Rossella Canese1, Miriam Dolciami2, Claudia Testa3, and Lucia Manganaro2
1Core Facilities, Istituto Superiore di Sanita', Rome, Italy, 2Department of Radiological, Oncological and Pathological Sciences, Policlinico Umberto I Sapienza University of Rome, Rome, Italy, 3Department of Physics and Astronomy, University of Bologna, Bologna, Italy, Rome, Italy
Synopsis
Cervical cancer (CC) is the fourth most common malignancy and
cancer-related mortality cause in women worldwide. A significant portion of
these patients are diagnosed as locally advanced cervical cancer (LACC), thus
requiring combined therapies. We investigate the role of the lipid signal derived from 1H magnetic
resonance (MR)-spectroscopy in assessing response to neoadjuvant chemotherapy
of LACC.
Introduction
Cervical cancer (CC)
is the fourth most common malignancy and cancer-related mortality cause in
women worldwide, with a higher prevalence in developing countries.1 Surgery
represents the gold standard in early-stage CC. However, a significant portion
of these patients are already diagnosed as locally advanced cervical cancer,
thus requiring combined therapies, such as concurrent chemo-radiotherapy (CCRT)
or neoadjuvant chemotherapy (NACT) combined with radical surgery (RS).2
Due to its excellent soft-tissue characterization, MRI represents the imaging
technique of choice for the staging of CC, playing a fundamental role in
assessing therapeutic strategy and response to therapy3. Besides the anatomical characterization
provided by conventional MRI, localized proton magnetic resonance spectroscopy
(1H MRS) allows in vivo metabolic characterization of a suspicious lesion,
giving non-invasive information useful for a more accurate and faster diagnosis4.
Few studies have
applied MRS to distinguish between benign and malignant gynecologic lesions,
including CC5-6 or as a response biomarker in cervical cancer7,
but with uncertain results.
Purpose
The purpose of our study was to investigate the
role of the lipid peak derived from 1H magnetic resonance (MR)-spectroscopy in
assessing cervical cancer (CC) prognosis, particularly in assessing response to
neoadjuvant chemotherapy of locally advanced cervical cancer (LACC).Methods
We enrolled 17 patients with histologically
proven CC who underwent MR at baseline. Images and spectra were acquired using
a superconducting magnet operating at a field strength of 3.0 T (GE Discovery
MR 750, GE Healthcare, Milwaukee, WI, USA) with an 32-channel phased-array
coil positioned on lower abdomen. In addition to conventional sequences for
pelvic assessment, the MR protocol included a single-point voxel resolved
spectroscopy (PRESS) sequence, with repetition time (TR) of 1500 ms and echo
time (TE) of 28 and 144 ms. Voxels (volume 18x18x18 mm3) were positioned
in the central part of the tumor, carefully avoiding contamination from
surrounding tissues and areas of necrosis. The short echo time (TE=28 ms) was
chosen for metabolite quantification, while the longest TE was chosen for the
detection of Lac whose signal can be hidden when a large lipid signal
(resonating at 1.28 ppm) is also present. Spectra were analyzed using the
LCModel fitting routine, thus extracting multiple metabolites, including lipids.
A quantitative protocol, which use the unsuppressed water signal as internal
standard was also applied.8
11/17 patients were found to be LACC. These
patients were treated with neoadjuvant chemotherapy and reassessed at term with
MR at 3 months. Patients were then divided into two groups: good responder (GR;
response to therapy >50%) and poor responder/non-responder (PR/NR; response
<50% or <20% respectively). Results
11/17 patients were found to be LACC. Of these
5 patients were excluded from further analysis because 3 were lost to follow-up
and 2 had a non-diagnostic spectrum due to a signal-to-noise ratio (SNR) <4.
Of the remaining 6 patients, 3 were GR and 3 PR/NR.
A statistically significant difference in lipid
values was observed in the two groups of patients, in particular with higher Lip
values in PR/NR patients than in GR patients, as shown in Figure 1.
Furthermore, a significant difference was also observed in the lipid/choline
ratio (Lip/tCho), with higher values in PR/NR patients (Figure 2). The absence
of lactate in the long echo time spectra (TE=144 ms) excluded lipid
overestimation in the quantitative analyses.Conclusions
According to our study, assessment of lipid
peak at 1H-MR-spectroscopy could be an additional quantitative parameter in
predicting the response to neoadjuvant chemotherapy in patients with LACC. Acknowledgements
No acknowledgement found.References
1)
Arbyn M,
Weiderpass E, Bruni L, et al. Estimates of incidence and mortality of cervical
cancer in 2018: a worldwide analysis. Lancet
Glob Health. 2020;8(2):e191-e203. doi:10.1016/S2214-109X(19)30482-6
2)
Bhatla N, Berek
JS, Cuello Fredes M, et al. Revised FIGO staging for carcinoma of the cervix uteri
[published correction appears in Int J Gynaecol Obstet. 2019 Nov;147(2):279-280]. Int J Gynaecol Obstet.
2019;145(1):129-135. doi:10.1002/ijgo.12749
3)
Manganaro L,
Lakhman Y, Bharwani N, et al. Staging, recurrence and follow-up of uterine cervical
cancer using MRI: Updated Guidelines of the European Society of Urogenital
Radiology after revised FIGO staging 2018 [published correction appears in Eur
Radiol. 2021 Jun 17;:]. Eur Radiol.
2021;31(10):7802-7816. doi:10.1007/s00330-020-07632-9
4) García-Figueiras R,
Baleato-González S, Padhani AR, et al. Proton magnetic resonance spectroscopy
in oncology: the fingerprints of cancer?. Diagn Interv Radiol.
2016;22(1):75-89. doi:10.5152/dir.2015.15009
5) Booth SJ, Pickles
MD, Turnbull LW. In vivo magnetic resonance spectroscopy of gynaecological
tumours at 3.0 Tesla. BJOG. 2009;116(2):300-303.
doi:10.1111/j.1471-0528.2008.02007.x
6) Mahon MM, Cox IJ, Dina R, et al. (1)H magnetic
resonance spectroscopy of preinvasive and invasive cervical cancer: in vivo-ex
vivo profiles and effect of tumor load. J Magn Reson Imaging. 2004;19(3):356-364.
doi:10.1002/jmri.20012
7) Harry VN. Novel
imaging techniques as response biomarkers in cervical cancer. Gynecol
Oncol. 2010;116(2):253-261. doi:10.1016/j.ygyno.2009.11.003
8) Canese R, Pisanu ME, Mezzanzanica D, et al. Characterisation of
in vivo ovarian cancer models by quantitative 1H magnetic resonance
spectroscopy and diffusion-weighted imaging. NMR Biomed.
2012;25(4):632-642. doi:10.1002/nbm.1779