Laser-driven solid density plasmas – generated in the interaction of a focused high-power laser pulse with the surface of a $\unicode{x3bc} \mathrm{m}$ to $\mathrm{nm}$ thin foil – can sustain electric field strengths of $\mathrm{TV}/\mathrm{m}$ . These fields enable compact and efficient particle acceleration, generating proton bunches exceeding $80\;\mathrm{MeV}$ kinetic energy on $\unicode{x3bc} \mathrm{m}$ spatial scales^[1^]. The intense proton bunches with only $\mathrm{ps}$ bunch duration at the source feature unprecedented dose rates exceeding ${10}^9\kern0.24em \mathrm{Gy}/\mathrm{s}$ , and hence make laser–plasma acceleration a unique laboratory-scale tool for the currently intensively studied field of ultra-high-dose-rate radiobiology^[2^].

While applications in radiobiology^[3^] and material characterization are rapidly developing^[4^], the complete characterization of the primary proton bunches as emitted from the laser–plasma accelerated (LPA) source still poses a major instrumental challenge. The proton emission occurs from an approximately $100\;\unicode{x3bc} \mathrm{m}$ source area (see Ref. [5] and references therein) into a large energy-dependent cone of $200{-}400\;\mathrm{mrad}$ ^[6^] half-opening angle and an exponentially decreasing energy spectrum up to a cut-off energy. Established direct spectral detection methods such as Thomson parabola^[7^–10^] or time-of-flight spectrometers^[11^–14^] only resolve the energy spectrum for a small solid angle of the full distribution. To capture the full solid angle, the spectral measurement is performed by absorbing the proton bunch in a detector volume, yielding the corresponding spatially resolved 3D dose distribution from which the energy spectrum is deconvoluted. Dose-based spectral characterization has been implemented with several detector types from stacks of radiochromic film (RCF)^[10^,15^] to scintillators^[16^–24^] and ultrasound-based methods^[25^,26^], yielding the angularly resolved spectrum with different granularity in either angle and/or energy. However, only scintillator- and ultrasound-based approaches in principle allow for real-time readouts. Yet, as implemented so far, the according detectors feature an angular and spectral resolution that is reduced in comparison to RCF.

The instrumental limits of current techniques regarding angular and spectral resolution as well as real-time operation are improved with the OCTOPOD detector, short for Optical Cone beam TOmograph for Proton Online Dosimetry. In the OCTOPOD detector, a proton bunch is absorbed in a cylindrical liquid scintillator volume of $5\;\mathrm{cm}$ diameter and $4.3\;\mathrm{cm}$ water-equivalent path length (for a scintillator density of $0.86\;\mathrm{g}/{\mathrm{cm}}^3$ ^[27^]), sufficient to stop protons up to $70\;\mathrm{MeV}$ kinetic energy. 2D projections of the 3D photon emission distribution are recorded via pinhole imaging onto 2D optical sensors for multiple angles, allowing for a tomographic image reconstruction of the 3D photon emission, as in single photon emission computed tomography (SPECT) medical imaging^[28^]. Retrieval of the angularly resolved energy spectrum then in principle requires spectral deconvolution as established for RCF measurements^[29^] after tomographic reconstruction of the 3D light emission pattern and signal calibration to dose.

In this paper, we present the detector setup and its characterization at a cyclotron proton source. Finally, the OCTOPOD is implemented at the Draco PW^[30^,31^] LPA proton source at Helmholtz-Zentrum Dresden–Rossendorf (HZDR) and provides for the first time real-time data of the complete accelerated proton bunch.

The central detection element of the OCTOPOD (Figure 1) is a volume of liquid scintillator (Saint-Gobain, BC-517H, 425 nm, ${n}_{\mathrm{ref}}=1.476$ ) of $5\;\mathrm{cm}$ diameter and length. Using a liquid scintillator prevents localized radiation damage and allows for a regular material exchange in the case of severe radiation damage. Light emission of the scintillator is in the visible range (maximum of emission at $425\;\mathrm{nm}$ ) and can hence be detected with standard silicon-based sensors.

The scintillator volume is housed in an octagonal polymethylmethacrylate (PMMA) block with a 5 cm wide base and the length of 7 cm, and the proton bunch enters through a 1 mm thick PMMA plate (Figures 1(b) and 1(c)). The PMMA block guides light emitted in the scintillator volume to the optical sensors. The nearly identical refractive indices of the scintillator material and PMMA $\left({n}_{\mathrm{ref}}=1.49\right)$ in combination with the perfect surface connection of the liquid and solid material keep the light transport from the scintillator volume to the light detection system refraction-free. This minimizes the overall detector size to a compact diameter of $23\;\mathrm{cm}$ and length of 10 cm.

The imaging system uses a pinhole camera concept to generate cone beam (CB) projections of the reconstruction volume (Figures 1(b) and 1(c)). The CB imaging is realized using pinholes that restrict the light transmission of the side surfaces of the PMMA octagon to circular $200\;\unicode{x3bc} \mathrm{m}$ diameter spots. This enables imaging with a resolution of $1\;\mathrm{mm}$ in the center of the reconstruction volume for the applied image plane distance of $1.5\;\mathrm{cm}$ behind the pinholes:

$$\begin{align}\kern-8pt R=d\cdot \left(1+\frac{1}{M}\right)=200\;\unicode{x3bc} \mathrm{m}\times \left(1+\frac{6\;\mathrm{cm}}{1.5\;\mathrm{cm}}\right)=1\;\mathrm{mm}.\end{align}$$  (1)

The sensors are attached to the octagon surface via 1.5 cm thick cuboid PMMA spacers fitting the size of the sensor sensitive area and defining the image plane distance from the pinholes (Figures 1(b) and 1(c)). The boundary connections among the PMMA octagon, pinholes, PMMA spacer and sensor are optimized for light transport with the help of silicone grease (Saint-Gobain, BC-630, ${n}_{\mathrm{ref}}=1.465$ ). With the octagonal symmetry of the detector design, eight sensors are used to obtain 24 CB projections of the reconstruction volume.

The tomographic signal reconstruction from the measured CB projections is performed via an iterative maximum likelihood expectation maximization (MLEM) algorithm. The MLEM algorithm iteratively compares measured and estimated CB projections to predict the most likely 3D scintillation light distribution in the reconstruction volume. An essential part of the MLEM algorithm is hence the forward projection, where the voxel signal values in the reconstruction volume are projected onto the sensor pixels to obtain a CB projection image that can be compared with the measured data. In the reverse, that is, the back-projection, the sensor pixel values are projected into the reconstruction volume voxels to obtain the 3D scintillation light signal.

Those forward and backward projections are defined by the fixed OCTOPOD setup and are generated via a ray tracing algorithm performed prior to the reconstruction. The respective algorithm calculates the relative signal contribution of each voxel in the reconstruction volume to the projected value on a certain pixel of the sensor and stores the result in a look-up table. To reduce the size of the look-up table, the sensor pixels are binned by a factor of 4 such that the pixel matrix of 512 × 1024 reduces to 128 × 256 and the pixel pitch increases from $48$ to $192\;\unicode{x3bc} \mathrm{m}$ . This step does not affect the $1\;\mathrm{mm}$ spatial resolution in the center of the reconstruction volume for the $200\;\unicode{x3bc} \mathrm{m}$ diameter pinhole, because the magnification of $M=0.25$ yields a signal resolution on the sensor area of $250\;\unicode{x3bc} \mathrm{m}$ . In addition, making use of the two symmetry axes of the setup’s geometry for one sensor allows for a further reduction of the pixel number that must be investigated by the ray tracing algorithm by a factor of 4.

The ray tracing algorithm samples random coordinates on the sensor pixel surfaces and the corresponding pinhole area (the geometry prohibits one pixel from seeing a signal from two different pinholes) and calculates 1000 lines defined by these two coordinates. For each voxel that is intersected by a calculated line, the length of the straight in the voxel is calculated and assigned to the voxel. If a voxel is intersected multiple times, the intersection lengths are summed up and divided by the number of intersections. Voxels that are not intersected have the value of zero. To account for the inverse-square law, each voxel value is also weighted by 1/ ${r}_1^2$ , where ${r}_1$ is the distance between the voxel and the pinhole. Equivalently, all intersected voxels for a single pixel are weighted with the factor 1/ ${r}_2^2$ , where ${r}_2$ is the distance between the pinhole and the sensor pixel. The thickness of the pinhole of $100\;\unicode{x3bc} \mathrm{m}$ leads to an angle-dependent effective pinhole area, which is considered by the ray tracing algorithm by weighting all the intersected voxels for a certain sensor pixel with the corresponding effective pinhole area and restricting the random coordinate sampling to the effective pinhole area.

Back-projection for each sensor of a homogeneous image with pixel values equal to 1 into the reconstruction volume yields the relative sampling efficiency for each voxel. The relative sampling efficiency for each voxel is determined by its position within the reconstruction volume and determined by the distance to the pinholes via the inverse-square law and the effective pinhole size, as described above. The inverse of the back-projected result forms the matrix used in the MLEM algorithm to correct for the sampling efficiency (Figure 2).

The signal readout from the reconstruction volume with single $200\;\unicode{x3bc} \mathrm{m}$ diameter pinholes strongly limits the sensitivity of the detector and yields a high threshold dose for detection. Increasing the detector sensitivity by using larger pinholes is efficient as the signal increases quadratically with the pinhole diameter, but comes at the cost of reducing the spatial resolution (Equation (1)). This problem is circumvented by using grids of multiple small pinholes (multi-pinhole grids), which increase the sensor signal by spatially overlapping CB projections then integrated by the sensor. This technique is often used in SPECT^[28^]. The reconstruction of the single-pinhole CB projection from the obtained multi-pinhole projections is performed with an iterative Richardson–Lucy deconvolution algorithm^[35^]. This iterative algorithm allows one to reconstruct an original image measured with an optical system that can be described with a line spread function (LSF), as for example, the multi-pinhole grids here.

First measurements with the OCTOPOD were performed at University Proton Therapy Dresden (UPTD; Dresden, Germany), which operates an isochronous cyclotron (Cyclone 230, Proteus Plus clinical facility, IBA) with an experimental hall equipped with a horizontal fixed-beam proton beamline^[36^] (Figure 3(a)). The goal was to investigate the MLEM reconstruction algorithm, to test the detector sensitivity and to benchmark the multi-pinhole reconstruction algorithm based on experimental data. The proton beamline was operated at output energies between $70$ and approximately $90\;\mathrm{MeV}$ , generating Bragg peak (BP) depth dose profiles in the detector volume. A range compensator ( $2\;\mathrm{cm}$ thick PMMA block) was placed in front of the detector entrance window to shift the BP position into the sensitive volume of the detector (Figure 3(b)). In addition, the measurement of a $70\;\mathrm{MeV}$ proton BP was performed with a half-blocked beam (Figure 3(c)). The lateral proton beam profile had a size of $20\;\mathrm{mm}$ , provided by the beamline without additional scatterers in place.

The OCTOPOD was set up in two configurations. First, two out of eight possible sensors were installed, each sensor equipped with a different pinhole geometry (single pinhole $200\;\unicode{x3bc} \mathrm{m}$ diameter, 3×3 pinhole grid $200\;\unicode{x3bc} \mathrm{m}$ diameter). To yield sufficient projections of the sensitive volume, the OCTOPOD detector was rotated eight times about the proton beam axis in steps of 45 ${}^{\circ }$ . Second, all eight sensors were equipped with 91-pinhole grids, to further increase the detector sensitivity.

Exemplary reconstructed BP data recorded with the single pinhole with and without the range shifter in place as well as with the half-blocked proton beam are shown in Figure 3. The relative signal intensity is proportional to the scintillator light output. The effect of the range shifter is clearly visible and the half-blocked beam setup generates a clear signal edge in the side cut-plane. Both features show that the detector concept and signal reconstruction are viable for the purpose of resolving 3D dose distributions.

To investigate the number of iterations required to reconstruct a BP with the MLEM algorithm, the depth dose profile of the reconstructed signal is monitored for each iteration step (Figure 4). The depth profile of the signal is generated by summing up the reconstructed 3D dose signal along both lateral dimensions. The reconstructed signal converges well within 20 iteration steps, with two features being visible. Firstly, there is a signal decrease in the detector’s entrance region, which is attributed to integrated background remaining from the CB back-projections into the reconstruction volume. Secondly, comparing the MLEM algorithm performance for BPs stopping towards the edge versus in the middle of the reconstruction volume, the latter show a faster convergence. The efficiency of the construction algorithm is optimal where the projection lines through the reconstruction volume are orthogonal to the beam axis (i.e., middle of the reconstruction volume) and is reduced where the projection lines traverse the reconstruction volume at a shallow angle.

To increase the sensitivity of the OCTOPOD detector, multi-pinhole grids with 3×3 pinholes and 91 pinholes as an alternative to imaging via a single pinhole were tested. Figure 5 compares all three pinhole options regarding geometry, LSF and measured/deconvoluted image. The summary shows that the entrance dose required to measure reasonable data reduces from the level of $24\;\mathrm{Gy}$ in the case of the single pinhole by a factor of 3 for the 3×3 pinhole grid to the level of approximately 1 Gy for the 91-pinhole grid. This sensitivity level fits the requirements of LPA proton sources. The increase in sensitivity comes at the cost of a smearing of the signal, as visible in the decreasing sharpness of the BPs’ distal edges (position $y=200\;\mathrm{px}$ ) in the measured images with increasing pinhole numbers. This effect is however corrected for in the unfolding, as visible in the according deconvoluted images. In the following, the performance of the multi-pinhole unfolding and reconstruction of the 3D signal will be discussed in detail.

Data for reconstructed depth dose profiles of BPs for proton energies of $70,\ 80,\ 91\;\mathrm{MeV}$ with the range shifter in place are compared for the single pinhole and the 3×3 pinhole grid (Figure 6(a)). Both pinhole configurations show a perfect agreement in proton range in the sensitive volume. Minor artifacts introduced by the multi-pinhole grid are some wave-like patterns in the plateau region of the BP and a slightly higher plateau region. In addition, the entrance signal is reduced compared to the single pinhole, an effect most likely originating from the less efficient overlapping of the single CB projections in the detector’s entrance region.

To further increase the sensitivity of the OCTOPOD, the reconstruction performance of the hexagonal grid with 91 pinholes is investigated, now with all eight sensors in operation to allow for single beam measurements without moving the detector setup. Reconstructed depth dose profiles for proton energies of $70,\ 75,\ 80,\ 85,\ 90\;\mathrm{MeV}$ with a $2\;\mathrm{cm}$ thick PMMA block in front of the detector for range compensation are shown in Figure 6(b). The experimental data are compared to simulated (FLUKA^[38^] Monte Carlo (MC) simulations) depth dose profiles for the respective proton beamline settings. Note that the MC simulations were benchmarked against measurements with stacks of RCF and required the implementation of a $2\;\mathrm{MeV}$ proton energy offset and a relative energy spread of 2.2 $\%$ for the proton beam (see Figure 7 for details). In addition, the measured depth dose profiles have been corrected for the scintillator-typical light output dependence on ionization density along a proton track, in short LET (linear energy transfer)^[39^]. The correction is based on the first-order model by Birks^[39^], using as input the fluence-weighted LET depth distribution from the reference simulation (Figure 6(b)) and the Birks constant of ${\mathrm{kB}}_{\mathrm{BC}-517\mathrm{H}}=0.0092\;\mathrm{g}/\left({\mathrm{MeV}\ \mathrm{cm}}^2\right)$ ^[40^] for the specific scintillator material.

With these beam settings and corrections applied, the reconstructed and simulated depth dose profiles show a very good overall shape agreement and in particular an excellent agreement regarding the proton range. Only minor remaining artifacts result from the reconstruction algorithm. These artifacts concern slightly broader measured than simulated BPs. Moreover, as also observed for the 3×3 pinhole grid, the reconstructed depth dose profiles exhibit a reduced entrance dose and wave-like structures in the plateau regions. The projections (not shown) furthermore feature an artifact in the middle of the reconstruction volume, caused by light reflection at the pinhole material. This issue may be circumvented by the choice of a different pinhole material.

In summary, the results show that multi-pinhole CB projection imaging only has a minor influence on the reconstruction result and is hence a viable option to increase detector sensitivity.

Operating the OCTOPOD detector at an LPA proton source with the aim to provide online feedback on the acceleration performance is complex due to the vacuum environment in which the source is located. Since the OCTOPOD detector itself is not vacuum-compatible (e.g., liquid scintillator, silicone grease, 3D-printed material), a vacuum-compatible detector housing was designed, compact enough to be placed at less than 10 cm distance from the LPA proton source (Figure 8(a)). The vacuum housing ensures an air-pressured environment for the OCTOPOD. It has a cylindrical shape with $37\;\mathrm{cm}$ diameter and a length of $15\;\mathrm{cm}$ . The main part of the housing is made of aluminum and is closed at the rear side with a stainless steel flange. On the front plate, a 5 cm diameter opening, which is covered with a $125\;\unicode{x3bc} \mathrm{m}$ thick Kapton foil, forms the entrance window for the proton bunch into the vacuum housing and then the OCTOPOD detector. During measurements, the Kapton window was protected by two layers of aluminum with $13\;\unicode{x3bc} \mathrm{m}$ thickness on either side, also ensuring light tightness of the detector.

The OCTOPOD was tested at the ultra-short pulse titanium:sapphire laser system Draco PW at HZDR, operated in a standard setting for efficient laser-driven proton acceleration in the target normal sheath acceleration (TNSA) regime^[31^]. The laser pulse, containing a maximum of $18.3\;\mathrm{J}$ of energy after compression and plasma mirror cleaning, was focused down to a $2.6\;\unicode{x3bc} \mathrm{m}$ full width at half maximum (FWHM) diameter spot to irradiate a $250\;\mathrm{nm}$ thick formvar target foil under a ${50}^{\circ }$ angle of incidence.

The OCTOPOD vacuum housing was positioned at a distance of $8.5\;\mathrm{cm}$ behind the target foil, resulting in an effective distance of $12\;\mathrm{cm}$ between the LPA proton source and the sensitive volume of the OCTOPOD (Figure 8(c)). The entrance window of the detector was approximately centered on the target normal axis. To protect the detector from electrons and bremsstrahlung emitted along the laser axis, the front surface of the housing where the laser axis intersects was shielded with a layer of lead (Figure 8(b)).

To reference the 3D dose distribution measured with the OCTOPOD detector and for calibration purposes, stacks of RCF (type EBT3 from Gafchromic, calibrated up to $55\;\mathrm{Gy}$ dose) could be positioned at a distance of $4.8\;\mathrm{cm}$ from the LPA proton source in front of the OCTOPOD detector using a motorized wheel. The RCF stacks were positioned such that they only partly blocked the entrance window of the OCTOPOD detector in order to enable the simultaneous measurement of the 3D proton dose distribution with both detector systems. Interlaced with copper absorbers, the first seven layers of the RCF stack sampled proton cut-off energies between $12$ and $45\;\mathrm{MeV}$ , corresponding to a proton range in water of $1.8{-}18.7\;\mathrm{mm}$ .

For a direct comparison of 3D dose distributions measured with the OCTOPOD and an RCF stack, the dose distributions are mapped by adapting the spatial scales and accounting for the inverse-square law regarding the pixel dose. Moreover, the OCTOPOD reconstructed light distribution is transferred to dose in water by applying a density-dependent correction for the proton penetration depth and taking into account the additional stopping power for protons penetrating the OCTOPOD’s front cover (aluminum protection, Kapton window, PMMA plate). All corrections applied, the OCTOPOD features a lower proton detection energy of approximately 11 MeV. In the final step, both the RCF and OCTOPOD 3D dose distribution are resampled to a voxel size of $0.5\;\mathrm{mm}$ , according to the reconstruction matrix of the OCTOPOD detector.

The resulting data are summarized in Figure 9, with Figure 9(a) showing the side, top and frontal (left to right) cut-plane of reconstructed 3D water dose distributions for the OCTOPOD (top) and RCF stack (bottom). As a note, the background signal in the top cut-plane (red rectangle) is a feature of the LPA process. It results from bremsstrahlung and electrons emitted in the laser forward direction, which are then detected in the ${270}^{\circ }$ projection sensor located in the laser forward direction, despite additional lead shielding at this position (Figures 8(b) and 8(c)). Otherwise, both methods yield a remarkable agreement in terms of penetration depth in water (side cut-plane) and proton beam profile (frontal cut-plane). Remaining differences in the proton beam profiles are caused by a truncation of the dose scale at $55\;\mathrm{Gy}$ (upper dose limit of RCF calibration), which artificially homogenizes the dose distribution in the high dose region. For deeper water depths $\left(3.5,\ 6,\ 9,\ 12\;\mathrm{mm}\right)$ and hence lower doses, the OCTOPOD reproduces the proton beam profile from the RCF stack reference measurement with high accuracy (Figure 9(b)). As the dose level decreases below $600\;\mathrm{mGy}$ (turquoise on the colormap in Figure 9(b) for water depths $>12\;\mathrm{mm}$ ), the OCTOPOD measurements start to visibly deviate from the RCF stack reference. This indicates that the OCTOPOD is sensitive to doses down to more than or equal to $600\;\mathrm{mGy}$ for the reconstruction of lateral beam profiles.

For the calibration of the OCTOPOD, the proton beam profile at $3.5\;\mathrm{mm}$ water depth is used, yielding a calibration factor of $2.1\;\mathrm{Gy}/1$ from the OCTOPOD voxel signal to the water dose.

The OCTOPOD’s sensitivity to changes of the incoming proton distribution is tested by scanning the laser energy on target from $10.4$ to $18.3\;\mathrm{J}$ in four steps. Figure 10 shows the according frontal (Figure 10(a)) and top (Figure 10(b)) cut-planes at $2.1\;\mathrm{mm}$ water depth derived from the reconstructed 3D water dose. The increasing penetration depth of protons into the detector as their kinetic energy increases with laser energy is clearly resolved in the depth dose distributions in Figure 10(c). From these measurements, the detection threshold is estimated to below $100\;\mathrm{mGy}$ because the depth dose curves feature a signal fall-off around $100\;\mathrm{mGy}$ that is resolved well. Note, however, that the detection threshold also depends on the overall irradiated scintillator volume versus the volume just exposed to background radiation, as this ratio affects the reconstruction performance.

The OCTOPOD’s capability to record the complete proton distribution is vital here in detecting that the proton beam profile is not only increasing in diameter with increasing laser energy on target, but also shifts towards the laser forward direction (x $<0\;\mathrm{mm}$ ).

As a second measurement, the target position with respect to the laser pulse focus was changed for a constant laser pulse energy of $18.3\;\mathrm{J}$ on target ( $15.2\;\mathrm{J}$ for position $-25\;\unicode{x3bc} \mathrm{m}$ due to saturation effects), altering the laser pulse focal spot size and hence laser intensity on target. This type of measurement constitutes a standard method to optimize the LPA proton performance, generally using the achieved proton cut-off energy as a figure of merit for optimal interaction conditions. The proton cut-off energy can be sensitive to changes in the focal spot position of less than $20\;\unicode{x3bc} \mathrm{m}$ , which is close to the achievable target alignment accuracy with respect to the focal spot position.

Figure 11 summarizes the OCTOPOD results for the frontal and top cut-planes from reconstructed 3D water doses. The TCC (target chamber center) here denotes that the target is positioned in the optically measured position of the laser focus and relative positions marked as positive/negative refer to target positions closer to and further away from the laser focusing optics, respectively. The top cut-planes show a clear decrease in penetration depth of the proton bunch into the detector volume with increasing distance from the TCC, in agreement with the expected decrease in proton cut-off energy with decreasing laser pulse intensity on target. As a side effect, the OCTOPOD also resolves the strong correlation between the bremsstrahlung/electron background generated in the laser forward direction (red rectangle in Figure 11) and the target position, that is, the laser pulse intensity on target.

Whereas these features may also be detected with alternative methods, for example, Thomson parabola/bremsstrahlung/electron spectrometers, the OCTOPOD provides the full proton beam profiles, here at a water depth of $2.1\;\mathrm{mm}$ reachable by protons with kinetic energies exceeding $13.5\;\mathrm{MeV}$ . Around the TCC ( $\pm 25\;\unicode{x3bc} \mathrm{m}$ ), the proton beam profile is shifted towards the laser forward direction ( $x<0\;\mathrm{mm}$ ), as observed for the laser energy scan, and shifts back into the direction of the target normal direction further away from TCC. For positions where $\mathrm{TCC}>+50\;\unicode{x3bc} \mathrm{m}$ , the OCTOPOD resolves a rotation of the proton beam profile and a double peak structure for $\mathrm{TCC}=+50\;\unicode{x3bc} \mathrm{m}$ . This behavior can be indicative of hybrid acceleration schemes^[41^], but may also be related to spatio-temporal coupling effects in the laser focus imprinting into the proton beam profile^[6^].

To conclude, the OCTOPOD detector is a solution to the long-standing challenge in detecting the full angular-spectral distribution of single LPA proton bunches in real-time. Careful choice of the projection approach (pinhole imaging) and light guiding design makes the detector compact enough to be placed close to the laser–target interaction region. Performing systematic characterization measurements at a cyclotron proton source, we could show the OCTOPOD’s capabilities in reliably reconstructing 3D dose distributions with mm-scale spatial resolution. Operated at the LPA proton source, the OCTOPOD was shown to be sensitive to minimal changes in the laser–target interaction conditions, for example, changes in the focal spot position of $25\;\unicode{x3bc} \mathrm{m}$ .

A further miniaturization of the setup and hence wider dissemination can be achieved by replacing the liquid scintillator with a plastic scintillator block and when using vacuum-compatible components throughout the detector design (e.g., silicone grease for the immersion of interfaces). In that case, the requirement for the bulky vacuum-compatible detector housing would be lifted. The housing has proven to allow for stable detector operation in the harsh plasma environment (optical and particle emission from the plasma emission, electromagnetic pulses) at a PW-class high-power laser system. However, the RadEye sensors can also be operated directly in vacuum when shielded from background radiation.

For any practical purpose, the OCTOPOD needs to be competitive with the established and hence trusted LPA proton detector systems Thomson parabola and RCF. In comparison to RCF, the OCTOPOD features a similar lower detection threshold of $100\;\mathrm{mGy}$ , providing comparable proton cut-off energy detectability. Moreover, the OCTOPOD can be operated with various pinhole configurations, also in combination for different projection directions. This feature gives a handle on the detector’s dynamic range and can prevent signal saturation for the low-energy portion of the spectrum, a general issue with RCF. The spectral resolution of the OCTOPOD is influenced by the detector’s spatial resolution, which is a factor of 4 higher for RCF ( $280\;\unicode{x3bc} \mathrm{m}$ thickness) than for the OCTOPOD ( $1\;\mathrm{mm}$ theoretical spatial resolution). Note that the given spatial resolution for the OCTOPOD is theoretical, not taking into account the influence of, for example, scintillation light scattering inside the scintillator volume. Yet, for most practical purposes of detecting protons with kinetic energies in the multi- $10\;\mathrm{MeV}$ range, RCF will be interlaced with absorbers in a stack setup. This limits the effective energy resolution to below the OCTOPOD’s capabilities and additionally introduces the uncertainty of signal generation in the RCF from proton-triggered nuclear reactions in the absorber material.

For TPs, the spectral resolution and cut-off energy detectability, particularly when operated with micro-channel plate detectors, are clearly higher than for the OCTOPOD detector, but the reduced angular acceptance introduces the uncertainty of whether the highest energy protons of a bunch are detected at all.

In summary, the unique capability of the OCTOPOD detector is the single pulse real-time detection of the full angular-spectral proton distribution with a sensitivity, dynamic range and spatial resolution adapted to the needs of current proton LPA experiments. A number of application scenarios will profit from this detector type. Firstly, the capability of a full characterization of the proton bunch will provide considerably better and most importantly statistical input data for LPA proton beamlines^[42^] and hence further promote the development of application experiments and the according instrumentation. Moreover, the OCTOPOD can enable an automated feedback loop between laser parameters governing the complex plasma dynamics of the acceleration process and a targeted application-specific 3D angular-spectral distribution. For both LPA electrons and protons, such automated feedback loops have successfully been implemented recently^[43^,44^]. The OCTOPOD will also open up new possibilities in investigating the spatio-temporal coupling effect in the laser pulse^[45^] affecting acceleration performance and angular proton emission patterns. Last but not least, a dedicated investigation of the spatial resolution limits as also affected by pinhole arrays might qualify the OCTOPOD as a viable detector for proton radiography studies^[46^].