Performance assessment of time-domain optical brain imagers, part 2: nEUROPt protocol

The nEUROPt protocol is one of two new protocols developed within the European project nEUROPt to characterize the performances of time-domain systems for optical imaging of the brain. It was applied in joint measurement campaigns to compare the various instruments and to assess the impact of technical improvements. This protocol addresses the characteristic of optical brain imaging to detect, localize, and quantify absorption changes in the brain. It was implemented with two types of inhomogeneous liquid phantoms based on Intralipid and India ink with well-defined optical properties. First, small black inclusions were used to mimic localized changes of the absorption coefficient. The position of the inclusions was varied in depth and lateral direction to investigate contrast and spatial resolution. Second, two-layered liquid phantoms with variable absorption coefficients were employed to study the quantification of layer-wide changes and, in particular, to determine depth selectivity, i.e., the ratio of sensitivities for deep and superficial absorption changes. We introduce the tests of the nEUROPt protocol and present examples of results obtained with different instruments and methods of data analysis. This protocol could be a useful step toward performance tests for future standards in diffuse optical imaging

Objective assessment of image quality (OAIQ) in fluorescence-enhanced optical imaging

The statistical evaluation of molecular imaging approaches for detecting, diagnosing, and monitoring molecular response to treatment are required prior to their adoption. The assessment of fluorescence-enhanced optical imaging is particularly challenging since neither instrument nor agent has been established. Small animal imaging does not address the depth of penetration issues adequately and the risk of administering molecular optical imaging agents into patients remains unknown. Herein, we focus upon the development of a framework for OAIQ which includes a lumpy-object model to simulate natural anatomical tissue structure as well as the non-specific distribution of fluorescent contrast agents. This work is required for adoption of fluorescence-enhanced optical imaging in the clinic. Herein, the imaging system is simulated by the diffusion approximation of the time-dependent radiative transfer equation, which describes near infra-red light propagation through clinically relevant volumes. We predict the time-dependent light propagation within a 200 cc breast interrogated with 25 points of excitation illumination and 128 points of fluorescent light collection. We simulate the fluorescence generation from Cardio-Green at tissue target concentrations of 1, 0.5, and 0.25 µM with backgrounds containing 0.01 µM. The fluorescence boundary measurements for 1 cc spherical targets simulated within lumpy backgrounds of (i) endogenous optical properties (absorption and scattering), as well as (ii) exogenous fluorophore crosssection are generated with lump strength varying up to 100% of the average background. The imaging data are then used to validate a PMBF/CONTN tomographic reconstruction algorithm. Our results show that the image recovery is sensitive to the heterogeneous background structures. Further analysis on the imaging data by a Hotelling observer affirms that the detection capability of the imaging system is adversely affected by the presence of heterogeneous background structures. The above issue is also addressed using the human-observer studies wherein multiple cases of randomly located targets superimposed on random heterogeneous backgrounds are used in a “double-blind” situation. The results of this study show consistency with the outcome of above mentioned analyses. Finally, the Hotelling observer’s analysis is used to demonstrate (i) the inverse correlation between detectability and target depth, and (ii) the plateauing of detectability with improved excitation light rejection

Reducing Radiation Dose to the Female Breast During Conventional and Dedicated Breast Computed Tomography

The purpose of this study was to quantify the effectiveness of techniques intended to reduce dose to the breast during CT coronary angiography (CTCA) scans with respect to task-based image quality, and to evaluate the effectiveness of optimal energy weighting in improving contrast-to-noise ratio (CNR), and thus the potential for reducing breast dose, during energy-resolved dedicated breast CT. A database quantifying organ dose for several radiosensitive organs irradiated during CTCA, including the breast, was generated using Monte Carlo simulations. This database facilitates estimation of organ-specific dose deposited during CTCA protocols using arbitrary x-ray spectra or tube-current modulation schemes without the need to run Monte Carlo simulations. The database was used to estimate breast dose for simulated CT images acquired for a reference protocol and five protocols intended to reduce breast dose. For each protocol, the performance of two tasks (detection of signals with unknown locations) was compared over a range of breast dose levels using a task-based, signal-detectability metric: the estimator of the area under the exponential free-response relative operating characteristic curve, AFE. For large-diameter/medium-contrast signals, when maintaining equivalent AFE, the 80 kV partial, 80 kV, 120 kV partial, and 120 kV tube-current modulated protocols reduced breast dose by 85%, 81%, 18%, and 6%, respectively, while the shielded protocol increased breast dose by 68%. Results for the small-diameter/high-contrast signal followed similar trends, but with smaller magnitude of the percent changes in dose. The 80 kV protocols demonstrated the greatest reduction to breast dose, however, the subsequent increase in noise may be clinically unacceptable. Tube output for these protocols can be adjusted to achieve more desirable noise levels with lesser dose reduction. The improvement in CNR of optimally projection-based and image-based weighted images relative to photon-counting was investigated for six different energy bin combinations using a bench-top energy-resolving CT system with a cadmium zinc telluride (CZT) detector. The non-ideal spectral response reduced the CNR for the projection-based weighted images, while image-based weighting improved CNR for five out of the six investigated bin combinations, despite this non-ideal response, indicating potential for image-based weighting to reduce breast dose during dedicated breast CT

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities

Quantitative Techniques for PET/CT: A Clinical Assessment of the Impact of PSF and TOF

Tomographic reconstruction has been a challenge for many imaging applications, and it is particularly problematic for count-limited modalities such as Positron Emission Tomography (PET). Recent advances in PET, including the incorporation of time-of-flight (TOF) information and modeling the variation of the point response across the imaging field (PSF), have resulted in significant improvements in image quality. While the effects of these techniques have been characterized with simulations and mathematical modeling, there has been relatively little work investigating the potential impact of such methods in the clinical setting. The objective of this work is to quantify these techniques in the context of realistic lesion detection and localization tasks for a medical environment. Mathematical observers are used to first identify optimal reconstruction parameters and then later to evaluate the performance of the reconstructions. The effect on the reconstruction algorithms is then evaluated for various patient sizes and imaging conditions. The findings for the mathematical observers are compared to, and validated by, the performance of three experienced nuclear medicine physicians completing the same task

Real-time tissue viability assessment using near-infrared light

Despite significant advances in medical imaging technologies, there currently exist no tools to effectively assist healthcare professionals during surgical procedures. In turn, procedures remain subjective and dependent on experience, resulting in avoidable failure and significant quality of care disparities across hospitals. Optical techniques are gaining popularity in clinical research because they are low cost, non-invasive, portable, and can retrieve both fluorescence and endogenous contrast information, providing physiological information relative to perfusion, oxygenation, metabolism, hydration, and sub-cellular content. Near-infrared (NIR) light is especially well suited for biological tissue and does not cause tissue damage from ionizing radiation or heat. My dissertation has been focused on developing rapid imaging techniques for mapping endogenous tissue constituents to aid surgical guidance. These techniques allow, for the first time, video-rate quantitative acquisition over a large field of view (> 100 cm2) in widefield and endoscopic implementations. The optical system analysis has been focused on the spatial-frequency domain for its ease of quantitative measurements over large fields of view and for its recent development in real-time acquisition, single snapshot of optical properties (SSOP) imaging. Using these methods, this dissertation provides novel improvements and implementations to SSOP, including both widefield and endoscopic instrumentations capable of video-rate acquisition of optical properties and sample surface profile maps. In turn, these measures generate profile-corrected maps of hemoglobin concentration that are highly beneficial for perfusion and overall tissue viability. Also utilizing optical property maps, a novel technique for quantitative fluorescence imaging was also demonstrated, showing large improvement over standard and ratiometric methods. To enable real-time feedback, rapid processing algorithms were designed using lookup tables that provide a 100x improvement in processing speed. Finally, these techniques were demonstrated in vivo to investigate their ability for early detection of tissue failure due to ischemia. Both pre-clinical studies show endogenous contrast imaging can provide early measures of future tissue viability. The goal of this work has been to provide the foundation for real-time imaging systems that provide tissue constituent quantification for tissue viability assessments.2018-01-09T00:00:00

High-resolution photoacoustic vascular imaging in vivo using a large-aperture acoustic lens

Reflection-mode photoacoustic microscopy with dark-field laser pulse illumination and high frequency ultrasonic detection is used to non-invasively image blood vessels in the skin in vivo. Dark-field illumination minimizes the interference caused by strong photoacoustic signals from superficial structures. A high numerical-aperture acoustic lens provides high lateral resolution, 45-120 micrometers in this system while a broadband ultrasonic detection system provides high axial resolution, estimated to be ~15-20 micrometers. The optical illumination and ultrasonic detection are in a coaxial confocal configuration for optimal image quality. The system is capable of imaging optical-absorption contrast at up to 3 mm depth in biological tissue

Differential ultra-wideband microwave imaging for medical applications

Elektromagnetische Ultrabreitband-Sensorik und -Bildgebung bieten vielversprechende Perspektiven für verschiedene biomedizinische Anwendungen, da diese Wellen biologisches Gewebe durchdringen können. Dabei stellt der Einsatz von leistungsarmen und nichtionisierenden Mikrowellen eine gesundheitlich unbedenkliche Untersuchungsmethode dar. Eine der Herausforderungen im Bereich der ultrabreitbandigen Mikrowellensensorik ist dabei die Extraktion der diagnostisch relevanten Informationen aus den Messdaten, da aufgrund der komplexen Wellenausbreitung im Gewebe meist rechenaufwändige Methoden notwendig sind. Dieses Problem wird wesentlich vereinfacht, wenn sich die Streueigenschaften des zu untersuchenden Objektes zeitlich ändern. Diese zeitliche Varianz der Streueigenschaften kann mit Hilfe einer Differenzmessung über ein bestimmtes Zeitintervall ausgenutzt werden. Im Rahmen dieser Arbeit wird der differentielle Ansatz mittels Ultrabreitband-Sensorik für zwei medizinische Anwendungsszenarien betrachtet. Die dabei genutzten Messsysteme basieren auf dem M-Sequenzverfahren, welches an der Technischen Universität Ilmenau entwickelt wurde. Die erste Anwendung bezieht sich auf das nicht-invasive Temperaturmonitoring mittels Ultrabreitband-Technologie während einer Hyperthermiebehandlung. Hyperthermie ist eine Wärmetherapie zur Unterstützung onkologischer Behandlungen (z. B. Chemo- oder Strahlentherapie). Während einer solchen Behandlung wird das Tumorgewebe um 4 °C bis 8 °C erhöht. Dabei ist es wichtig, dass die Temperatur die obere Grenze von 45 °C nicht überschreitet. In diesem Zusammenhang bietet das differentielle Ultrabreitband-Monitoring eine vielversprechende Technik zur kontinuierlichen und nicht-invasiven Messung der Temperatur im Körperinneren. Der Ansatz basiert auf den temperaturabhängigen dielektrischen Eigenschaften von biologischem Gewebe. Dabei werden elektromagnetische Wellen mit einer geringen Leistung in das Untersuchungsmedium eingebracht, die sich gemäß den dielektrischen Eigenschaften von Gewebe ausbreiten. Wird eine Zielregion (bspw. Tumor) erwärmt, so ändern sich dessen dielektrische Eigenschaften, was zu einem sich ändernden Streuverhalten der elektromagnetischen Welle führt. Diese Änderungen können mittels Ultrabreitband-Sensorik erfasst werden. Für die Evaluierung der gemessenen Änderungen im Radarsignal ist es notwendig, die temperaturabhängigen dielektrischen Eigenschaften von Gewebe im Mikrowellenfrequenzbereich zu kennen. Aufgrund der wenigen in der Literatur vorhandenen temperaturabhängigen dielektrischen Eigenschaften von Gewebe über einen breiten Mikrowellenfrequenzbereich werden in dieser Arbeit die dielektrischen Eigenschaften für Leber, Muskel, Fett und Blut im Temperaturbereich zwischen 30 °C und 50 °C von 500 MHz bis 7 GHz erfasst. Hierzu wird zunächst ein Messaufbau für die temperaturabhängige dielektrische Spektroskopie von Gewebe, Gewebeersatz und Flüssigkeiten vorgestellt und die wesentlichen Einflussfaktoren auf die Messungen analysiert. Die Messdaten werden mit Hilfe eines temperaturabhängigen Cole-Cole Models modelliert, um die dielektrischen Eigenschaften für beliebige Werte im untersuchten Temperatur- und Frequenzbereich berechnen zu können. In einem weiteren Experiment wird die nicht-invasive Erfassung von Temperaturänderungen mittels Ultrabreitband-Technologie in einem experimentellen Messaufbau nachgewiesen. Die Ergebnisse zeigen, dass eine Temperaturänderung von 1 °C zu Differenzsignalen führt, welche mit der genutzten Ultrabreitband-Sensorik (M-Sequenz) detektierbar sind. Die zweite Anwendung befasst sich mit der kontrastbasierten Mikrowellen-Brustkrebsbildgebung. Aufgrund des physiologisch gegebenen geringen dielektrischen Kontrastes zwischen Drüsen- und Tumorgewebe kann durch den Einsatz von Kontrastmitteln, im Speziellen magnetischen Nanopartikeln, die Zuverlässigkeit einer Diagnose verbessert werden. Der Ansatz beruht darauf, dass funktionalisierte magnetische Nanopartikel in der Lage sind, sich selektiv im Tumorgewebe zu akkumulieren, nachdem diese intravenös verabreicht wurden. Unter der Bedingung, dass sich eine ausreichende Menge der Nanopartikel im Tumor angesammelt hat, können diese durch ein äußeres polarisierendes Magnetfeld moduliert werden. Aufgrund der Modulation ändert sich das Streuverhalten der magnetischen Nanopartikel, was wiederum zu einem sich ändernden Rückstreuverhalten führt. Diese Änderungen können mittels leistungsarmen elektromagnetischen Wellen detektiert werden. In dieser Arbeit wird die Detektierbarkeit und Bildgebung von magnetischen Nanopartikeln mittels Ultrabreitband-Sensorik im Mikrowellenfrequenzbereich in Hinblick auf die Brustkrebsdetektion betrachtet. Dabei werden zunächst verschiedene Einflussfaktoren, wie die Abhängigkeit der Masse der magnetischen Nanopartikel, die Magnetfeldstärke des äußeren Magnetfeldes sowie die Viskosität des Umgebungsmediums, in das die Nanopartikel eingebettet sind, auf die Detektierbarkeit der magnetischen Nanopartikel untersucht. Die Ergebnisse zeigen eine lineare Abhängigkeit zwischen dem gemessenen Radarsignal und der Masse der magnetischen Nanopartikel sowie einen nichtlinearen Zusammenhang zwischen der Antwort der magnetischen Nanopartikel und der Feldstärke des äußeren Magnetfeldes. Darüber hinaus konnten die magnetischen Nanopartikel für alle untersuchten Viskositäten erfolgreich detektiert werden. Basierend auf diesen Voruntersuchungen wird ein realistischer Messaufbau für die kontrastbasierte Brustkrebsbildgebung vorgestellt. Die Evaluierung des Messaufbaus erfolgt mittels Phantommessungen, wobei die verwendeten Phantommaterialien die dielektrischen Eigenschaften von biologischem Gewebe imitieren, um eine möglichst hohe Aussagekraft der Ergebnisse hinsichtlich eines praktischen Messszenarios zu erhalten. Dabei wird die Detektierbarkeit und Bildgebung der magnetischen Nanopartikel in Abhängigkeit der Tumortiefe analysiert. Die Ergebnisse zeigen, dass die magnetischen Nanopartikel erfolgreich detektiert werden können. Dabei hängt im dreidimensionalen Bild die Intensität des Messsignals, hervorgerufen durch die magnetischen Nanopartikel, von deren Position ab. Die Ursachen hierfür sind die pfadabhängige Dämpfung der elektromagnetischen Wellen, die inhomogene Ausleuchtung des Mediums mittels Mikrowellen, da eine gleichmäßige Anordnung der Antennen aufgrund der Magnetpole des Elektromagneten nicht möglich ist, sowie das inhomogene polarisierende Magnetfeld innerhalb des Untersuchungsmediums. In Bezug auf den letzten Aspekt wird das Magnetfeld im Untersuchungsbereich ausgemessen und ein Ansatz präsentiert, mit dem die Inhomogenität des Magnetfeldes kompensiert werden kann. Weiterhin wurden die Störeinflüsse des polarisierenden Magnetfeldes auf das Messsystem untersucht. In diesem Zusammenhang werden zwei verschiedene Modulationsarten (eine Modulation mit den zwei Zuständen AN/AUS und eine periodische Modulation) des äußeren polarisierenden Magnetfeldes analysiert. Es wird gezeigt, dass mit beiden Modulationen die magnetischen Nanopartikel bildgebend dargestellt werden können. Abschließend werden die Ergebnisse in Hinblick auf die Störeinflüsse sowie ein praktisches Anwendungsszenario diskutiert.Electromagnetic ultra-wideband sensing and imaging provide promising perspectives in various biomedical applications as these waves can penetrate biological tissue. The use of low-power and nonionizing electromagnetic waves in the microwave frequency range offers an examination method that is harmless to health. One of the challenges in the field of ultra-wideband microwave sensor technology is the extraction of diagnostically relevant information from the measurement data, since the complex wave propagation in tissue usually requires computationally intensive methods. This problem is simplified when the scattering properties of the object under observation change with time. Such a time variance of the scattering properties can be exploited by means of a differential measurement over a certain time interval. In this work, a differential approach using ultra-wideband sensing is considered for two medical applications. The measurement systems used in this work are based on the M-sequence technology developed at the Technische Universität Ilmenau. The first application relates to noninvasive temperature monitoring using ultra-wideband technology during hyperthermia treatment. Hyperthermia is a thermal therapy to support oncological treatments (e.g. chemotherapy or radiotherapy). During such a treatment, the tumor tissue is heated by 4 °C to 8 °C, whereby it is important that the temperature does not exceed the upper limit of 45 °C. In this context, differential ultra-wideband monitoring offers a promising technique for continuous and noninvasive temperature monitoring inside the body. The approach is based on the temperature-dependent dielectric properties of biological tissue. In this method, low power electromagnetic waves are emitted into the medium under investigation. These waves propagate according to the dielectric properties of tissue. If a target region (e.g. tumor) is heated, its dielectric properties will change, which leads to a changing scattering behavior of the electromagnetic wave. These changes can be detected in the measured reflection signals using ultra-wideband microwave technology. To evaluate the measured changes in the radar signal, it is necessary to know the temperature-dependent dielectric properties of tissue in the microwave frequency range. Due to the lack of knowledge of temperature-dependent dielectric properties of tissues over a wide microwave frequency range, the dielectric properties for liver, muscle, fat and blood in the temperature range between 30 °C and 50 °C from 500 MHz to 7 GHz are acquired in this work. For this purpose, a measurement setup for the temperature-dependent dielectric spectroscopy of tissue, tissue substitutes and fluids is presented. Furthermore, the main influences on measuring the temperature-dependent dielectric properties are analyzed. The measured data are modeled using a temperature-dependent Cole-Cole model in order to calculate the dielectric properties for arbitrary values in the investigated temperature and frequency range. In a further experiment, the noninvasive detection of temperature changes using ultra-wideband microwave technology is demonstrated in an experimental measurement setup. The results show that a temperature change of 1 °C results in differential signals that are detectable by means of ultra-wideband pseudo-noise sensing (M-sequence). The second application is dealing with contrast enhanced microwave breast cancer imaging. Due to the physiologically given low dielectric contrast between glandular and tumor tissue, the use of contrast agents, specifically magnetic nanoparticles, can improve the diagnostic reliability. The approach is based on the assumption that functionalized magnetic nanoparticles are able to selectively accumulate in tumor tissue after intravenous administration. Provided that a sufficient amount of nanoparticles has accumulated in the tumor, they can be modulated by an external polarizing magnetic field. Due to the modulation, the scattering behavior of the magnetic nanoparticles changes, which results a changing backscattering behavior. This change can be detected using low-power electromagnetic waves. In this work, the detectability and imaging of magnetic nanoparticles by means of ultra-wideband pseudo-noise sensing in the microwave frequency range is considered with respect to breast cancer detection. First, various influencing factors on the detectability of the magnetic nanoparticles are investigated, such as the mass of the magnetic nanoparticles, the magnetic field strength of the external polarizing magnetic field and the viscosity of the surrounding medium in which the nanoparticles are embedded. The results reveal a linear dependence between the measured radar signal and the mass of the magnetic nanoparticles as well as a nonlinear relationship between the response signal of the magnetic nanoparticles and the magnetic field intensity of the external magnetic field. Furthermore, the magnetic nanoparticles can be successfully detected in all investigated viscosities of the surrounding medium. Based on these preliminary investigations, a realistic measurement setup for contrast enhanced microwave breast cancer imaging is presented. The evaluation of the measurement setup is performed by phantom measurements, where the used phantom materials mimic the dielectric properties of biological tissue to obtain significance of the results with respect to a practical measurement scenario. In this context, the detectability and imaging of the magnetic nanoparticles are analyzed depending on the tumor position and penetration depth, respectively. The results show that the magnetic nanoparticles can be successfully detected. However, the magnetic poles of the electromagnet limit the space for the transmitting and receiving antennas, resulting in an inhomogeneous microwave illumination of the medium under test, which leads to a location-dependent magnetic nanoparticle response. Furthermore, the intensity of the response signal caused by the magnetic nanoparticles in the three-dimensional image depends on their position due to the path-dependent attenuation and the inhomogeneous magnetic field within the investigated medium. Regarding the last point, the external polarizing magnetic field is measured in the investigation area and an approach to compensate for the inhomogeneity of the magnetic field is presented. In addition, the disturbing influences of the polarizing magnetic field on the measurement setup are analyzed. In this context, two different modulation types (a two-state and a periodic modulation) of the external polarizing magnetic field are investigated. It is shown that both modulations can be used to image the magnetic nanoparticles. Finally, the results are discussed with respect to the spurious effects as well as a practical application scenario

Fluorescence Tomography Characterization for Sub-Surface Imaging with Protoporphyrin IX

Optical imaging of fluorescent objects embedded in a tissue simulating medium was characterized using non-contact based approaches to fluorescence remittance imaging (FRI) and sub-surface fluorescence diffuse optical tomography (FDOT). Using Protoporphyrin IX as a fluorescent agent, experiments were performed on tissue phantoms comprised of typical in-vivo tumor to normal tissue contrast ratios, ranging from 3.5:1 up to 10:1. It was found that tomographic imaging was able to recover interior inclusions with high contrast relative to the background; however, simple planar fluorescence imaging provided a superior contrast to noise ratio. Overall, FRI performed optimally when the object was located on or close to the surface and, perhaps most importantly, FDOT was able to recover specific depth information about the location of embedded regions. The results indicate that an optimal system for localizing embedded fluorescent regions should combine fluorescence reflectance imaging for high sensitivity and sub-surface tomography for depth detection, thereby allowing more accurate localization in all three directions within the tissue

Characterizing Accuracy of Total Hemoglobin Recovery Using Contrast-Detail Analysis in 3D Image-Guided Near Infrared Spectroscopy with the Boundary Element Method

The quantification of total hemoglobin concentration (HbT) obtained from multi-modality image-guided near infrared spectroscopy (IG-NIRS) was characterized using the boundary element method (BEM) for 3D image reconstruction. Multi-modality IG-NIRS systems use a priori information to guide the reconstruction process. While this has been shown to improve resolution, the effect on quantitative accuracy is unclear. Here, through systematic contrast-detail analysis, the fidelity of IG-NIRS in quantifying HbT was examined using 3D simulations. These simulations show that HbT could be recovered for medium sized (20mm in 100mm total diameter) spherical inclusions with an average error of 15%, for the physiologically relevant situation of 2:1 or higher contrast between background and inclusion. Using partial 3D volume meshes to reduce the ill-posed nature of the image reconstruction, inclusions as small as 14mm could be accurately quantified with less than 15% error, for contrasts of 1.5 or higher. This suggests that 3D IG-NIRS provides quantitatively accurate results for sizes seen early in treatment cycle of patients undergoing neoadjuvant chemotherapy when the tumors are larger than 30mm