Abstract:Objective. Clinical dosimetry in the presence of a 1.5 T magnetic field is challenging, let alone in case small fields are involved. The scope of this study is to determine a set of relevant correction factors for a variety of MR-compatible detectors with emphasis on small fields. Two dosimetry formalisms adopted from the literature are considered. Approach. Six small-cavity ionization chambers (from three manufacturers), four active solid-state detectors and a thermoluminescence dosimeter microcube were modeled in the EGSnrc Monte Carlo code. Phase space files for field sizes down to 1 × 1 cm2 of the Unity 1.5 T/7 MV MR-linac (Elekta, UK) were used as source models. Simulations were performed to calculate the kQB,QfB,f (also known as kB,Q), kQmsrB,fmsr and kQclin,QmsrB,fclin,fmsr relevant to two different dosimetry formalisms. Two detector orientations with respect to the magnetic field were considered. Moreover, the effect of the ionization chamber’s stem length (a construction parameter) on the correction factor was investigated. Simulations were also carried out to determine whether correction factors obtained in water can be applied in dosimetry procedures involving water-equivalent solid phantoms. Main results. Under the kQB,QfB,f-based formalism, the required corrections to ionization chamber responses did not exceed 1.5% even for the smallest field size considered. A much wider range of kQB,QfB,f values was obtained for the active solid-state detectors included in the simulations. This is the first study to report kQclin,QmsrB,fclin,fmsr values for ionization chambers. The impact of the stem on correction factors is not significant for lengths ⩾0.75 cm. Correction factors determined in water are also valid in dosimetry protocols employing solid phantoms. Significance. This work substantially expands the range of available detectors that can be used in small field dosimetry, enabling more options for commissioning, beam modeling and quality assurance procedures in 1.5 T MR-Linacs. However, more studies are needed to establish a complete and reliable dataset.