth factor content, in the treatment of severe dry eye diseases (DED) resistant to conventional therapy.

METHODS

This was a multicentre randomised, double-masked, cross-over clinical trial. Sixty patients diagnosed as severe DED, associated to persistent corneal epithelial defects were randomised and equally assigned to group A (treated with cord blood serum (CBS)) or group B (treated with PBS), eyedrops administered eight times/day for 1 month. Primary outcome was the pretreatment and post-treatment change in corneal fluorescein staining. Secondary outcomes included the pretreatment and post-treatment change in Ocular Surface Disease Index (OSDI) questionnaire and Visual Analogue Score (VAS) of subjective symptoms, Schirmer I test, tear break-up time and conjunctival staining. Patients with relapse in signs or symptoms after further 2 months switched to the remaining group for one additional month. Data were statistically analysed (p<0.05).

RESULTS

Corneal staining was more significantly reduced after the CBS treatment, both VAS and OSDI score reduction was observed in both groups, but group A reported significantly less grittiness and pain. Nineteen patients shifted in the crossover period, the within individual comparison confirmed a better recovery in the CBS treatment period. Reduction in epithelial damage was positively associated with epidermal growth factor, transforming growth factorα and platelet-derived growth factor content. Levels of interleukins (IL-13) were positively associated with symptom decrease.

CONCLUSIONS

Overall, DED signs improved after both CBS and PBS treatments, with potential advantages of CBS for subjective symptoms and corneal damage reduction.

CLINICAL TRIAL REGISTRATION

NCT03064984.

Partial volume effect of SPECT images in PRRT with 177Lu labelled somatostatin analogues: A practical solution

BACKGROUND

At present activity quantification is one of the most critical step in dosimetry calculation, and Partial Volume Effect (PVE) one of the most important source of error. In recent years models based upon phantoms that incorporate hot spheres have been used to establish recovery models. In this context the goal of this study was to point out the most critical issues related to PVE and to establish a model closer to a biological imaging environment.

METHODS

Two different phantoms, filled with a ¹⁷⁷Lu solution, were used to obtain the PVE Recovery Coefficients (RCs): a phantom with spherical inserts and a phantom with organ-shaped inserts. Two additional phantoms with inserts of various geometrical shapes and an anthropomorphic phantom were acquired to compare the real activities to predicted values after PVE correction.

RESULTS

The RCs versus volume of the inserts produced two different curves, one for the spheres and one for the organs. After PVE correction, accuracy on activity quantification averaged over all inserts of three test phantoms passed from -26% to 1.3% (from 26% to 10% for absolute values).

CONCLUSION

RCs is a simple method for PVE correction easily applicable in clinical routine. The use of two different models for organs and lesions has permitted to closely mimic the situation in a living subject. A marked improvement in the quantification of activity was observed when PVE correction was adopted, even if further investigations should be performed for more accurate models of PVE corrections.

Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines

BACKGROUND AND PURPOSE

In this study we attempt to automatically classify individual patients with different parkinsonian disorders, making use of pattern recognition techniques to distinguish among several forms of parkinsonisms (multi-class classification), based on a set of binary classifiers that discriminate each disorder from all others.

METHODS

We combine diffusion tensor imaging, proton spectroscopy and morphometric-volumetric data to obtain MR quantitative markers, which are provided to support vector machines with the aim of recognizing the different parkinsonian disorders. Feature selection is used to find the most important features for classification. We also exploit a graph-based technique on the set of quantitative markers to extract additional features from the dataset, and increase classification accuracy.

RESULTS

When graph-based features are not used, the MR markers that are most frequently automatically extracted by the feature selection procedure reflect alterations in brain regions that are also usually considered to discriminate parkinsonisms in routine clinical practice. Graph-derived features typically increase the diagnostic accuracy, and reduce the number of features required.

CONCLUSIONS

The results obtained in the work demonstrate that support vector machines applied to multimodal brain MR imaging and using graph-based features represent a novel and highly accurate approach to discriminate parkinsonisms, and a useful tool to assist the diagnosis.

Evaluation of Dose Homogeneity in Cone-Beam Breast Computed Tomography

The aim of this study is to determine, via measurements on phantoms and Monte Carlo (MC) simulations, the dose distribution of absorbed dose in a cone-beam breast computed tomography scan. The absorbed dose volume distribution was measured inside a polyethylene cylindrical phantom, simulating adipose breast tissue, using LiF:Mg,Ti thermoluminescence dosimeters. A reasonable agreement (between 2 and 8%) between the simulated and measured data was observed. The 3D distribution of absorbed dose was evaluated at 40, 60 and 80 kV in a phantom simulating a pendant breast. MC simulations indicate a significantly lower spread of volume dose than in mammography. The dose variation along the radial distance in the simulated phantoms was in the range of 4‒14%. These findings might be useful when devising models for breast imaging dose assessment that take into account the uneven distribution of the glandular mass in the breast volume.

Fully automated VMAT treatment planning for advanced-stage NSCLC patients

PURPOSE

To develop a fully automated procedure for multicriterial volumetric modulated arc therapy (VMAT) treatment planning (autoVMAT) for stage III/IV non-small cell lung cancer (NSCLC) patients treated with curative intent.

MATERIALS AND METHODS

After configuring the developed autoVMAT system for NSCLC, autoVMAT plans were compared with manually generated clinically delivered intensity-modulated radiotherapy (IMRT) plans for 41 patients. AutoVMAT plans were also compared to manually generated VMAT plans in the absence of time pressure. For 16 patients with reduced planning target volume (PTV) dose prescription in the clinical IMRT plan (to avoid violation of organs at risk tolerances), the potential for dose escalation with autoVMAT was explored.

RESULTS

Two physicians evaluated 35/41 autoVMAT plans (85%) as clinically acceptable. Compared to the manually generated IMRT plans, autoVMAT plans showed statistically significant improved PTV coverage (V_95% increased by 1.1% ± 1.1%), higher dose conformity (R₅₀ reduced by 12.2% ± 12.7%), and reduced mean lung, heart, and esophagus doses (reductions of 0.9 Gy ± 1.0 Gy, 1.5 Gy ± 1.8 Gy, 3.6 Gy ± 2.8 Gy, respectively, all p < 0.001). To render the six remaining autoVMAT plans clinically acceptable, a dosimetrist needed less than 10 min hands-on time for fine-tuning. AutoVMAT plans were also considered equivalent or better than manually optimized VMAT plans. For 6/16 patients, autoVMAT allowed tumor dose escalation of 5-10 Gy.

CONCLUSION

Clinically deliverable, high-quality autoVMAT plans can be generated fully automatically for the vast majority of advanced-stage NSCLC patients. For a subset of patients, autoVMAT allowed for tumor dose escalation.

Towards breast tomography with synchrotron radiation at Elettra: first images

The aim of the SYRMA-CT collaboration is to set-up the first clinical trial of phase-contrast breast CT with synchrotron radiation (SR). In order to combine high image quality and low delivered dose a number of innovative elements are merged: a CdTe single photon counting detector, state-of-the-art CT reconstruction and phase retrieval algorithms. To facilitate an accurate exam optimization, a Monte Carlo model was developed for dose calculation using GEANT4. In this study, high isotropic spatial resolution (120 μm)(3) CT scans of objects with dimensions and attenuation similar to a human breast were acquired, delivering mean glandular doses in the range of those delivered in clinical breast CT (5-25 mGy). Due to the spatial coherence of the SR beam and the long distance between sample and detector, the images contain, not only absorption, but also phase information from the samples. The application of a phase-retrieval procedure increases the contrast-to-noise ratio of the tomographic images, while the contrast remains almost constant. After applying the simultaneous algebraic reconstruction technique to low-dose phase-retrieved data sets (about 5 mGy) with a reduced number of projections, the spatial resolution was found to be equal to filtered back projection utilizing a four fold higher dose, while the contrast-to-noise ratio was reduced by 30%. These first results indicate the feasibility of clinical breast CT with SR.

Free software for performing physical analysis of systems for digital radiography and mammography

PURPOSE

In this paper, the authors present a free software for assisting users in achieving the physical characterization of x-ray digital systems and image quality checks.

METHODS

The program was developed as a plugin of a well-known public-domain suite ImageJ. The software can assist users in calculating various physical parameters such as the response curve (also termed signal transfer property), modulation transfer function (MTF), noise power spectra (NPS), and detective quantum efficiency (DQE). It also includes the computation of some image quality checks: defective pixel analysis, uniformity, dark analysis, and lag.

RESULTS

The software was made available in 2009 and has been used during the last couple of years by many users who gave us valuable feedback for improving its usability. It was tested for achieving the physical characterization of several clinical systems for digital radiography and mammography. Various published papers made use of the outcomes of the plugin.

CONCLUSIONS

This software is potentially beneficial to a variety of users: physicists working in hospitals, staff working in radiological departments, such as medical physicists, physicians, engineers. The plugin, together with a brief user manual, are freely available and can be found online (www.medphys.it/downloads.htm). With our plugin users can estimate all three most important parameters used for physical characterization (MTF, NPS, and also DQE). The plugin can run on any operating system equipped with ImageJ suite. The authors validated the software by comparing MTF and NPS curves on a common set of images with those obtained with other dedicated programs, achieving a very good agreement.

Quantitative comparison between the commercial software STRATOS(®) by Philips and a homemade software for voxel-dosimetry in radiopeptide therapy

BACKGROUND

Targeted radionuclide therapy is a rapidly growing modality. A few commercial treatment planning systems are entering the market. However, some in-house systems are currently developed for a more flexible and customized dosimetry calculation at voxel-level. For this purpose, we developed a novel software, VoxelMed, and performed a comparison with the software STRATOS.

METHODS

The validation of both of them was undertaken using radioactive phantoms with different volume inserts. A cohort of 10 patients was also studied after a therapeutic administration of (177)Lu-labelled radiopeptides. The activity, number of disintegrations, absorbed dose and dose-volume histogram (DVH) were calculated for the phantoms and the kidneys in patients, which were the main critical organs at risk in this study.

RESULTS

In phantoms the absorbed doses computed with VoxelMed and STRATOS agree within 5%. In patients at the voxel-level the absorbed dose to kidneys (VoxelMed: mean 0.66 Gy/GBq) showed a limited difference of 5%, but with a remarkable range (-40%, +60%) between the two software packages. Voxel-dosimetry allows to estimate the dose non-homogeneities in volumes, which may be evaluated through DVHs.

CONCLUSION

This study demonstrates that a fully 3D voxel-dosimetry with multiple SPECT images is feasible by using home-made or commercial software package and absorbed dose results obtained are similar. The main difference between the studied tools was observed in the activity integration method (effective vs physical half-time to time activity curve tail). We believe that an effective half-time integration method produces a more accurate approximation of clinical uptake and resultant dosimetry.

Intrafraction prostate translations and rotations during hypofractionated robotic radiation surgery: dosimetric impact of correction strategies and margins

PURPOSE

To investigate the dosimetric impact of intrafraction prostate motion and the effect of robot correction strategies for hypofractionated CyberKnife treatments with a simultaneously integrated boost.

METHODS AND MATERIALS

A total of 548 real-time prostate motion tracks from 17 patients were available for dosimetric simulations of CyberKnife treatments, in which various correction strategies were included. Fixed time intervals between imaging/correction (15, 60, 180, and 360 seconds) were simulated, as well as adaptive timing (ie, the time interval reduced from 60 to 15 seconds in case prostate motion exceeded 3 mm or 2° in consecutive images). The simulated extent of robot corrections was also varied: no corrections, translational corrections only, and translational corrections combined with rotational corrections up to 5°, 10°, and perfect rotational correction. The correction strategies were evaluated for treatment plans with a 0-mm or 3-mm margin around the clinical target volume (CTV). We recorded CTV coverage (V100%) and dose-volume parameters of the peripheral zone (boost), rectum, bladder, and urethra.

RESULTS

Planned dose parameters were increasingly preserved with larger extents of robot corrections. A time interval between corrections of 60 to 180 seconds provided optimal preservation of CTV coverage. To achieve 98% CTV coverage in 98% of the treatments, translational and rotational corrections up to 10° were required for the 0-mm margin plans, whereas translational and rotational corrections up to 5° were required for the 3-mm margin plans. Rectum and bladder were spared considerably better in the 0-mm margin plans. Adaptive timing did not improve delivered dose.

CONCLUSIONS

Intrafraction prostate motion substantially affected the delivered dose but was compensated for effectively by robot corrections using a time interval of 60 to 180 seconds. A 0-mm margin required larger extents of additional rotational corrections than a 3-mm margin but resulted in lower doses to rectum and bladder.

On the beam direction search space in computerized non-coplanar beam angle optimization for IMRT-prostate SBRT

In a recent paper, we have published a new algorithm, designated 'iCycle', for fully automated multi-criterial optimization of beam angles and intensity profiles. In this study, we have used this algorithm to investigate the relationship between plan quality and the extent of the beam direction search space, i.e. the set of candidate beam directions that may be selected for generating an optimal plan. For a group of ten prostate cancer patients, optimal IMRT plans were made for stereotactic body radiation therapy (SBRT), mimicking high dose rate brachytherapy dosimetry. Plans were generated for five different beam direction input sets: a coplanar (CP) set and four non-coplanar (NCP) sets. For CP treatments, the search space consisted of 72 orientations (5° separations). The NCP CyberKnife (CK) space contained all directions available in the robotic CK treatment unit. The fully non-coplanar (F-NCP) set facilitated the highest possible degree of freedom in selecting optimal directions. CK(+) and CK(++) were subsets of F-NCP to investigate some aspects of the CK space. For each input set, plans were generated with up to 30 selected beam directions. Generated plans were clinically acceptable, according to an assessment of our clinicians. Convergence in plan quality occurred only after around 20 included beams. For individual patients, variations in PTV dose delivery between the five generated plans were minimal, as aimed for (average spread in V(95): 0.4%). This allowed plan comparisons based on organ at risk (OAR) doses, with the rectum considered most important. Plans generated with the NCP search spaces had improved OAR sparing compared to the CP search space, especially for the rectum. OAR sparing was best with the F-NCP, with reductions in rectum D(Mean), V(40Gy), V(60Gy) and D(2%) compared to CP of 25%, 35%, 37% and 8%, respectively. Reduced rectum sparing with the CK search space compared to F-NCP could be largely compensated by expanding CK with beams with relatively large direction components along the superior-inferior axis (CK(++)). Addition of posterior beams (CK(++) → F-NCP) did not lead to further improvements in OAR sparing. Plans with 25 beams clearly performed better than 11-beam plans. For CP plans, an increase from 11 to 25 involved beams resulted in reductions in rectum D(Mean), V(40Gy), V(60Gy) and D(2%) of 39%, 57%, 64% and 13%, respectively.

Physical and clinical comparison between a screen-film system and a dual-side reading mammography-dedicated computed radiography system

BACKGROUND

Digital mammography systems, thanks to a physical performance better than conventional screen-film units, have the potential of reducing the dose to patients, without decreasing the diagnostic accuracy.

PURPOSE

To achieve a physical and clinical comparison between two systems: a screen-film plate and a dual-side computed radiography system (CRM; FUJIFILM FCR 5000 MA).

MATERIAL AND METHODS

A unique feature of the FCR 5000 MA system is that it has a clear support medium, allowing light emitted during the scanning process to be detected on the "back" of the storage phosphor plate, considerably improving the system's efficiency. The system's physical performance was tested by means of a quantitative analysis, with calculation of the modulation transfer function, detective quantum efficiency, and contrast-detail analysis; subsequently, the results were compared with those achieved using a screen-film system (SFM; Eastmann Kodak MinR-MinR 2000). A receiver operating characteristic (ROC) analysis was then performed on 120 paired clinical images obtained in a craniocaudal projection with the conventional SFM system under standard exposure conditions and also with the CRM system working with a dose reduced by 35% (average breast thickness: 4.3 cm; mean glandular dose: 1.45 mGy). CRM clinical images were interpreted both in hard copy and in soft copy.

RESULTS

The ROC analysis revealed that the performances of the two systems (SFM and CRM with reduced dose) were similar (P>0.05): the diagnostic accuracy of the two systems, when valued in terms of the area underneath the ROC curve, was found to be 0.74 for the SFM, 0.78 for the CRM (hard copy), and 0.79 for the CRM (soft copy).

CONCLUSION

The outcome obtained from our experiments shows that the use of the dual-side CRM system is a very good alternative to the screen-film system.

Computer-aided mass detection in mammography: false positive reduction via gray-scale invariant ranklet texture features

In this work, gray-scale invariant ranklet texture features are proposed for false positive reduction (FPR) in computer-aided detection (CAD) of breast masses. Two main considerations are at the basis of this proposal. First, false positive (FP) marks surviving our previous CAD system seem to be characterized by specific texture properties that can be used to discriminate them from masses. Second, our previous CAD system achieves invariance to linear/nonlinear monotonic gray-scale transformations by encoding regions of interest into ranklet images through the ranklet transform, an image transformation similar to the wavelet transform, yet dealing with pixels' ranks rather than with their gray-scale values. Therefore, the new FPR approach proposed herein defines a set of texture features which are calculated directly from the ranklet images corresponding to the regions of interest surviving our previous CAD system, hence, ranklet texture features; then, a support vector machine (SVM) classifier is used for discrimination. As a result of this approach, texture-based information is used to discriminate FP marks surviving our previous CAD system; at the same time, invariance to linear/nonlinear monotonic gray-scale transformations of the new CAD system is guaranteed, as ranklet texture features are calculated from ranklet images that have this property themselves by construction. To emphasize the gray-scale invariance of both the previous and new CAD systems, training and testing are carried out without any in-between parameters' adjustment on mammograms having different gray-scale dynamics; in particular, training is carried out on analog digitized mammograms taken from a publicly available digital database, whereas testing is performed on full-field digital mammograms taken from an in-house database. Free-response receiver operating characteristic (FROC) curve analysis of the two CAD systems demonstrates that the new approach achieves a higher reduction of FP marks when compared to the previous one. Specifically, at 60%, 65%, and 70% per-mammogram sensitivity, the new CAD system achieves 0.50, 0.68, and 0.92 FP marks per mammogram, whereas at 70%, 75%, and 80% per-case sensitivity it achieves 0.37, 0.48, and 0.71 FP marks per mammogram, respectively. Conversely, at the same sensitivities, the previous CAD system reached 0.71, 0.87, and 1.15 FP marks per mammogram, and 0.57, 0.73, and 0.92 FPs per mammogram. Also, statistical significance of the difference between the two per-mammogram and per-case FROC curves is demonstrated by the p-value < 0.001 returned by jackknife FROC analysis performed on the two CAD systems.

Comparison of different commercial FFDM units by means of physical characterization and contrast-detail analysis

The purpose of this study was to perform a complete evaluation of three pieces of clinical digital mammography equipment. Image quality was assessed by performing physical characterization and contrast-detail (CD) analysis. We considered three different FFDM systems: a computed radiography unit (Fuji "FCR 5000 MA") and two flat-panel units, the indirect conversion a-Si based GE "Senographe 2000D" and the direct conversion a-Si based IMS "Giotto Image MD." The physical characterization was estimated by measuring the MTF, NNPS, and DQE of the detectors with no antiscatter grid and over the clinical range of exposures. The CD analysis was performed using a CDMAM 3.4 phantom and custom software designed for automatic computation of the contrast-detail curves. The physical characterization of the three digital systems confirms the excellent MTF properties of the direct conversion flat-panel detector (FPD). We performed a relative standard deviation (RSD) analysis, for investigating the different components of the noise presented by the three systems. It turned out that the two FPDs show a significant additive component, whereas for the CR system the statistical noise is dominant. The multiplicative factor is a minor constituent for all the systems. The two FPDs demonstrate better DQE, with respect to the CR system, for exposures higher than 70 microGy. The CD analysis indicated that the three systems are not statistically different for detail objects with a diameter greater than 0.3 mm. However, the IMS system showed a statistically significant different response for details smaller than 0.3 mm. In this case, the poor response of the a-Se detector could be attributed to its high-frequency noise characteristics, since its MTF, NEQ, and DQE are not inferior to those of the other systems. The CD results were independent of exposure level, within the investigated clinical range. We observed slight variations in the CD results, due to the changes in the visualization parameters (window/level and magnification factor). This suggests that radiologists would benefit from viewing images using varied window/level and magnification.

A novel featureless approach to mass detection in digital mammograms based on support vector machines

In this work, we present a novel approach to mass detection in digital mammograms. The great variability of the appearance of masses is the main obstacle to building a mass detection method. It is indeed demanding to characterize all the varieties of masses with a reduced set of features. Hence, in our approach we have chosen not to extract any feature, for the detection of the region of interest; in contrast, we exploit all the information available on the image. A multiresolution overcomplete wavelet representation is performed, in order to codify the image with redundancy of information. The vectors of the very-large space obtained are then provided to a first support vector machine (SVM) classifier. The detection task is considered here as a two-class pattern recognition problem: crops are classified as suspect or not, by using this SVM classifier. False candidates are eliminated with a second cascaded SVM. To further reduce the number of false positives, an ensemble of experts is applied: the final suspect regions are achieved by using a voting strategy. The sensitivity of the presented system is nearly 80% with a false-positive rate of 1.1 marks per image, estimated on images coming from the USF DDSM database.

An SVM classifier to separate false signals from microcalcifications in digital mammograms

In this paper we investigate the feasibility of using an SVM (support vector machine) classifier in our automatic system for the detection of clustered microcalcifications in digital mammograms. SVM is a technique for pattern recognition which relies on the statistical learning theory. It minimizes a function of two terms: the number of misclassified vectors of the training set and a term regarding the generalization classifier capability. We compare the SVM classifier with an MLP (multi-layer perceptron) in the false-positive reduction phase of our detection scheme: a detected signal is considered either microcalcification or false signal, according to the value of a set of its features. The SVM classifier gets slightly better results than the MLP one (Az value of 0.963 against 0.958) in the presence of a high number of training data; the improvement becomes much more evident (Az value of 0.952 against 0.918) in training sets of reduced size. Finally, the setting of the SVM classifier is much easier than the MLP one.