3D Treatment Research Articles

Gating Verification via Correlation of Dynamic DRRs and Respiration-Correlated MV Fluoroscopic Images

Purpose/Objective: To demonstrate the practicality of low-dose megavoltage (MV) fluoroscopic imaging for dynamic treatment plan verification and respiratory gate adjustment.Materials/Methods: A treatment linac, fitted with an MV-optimized flat panel detector, was modified in order to produce low-dose MV fluoroscopic images at acquisition doses ranging form 0.02 to 0.06 cGy per frame at a frame rate of 2 per second. This fluoroscopic imaging mode was realized using a fast beam formation technique that ensures beam stability within 5ms of beam activation. A static torso phantom was imaged to determine whether clinically useful lung visualization could be achieved at these dose levels. Dynamic imaging was evaluated using an anthropomorphic breathing torso phantom fitted with a respiration-sensing belt. The MV image-readout and respiratory trace signals were simultaneously recorded. Verification and adjustment of the trigger window used for gated delivery was performed within a computer application that matched digitally reconstructed radiographs (DRRs) derived from a 4D treatment planning CT study to the MV fluoroscopy image series.Results: Static torso phantom images allowed clear delineation of diaphragm and lung from surrounding tissue. Using the dynamic phantom, we demonstrated that the adjustment of the gating window can be used to restore the temporal and spatial consistency between the planning CT-derived treatment plan and the treatment delivery.Conclusions: MV fluoroscopy is useful for the verification of dynamic treatment plans and specifically for the modification of treatment gate windows to account for differences in the correlations between anatomy motion and respiratory traces that can arise between the time of planning CT acquisition and treatment. Total patient dose for a fluoroscopy of one minute duration (during which approximately 24 breathing cycles can be sampled) is similar to the dose associated with a single portal image. Purpose/Objective: To demonstrate the practicality of low-dose megavoltage (MV) fluoroscopic imaging for dynamic treatment plan verification and respiratory gate adjustment. Materials/Methods: A treatment linac, fitted with an MV-optimized flat panel detector, was modified in order to produce low-dose MV fluoroscopic images at acquisition doses ranging form 0.02 to 0.06 cGy per frame at a frame rate of 2 per second. This fluoroscopic imaging mode was realized using a fast beam formation technique that ensures beam stability within 5ms of beam activation. A static torso phantom was imaged to determine whether clinically useful lung visualization could be achieved at these dose levels. Dynamic imaging was evaluated using an anthropomorphic breathing torso phantom fitted with a respiration-sensing belt. The MV image-readout and respiratory trace signals were simultaneously recorded. Verification and adjustment of the trigger window used for gated delivery was performed within a computer application that matched digitally reconstructed radiographs (DRRs) derived from a 4D treatment planning CT study to the MV fluoroscopy image series. Results: Static torso phantom images allowed clear delineation of diaphragm and lung from surrounding tissue. Using the dynamic phantom, we demonstrated that the adjustment of the gating window can be used to restore the temporal and spatial consistency between the planning CT-derived treatment plan and the treatment delivery. Conclusions: MV fluoroscopy is useful for the verification of dynamic treatment plans and specifically for the modification of treatment gate windows to account for differences in the correlations between anatomy motion and respiratory traces that can arise between the time of planning CT acquisition and treatment. Total patient dose for a fluoroscopy of one minute duration (during which approximately 24 breathing cycles can be sampled) is similar to the dose associated with a single portal image.

TH-B-T-6E-01: Monte Carlo Applications in Conformal, IMRT and 4D Clinical Treatment Planning: Pitfalls and Triumphs

Due to its ability to accurately model dose distributions for arbitrarily complex treatment delivery scenarios and patient geometries, it is highly probable that over the next few years the use of Monte Carlo in routine clinical planning will become substantially more widespread. Building on the discussion of the role of Monte Carlo in treatment head simulation (from the first course), this second Monte Carlo course will focus on patient planning applications. The goal of the course is to familiarize clinical medical physicists with the use of Monte Carlo in treatment planning, including advanced treatment techniques such as IMRT and motion compensated 4D treatment, and to discuss how Monte Carlo based planning differs from conventional algorithm based planning. We will demonstrate the utility of Monte Carlo with respect to improved dose calculation accuracy (versus conventional algorithms) in heterogeneous patient tissues, and illustrate how a properly benchmarked Monte Carlo system can play a unique role in the modeling of complex delivery procedures, such as IMRT. In particular, the ability to effectively model the dosimetric consequences of the detailed the multi‐leaf collimator(MLC) geometry with Monte Carlo will be demonstrated. Finally, we will show how Monte Carlo can be applied to compensate for organ motion in 4D treatment planning without an increase in computation time. In addition to illustrating the role of Monte Carlo in complex treatment planning, an important focus of this course will be to provide guidance to clinical physicists on practical issues associated with the implementation, verification and clinical use of Monte Carlo systems. Educational Objectives: 1. To familiarize clinical physicists with Monte Carlo applications for routine clinical treatment planning. 2. To understand the dosimetric influence of Monte Carlo in different anatomical sites and to become familiar with the potential clinical outcome benefits of Monte Carlo. 3. To understand some of the issues that clinical physicists face in the implementation and experimental verification of Monte Carlotreatment planning systems. 4. To understand the use, benefits and limitations of Monte Carlo for IMRT optimization and QA. 5. To become familiar with the role of Monte Carlo in motion compensated (4D) treatment planning.

SU-FF-J-09: Comparison of Auto-Contouring with Manual Contouring: A First Step Towards Automated 4D Treatment Planning

Purpose: Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning and delivery of radiotherapy. One key component of 4D radiotherapy planning, is the ability to auto contour the individual respiratory phase CT datasets (up to ten in total) comprising a 4D computed tomography (CT) scan. A tool that can be used to automatically generate such contours (based on contours manually drawn on a single CT phase) is deformable image registration. The purpose of the current study was to compare automatically generated contours with manually drawn contours. Method and Materials: Two out of ten patient 4D CT data sets have completed this study. The 4D CT scans consisted of a series of ten 3D CT image sets acquired at different respiratory phases. Large deformable diffeomorphic image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding with subsequent respiration phases. The calculated displacement vector fields were used to deform contours defined on the peak-inhale CT automatically to the other respiratory phase CT image sets. Auto-contouring was performed on each of the ten 3D image sets via automated scripts. Treatment planning system, Pinnacle version 7.7 was interfaced with automated scripts to view the resulting images and to obtain the volumetric and displacement information. Results: Deformation with respiration was observed for the lung tumor and normal tissues. This deformation was verified by examining the mapping of high contrast objects, such as the lungs and cord, between image sets. Conclusion: An automated system is established to auto - contour the ROI's starting form the ROI's in the inhale phase to the other phases of the respiratory motion using Pinnacle Treatment planning system. Auto-contoured organs and the GTV in the Thorax agree with the manually drawn ROI's.

SU‐EE‐A3‐05: Robustness of Two 4D Radiotherapy Approaches with Respect to Temporal Irregularity in Organ Motion

Purpose: Respiratory motion of cancer patients during radiotherapy often lacks spatial and temporal regularity. Delays between motion monitoring and radiation adjustment in motion tracking treatment can cause large deviations between the delivered and the intended dosimetry. We demonstrate the advantage of a motion‐pattern‐based 4D approach we developed previously with regard to organ motion temporal variation for lung cancer radiotherapy. Method and Materials: A 4D CT image set of a lung cancer patient and a moving phantom were studied using 4D treatment planning in the in‐house TPS PLUNC, with and without the 4D optimization that is based on large‐deformation diffeomorphic registration and index‐dose gradient optimization algorithms. 4D dosimetry refers to the cumulative dose received by anatomical structures in patients with deformable organ motion. The 4D optimization generates static IMRT plans that can be delivered via compensators. The 4D IMRT treatment is compared with non‐IMRT motion tracking treatment, with and without tracking delay, for robustness against temporal motion pattern irregularity. The same beam setup, field margin, and dosimetric goal were used by all the plans in the comparison. Results: The perfect motion tracking technique gave the best CTV 4D DVH. The 4D IMRT performed better than the motion tracking treatment with systematic delays of 0.5 second or larger (motion cycle is 4 seconds). The 4D IMRT yielded better sparing of lung tissue and heart than all the non‐IMRT motion tracking treatments. Results on EUD are also presented. Conclusion: The motion‐pattern‐based 4D IMRT has the advantages of treatment delivery simplicity and robustness with respect to organ motion temporal irregularity. Compared to non‐IMRT motion tracking, it gives better 4D dosimetry for the moving tumor, lung, and heart in treatments of small‐size and large‐motion lung tumors having irregular temporal motion pattern. Conflict of interest: Research is partially supported by Siemens.

SU-FF-T-380: Dose Mass Histogram and Its Application for 4D Treatment Planning

Purpose: In evaluating dose distributions of lung treated during respiration, dose volume histogram (DVH) may not be an appropriate term because of variable lung volume with respiration. The purposes of this work are to investigated the use of dose mass histogram (DMH) for lung and assess the differences between DVH and DMH for conventional and 4D treatment planning. Method and Materials: DMH was calculated based on a similar concept of DVH excepted mass of each voxel, which was calculated from CT number to density conversion, was used in tallying dose distributions. For conventional treatment planning, DVHs and DMHs of normal lung (excluding GTV) were calculated and compared for 51 lung cancer cases and 52 esophagus cancer cases. For 4D treatment planning, ten lung cancer cases were analyzed, each of which had 4DCT scans of full lung and optimal CT image quality. Total normal lung was delineated on CT images of all respiratory phases using auto-thresholding with a single CT number. Dose distributions were computed on all respiratory phases with DVH and DMH being calculated for the lung. Results: For conventional plans, difference between DMH and DVH existed for cases with highly inhomogenuous lung tissues. For a majority of cases, such differences were small and may not be clinically significant. For 4D treatment planning, lung volume changed on average by 16.3% between inspiration and expiration. As expected, variation of lung mass was much smaller, only by about 6.6% as assessed from the 4DCT. The change of lung DMH with breathing was often different from that of lung DVH, indicating that deformation of lung mass followed different patterns than that of the lung volume during breathing. Conclusion: DMH may be more relevant than DVH considering varying alveolar-cell density in lung and conservation of lung mass in 4D treatment planning.

Four-dimensional image-based treatment planning: Target volume segmentation and dose calculation in the presence of respiratory motion

To describe approaches to four-dimensional (4D) treatment planning, including acquisition of 4D-CT scans, target delineation of spatio-temporal image data sets, 4D dose calculations, and their analysis. The study included patients with thoracic and hepatocellular tumors. Specialized tools were developed to facilitate visualization, segmentation, and analysis of 4D-CT data: maximum intensity volume to define the extent of lung tumor motion, a 4D browser to examine and dynamically assess the 4D data sets, dose calculations, including respiratory motion, and deformable registration to combine the dose distributions at different points. Four-dimensional CT was used to visualize and quantitatively assess respiratory target motion. The gross target volume contours derived from light breathing scans showed significant differences compared with those extracted from 4D-CT. Evaluation of deformable registration using difference images of original and deformed anatomic maps suggested the algorithm is functionally useful. Thus, calculation of effective dose distributions, including respiratory motion, was implemented. Tools and methods to use 4D-CT data for treatment planning in the presence of respiratory motion have been developed and applied to several case studies. The process of 4D-CT-based treatment planning has been implemented, and technical barriers for its routine use have been identified.

Respiratory gating and 4‐D tomotherapy

Helical tomotherapy is a new intensity‐modulated radiotherapy (IMRT) delivery process developed at the University of Wisconsin and TomoTherapy Inc. Tomotherapy may be of advantage in lung cancer treatment due to its rotational delivery mode. As with conventional IMRT delivery, however, intrafraction respiratory motion during a tomotherapy treatment causes unnecessary radiation to the healthy tissue. Possible solutions to these problems associated with intrafraction motion have been studied in this thesis. A spirometer is useful for monitoring breathing because of its direct correlation with lung volume changes. However, its inherent drift prevents its application in long‐term breathing monitoring. With calibration and stabilization algorithms, a spirometer is able to provide accurate, long‐term lung volume change measurements. Such a spirometer system is most suited for deep inspiration breath‐hold (DIBH) treatments. An improved laser‐spirometer combined system has also been developed for target tracking in 4‐D treatment. Spirometer signals are used to calibrate the displacement measurements into lung volume changes, thereby eliminating scaling errors from daily setup variations. The laser displacement signals may also be used to correct spirometer drifts during operation. A new 4‐D treatment technique has been developed to account for intrafraction motion in treatment planning. The patient's breathing and the beam delivery are synchronized, and the target motion/deformation is incorporated into treatment plan optimization. Results show that this new 4D treatment technique significantly reduces motion effects and provides improved patient tolerance.

27 4D imaging, planning, and treatment of moving targets at MGH

27 4D imaging, planning, and treatment of moving targets at MGH

308 4D imaging and treatment planning

308 4D imaging and treatment planning

A four-dimensional controller for DMLC-based tumor tracking

The development of four-dimensional (4D) radiotherapy for dynamic multileaf collimator (DMLC)-based tumor tracking requires the development of new hardware and software for controlling the radiation delivery, termed a four-dimensional controller (4DC). The four-dimensional controller integrates the information from the treatment plan and the respiration signal and computes multileaf collimator positions which are then sent to the DMLC to facilitate tumor tracking. The purpose of this study was to (a) develop a prototype 4DC and (b) determine the efficacy of the 4DC for 4-dimensional radiotherapy. In this work, three key components of 4DC were studied: (1) the effect of respiratory coaching on the reproducibility of respiratory patterns, (2) the mechanical ability of the DMLC to perform tumor tracking and (3) the ability to predict respiratory patterns to account for the delay between respiratory signal acquisition and DMLC. (1) Respiratory coaching: Respiration reproducibility is an important component, not just of 4D radiation delivery, but also 4DCT acquisition and 4D treatment planning. To investigate if coaching methods can improve respiration reproducibility, 300 four-minute respiratory traces were obtained from 23 lung cancer patients enrolled in an IRB-approved study under the conditions of free breathing, audio coaching, and audio-visual coaching. Respiration reproducibility was quantified by cycle-to-cycle position, displacement and breathing period variations. (2) DMLC capability: To investigate the mechanical capabilities of the DMLC to perform tumor tracking for respiratory motion, the maximum leaf velocity, acceleration and deceleration were measured for three different MLCs at different time periods and under various gravitational and friction environments. The measured values were input into equations of motion to determine the DMLC response time for positional changes under various initial and final conditions. The DMLC response was compared with fluoroscopy-measured diaphragm motion from 60 data-sets from five lung cancer patients. (3) Respiration prediction: To account for the system response time between respiration signal acquisition and execution of the MLC motion, a linear adaptive prediction filter was employed. This filter was implemented and the prediction accuracy tested on sixty fluoroscopy datasets from lung cancer patients in which the diaphragm motion was tracked for system response times of 0.2, 0.4 and 0.6 seconds. (1) Respiratory coaching: Respiratory reproducibility is significantly improved with audio-visual coaching. The variation in breathing rate and position and displacement was less for audio-visual coaching than free breathing and audio coaching. (2) DMLC capability: Significant differences were observed between inner (0.5 cm thick) and outer (1.0 cm thick) leaves. The DMLC maximum leaf velocities are 3.9 ± 0.5 cm/s and 3.3 ± 0.1 cm/s respectively and acceleration 37 ± 8 cm/s2 and 37 ± 10 cm/s2. Based on these measurements, the mechanical MLC delay time is around 0.1 seconds leading to an overall system response time of approximately 0.4 seconds. Applying equations of motion derived from these measurements to fluoroscopy-measured internal motion indicates that DMLC tracking will be over 95% efficient, however a beam-hold is required to account for irregular respiration such as coughing. (3) Respiration prediction: The ability to predict respiratory motion as the system response time increases. However, for a response time of 0.4 seconds (the estimated value for 4D radiotherapy utilizing current technology) the position prediction error is less than 2 mm (1.s.d.). A prototype version of a four-dimensional controller for DMLC-based tumor tracking has been developed. Based on patient respiratory and fluoroscopy analysis, and DMLC mechanical measurements and analysis, the existing linear accelerator technology is capable of 4D radiation delivery.

Validation of the path integration of 4D dose distributions with 4D phantom measurements

4D treatment planning generates a series of 3D dose distributions to represent the motion properties of the patient and/or radiation delivery system. The purpose of this study is to validate with 4D phantom measurements the use of the 3D optical flow method algorithm for the numerical path integration of 4D dose distribution data into a single 3D dose distribution. The Radiological Physics Center (RPC) thoracic phantom was placed on a programmable motion table to simulate respiratory motion. 4D CT imaging was performed on a multi-slice CT scanner (Philips Medical Systems, Anhover, MA). The CT data was binned into eight phases. The CT images were sent to a Pinnacle workstation (version 6.2b, Phillips Medical Systems, Anhover, MA) where a treatment plan was designed on the end expiration image set. The treatment plan was transposed onto the other respiratory phases and a 4D dose data set generated. The plan was delivered using a Varian 2100 linear accelerator (Varian Medical System, Palo Alto, CA). The dose delivered to the RPC thoracic phantom was recorded using radiographic film and thermoluminescent dosimeters for calibration. The 3D optical flow method (3D OFM) algorithm is a deformable image registration algorithm we have implemented. 3D OFM was used to calculate the displacement fields between the respiratory phases. The displacement fields were used to map the dose distributions from the multiple respiratory phases onto the end expiration phase. The resulting dose distributions were summed with equal weighting, performing numerical path integration. The calculated and measured dose distributions were compared with the static plan. The attached figure illustrates the dose distributions. A coronal section through the static treatment plan is shown in figure A.u1/2pick;3197f1;0;11 The 3D OFM algorithm was applied and numerical path integration performed on the 4D dose distribution data resulting in a single 3D dose distribution. The corresponding coronal section is shown in figure B. A coronal section through the measured dose distribution is shown in figure C. The delivered dose distribution had a peak width at 90% maximum of 38.5 mm. The corresponding value for the path integrated 4D plan and the end expiration static plan were 42.6 mm and 47.0 mm. The 50% isodose line was displaced 0.5 mm when compared with the path integrated 4D plan and 8.6 mm when compared with the end expiration static plan. The 3D OFM algorithm provides the displacement field necessary for numerical path integration to map a 4D dose distribution data set into a single 3D dose distribution accurately. The resulting dose distribution was found to more closely represent the delivered dose versus the static plan for a moving phantom.

Validation of the path integration of 4D dose distributions with 4D phantom measurements

4D treatment planning generates a series of 3D dose distributions to represent the motion properties of the patient and/or radiation delivery system. The purpose of this study is to validate with 4D phantom measurements the use of the 3D optical flow method algorithm for the numerical path integration of 4D dose distribution data into a single 3D dose distribution.

Monte Carlo as a four-dimensional radiotherapy treatment-planning tool to account for respiratory motion**Paper presented at World Congress on Medical Physics and Biomedical Engineering (Sydney)—WC2003.

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning and delivery of radiotherapy. Temporal anatomic changes can occur for many reasons, though the focus of the current investigation was respiration motion for lung tumours. The aims of the current research were first to develop a 4D Monte Carlo methodology and second to apply this technique to an existing 4D treatment plan. A 4D CT scan consisting of a series of 3D CT image sets acquired at different respiratory phases was used. Deformable image registration was performed to map each CT set from the end-inhale respiration phase to the CT image sets corresponding with subsequent respiration phases. This deformable registration allowed the contours drawn on the end-inhale CT to be automatically drawn on the other respiratory phase CT image sets. A treatment plan was created on the end-inhale CT image set and then automatically created on each of the 3D CT image sets corresponding with subsequent respiration phases, based on the beam arrangement and dose prescription in the end-inhale plan. Dose calculation using Monte Carlo was simultaneously performed on each of the N (=8) 3D image sets with 1/N fewer particles per calculation than for a 3D plan. The dose distribution from each respiratory phase CT image set was mapped back to the end-inhale CT image set for analysis. This use of deformable image registration to merge all the statistically noisy dose distributions back onto one CT image set effectively yielded a 4D Monte Carlo calculation with a statistical uncertainty equivalent to a 3D calculation, with a similar calculation time for the 3D and 4D methods. Monte Carlo as a dose calculation tool for 4D radiotherapy planning has two advantages: (1) higher accuracy for calculation in electronic disequilibrium conditions, such as those encountered during lung radiotherapy, and (2) if deformable image registration is used, the calculation time for Monte Carlo is independent of the number of 3D CT image sets constituting a 4D CT, unlike other algorithms for which the calculation time scales linearly with the number of 3D CT image sets constituting a 4D CT.

Acquiring 4D thoracic CT scans using a multislice helical method

Respiratory motion degrades anatomic position reproducibility during imaging, necessitates larger margins during radiotherapy planning and causes errors during radiation delivery. Computed tomography (CT) scans acquired synchronously with the respiratory signal can be used to reconstruct 4D CT scans, which can be employed for 4D treatment planning to explicitly account for respiratory motion. The aim of this research was to develop, test and clinically implement a method to acquire 4D thoracic CT scans using a multislice helical method. A commercial position-monitoring system used for respiratory-gated radiotherapy was interfaced with a third generation multislice scanner. 4D cardiac reconstruction methods were modified to allow 4D thoracic CT acquisition. The technique was tested on a phantom under different conditions: stationary, periodic motion and non-periodic motion. 4D CT was also implemented for a lung cancer patient with audio-visual breathing coaching. For all cases, 4D CT images were successfully acquired from eight discrete breathing phases, however, some limitations of the system in terms of respiration reproducibility and breathing period relative to scanner settings were evident. Lung mass for the 4D CT patient scan was reproducible to within 2.1% over the eight phases, though the lung volume changed by 20% between end inspiration and end expiration (870 cm3). 4D CT can be used for 4D radiotherapy, respiration-gated radiotherapy, ‘slow’ CT acquisition and tumour motion studies.

4-dimensional computed tomography imaging and treatment planning

In the era of conformal therapy and intensity-modulated therapy, there is an increased desire to raise tumor dose to facilitate improved survival and decrease normal tissue dose to reduce treatment-related complications. Setup accuracy and internal motion limit our ability to reduce margins. Internal motion has both interfraction and intrafraction components, although only the intrafraction component will be addressed here. Intrafraction motion is significant for lung, liver, and pancreatic radiotherapy and to a lesser extent breast and prostate radiotherapy. A method to explicitly account for intrafraction motion is to temporally adjust the treatment beam based on the tumor position with time such that the motion of the radiation beam is synchronized with the tumor motion. This addition of time into the 3-dimensional treatment process is termed 4-dimensional (4D) radiotherapy. Four-dimensional radiotherapy may allow safe clinical target volume-planning target volume margin reduction to achieve the goals of raised tumor dose and decreased normal tissue dose. This article discusses methodology for 4D CT imaging and 4D treatment planning, with some comments on 4D radiation delivery.

Four-dimensional treatment planning and fluoroscopic real-time tumor tracking radiotherapy for moving tumor

Purpose: To achieve precise three-dimensional (3D) conformal radiotherapy for mobile tumors, a new radiotherapy system and its treatment planning system were developed and used for clinical practice. Methods and Materials: We developed a linear accelerator synchronized with a fluoroscopic real-time tumor tracking system by which 3D coordinates of a 2.0-mm gold marker in the tumor can be determined every 0.03 second. The 3D relationships between the marker and the tumor at different respiratory phases are evaluated using CT image at each respiratory phase, whereby the optimum phase can be selected to synchronize with irradiation (4D treatment planning). The linac is triggered to irradiate the tumor only when the marker is located within the region of the planned coordinates relative to the isocenter. Results: The coordinates of the marker were detected with an accuracy of ± 1 mm during radiotherapy in the phantom experiment. The time delay between recognition of the marker position and the start or stop of megavoltage X-ray irradiation was 0.03 second. Fourteen patients with various tumors were treated by conformal radiotherapy with a “tight” planning target volume (PTV) margin. They were surviving without relapse or complications with a median follow-up of 6 months. Conclusion: Fluoroscopic real-time tumor tracking radiotherapy following 4D treatment planning was developed and shown to be feasible to improve the accuracy of the radiotherapy for mobile tumors.

Ab initio calculation and spectroscopic analysis of the intramolecular vibrational redistribution in 1,1,1,2-tetrafluoroiodoethane CF3CHFI

We report a new mechanism for intramolecular vibrational redistribution (IVR) in CF3CHFI which couples the CH chromophore vibrations through a strong Fermi resonance to the formal CF stretching normal mode (a heavy atom frame mode) involving the trans F-atom across the CC bond. The analysis is made possible by comparing spectroscopic results with extensive ab initio calculations of the vibrational fundamental and overtone spectra in the range extending to 12 000 cm−1. Potential energy and electric dipole moment hypersurfaces are calculated ab initio by second order Møller–Plesset perturbation theory (MP2) on a grid involving the CH stretching, two CH bending modes and one high frequency CF stretching normal mode. The potentials are scaled to obtain agreement between the experimental spectrum and the theoretical spectrum calculated by a discrete variable representation technique on this grid. Both spectra are then analyzed in terms of three-dimensional (3D) and four-dimensional (4D) effective vibrational Hamiltonians including Fermi- and Darling–Dennison-type resonances between the CH stretching mode and the CH bending modes and the CF stretching mode. The interaction between the CH modes and the CF mode is clearly visible in the experimental and calculated (4D) spectra. The effective Fermi resonance coupling constants [ksff′≃(40±10) cm−1 and ksaf′≃(55±10) cm−1] coupling the CH and CF mode subspaces are of about the same magnitude as the intra-CH chromophore Fermi resonances (ksaa′≃56 cm−1 and ksbb′≃42 cm−1, coupling CH stretching mode “s” with the two CH bending modes “a” and “b”). The chiral, pseudo-Cs symmetry breaking coupling (ksab′≃11 cm−1) is complemented by an equally strong coupling through the CF mode (ksfb′≃15 cm−1). It is demonstrated that low order perturbation theoretical analysis using potential constants from a polynomial expansion to represent effective coupling constants gives inadequate results with discrepancies ranging about from factors of 2–5. Time dependent population and wave packet analysis shows essentially complete IVR among the CH chromophore modes within about 100 fs, the 3D and 4D evolutions being similar up to about that time. At longer times of about 250 fs, there is substantial excitation of the CF stretching mode (with initial pure CH stretching excitation). The 4D treatment is then essential for a correct description of the dynamics.