1 Background

Terahertz frequency (THzF) radiation lies between two safe (Fig. 1), non-ionizing regions of the electromagnetic spectrum: the microwave and the infrared. It can be generated by up-conversion from sources of micro-waves, or by down-conversion from sources of higher frequency [56]. It is strongly absorbed by polar molecules like water, that is why it is very sensitive to any difference in water content between healthy tissue and a tumor [49, 59]. Due to the non-ionizing nature of THz light and its high sensitivity to soft tissues, there is an increasing interest in biomedical applications including both in vivo and ex vivo studies.

Fig. 1
figure 1

The spectrum of the terahertz radiation

Full size image

Thanks to the development of terahertz sources and detectors of continuous and pulsed wave, methods of terahertz imaging (THzI) (CWI or TPI in reflection geometry) in vivo and ex vivo have spread rapidly [17,18,19, 21, 47,48,49, 51,52,53,54].

Investigations about various tissues to discriminate between healthy and malignant breast tissues were carried out [1, 2, 5, 6, 8, 13, 18, 25, 36, 40, 47, 51,52,53,54, 56]. Okada et al. [32] who reported terahertz near-field microscopy of ductal carcinoma in situ (DCIS) of the breast, Vafapour et al. [42] who reported the potential of terahertz sensing for cancer diagnosis, Ke et al. [26, 27] used THz technology in vivo sensing of rabbit cornea, Cassar et al. [7] who reported investigations led on the combination of the refractive index and morphological dilation to enhance performances toward breast tumor margin delineation during conserving surgeries. Smolyanskaya et al. [35] discussed in their review THz dielectric permittivity of water and water—containing media, using THz time-domain spectroscopy and spectroscopy, and sub-wavelength resolution THz imaging.

1.1 Image data treatment

A number of algorithms some with numerical simulation [3] were developed to process THz image data [33]. Studies about pattern identification in a series of medical images recorded in a timestamps were carried out [57]; approaches for image-huge data supervised classification using support vector machine (SVM) [20] and unsupervised clustering using k-means [one of machine learning algorithms] [4] were developed. Ornstein–Uhlenbeck process used to distinguish Malignant and benign thyroid nodule [16, 22, 24, 28,29,30, 41].

1.2 THz radiation effects

Various studies about THz effects on biological tissues were carried out [50]. Sun et al. [38] reported that THz light is absorbed by H-bonds presents in water and proteins, deducing its sensitivity to any change in water or blood content. Son et al. [36] reported in their review that methylated malignant DNA exhibits a characteristic resonance at approximately 1.65 THz, which may help in treating cancer through the demethylation of malignant DNA using high-power terahertz pulse at this specific frequency. Cherkasovaa et al. [9] discussed in their review THz thermal effects on tissue and its ability to induce resonance effects. With high energy pulse, THz radiation may penetrate the cytoplasm and the membrane of the nucleus. Nikitkina et al. [31] reported in their review the effects of THz radiation and problems of using it in medical diagnosis, THz Dosimetry, effects of this Radiation on Blood, Skin, Nerve and Stem Cells, and mechanism that underlie the effects of THz Radiation and showed the possibility of cancer therapy using the appropriate intensity of THz waves, depending the case [10,11,12, 14, 15, 37, 39, 43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58].

1.3 The aim of the work

The aim of this work was measuring the awareness of medical community in our country in order to apply the THz technology to improve the resolution of tumor surgery and may be, treating certain cases of cancer. The availability of THz imaging and spectroscopic techniques and their ability to distinguish between benign and malignant tissues, as well as the possibility to heal some tumors by THz exposure encourage us to set off our project.

2 Methods

The latter facts motivated us to launch, using Google forms, a survey of 33 questions to obtain information about the scientific community’s awareness of the use of THz technique in Syrian Arab Republic, with an ambition to make tumor surgery more accurate and results of histopathology of excised tissues faster. The survey consisted of 2 groups of questions. The first group, which aims to promote practicing THz methods in Syrian Arab Republic, involves 28 questions concerning THz waves, sources, properties, uses in tissue imaging and spectroscopy, and its importance in pain relieving for patients who bore a tumor surgery. The second group of 5 questions concerns the knowledge of some information about THz Technique. The survey targeted scientific faculties: Medicine, Dentistry, Pharmacy, Science and other faculties, of various qualifications ranging from undergraduates to university degree, M.A degree and Ph.D. We used IBM SPSS statistics 26 software (Lawrence 1983, [34], and [23] for analyzing the results.

The survey was launched on google drive, and the data were transferred to an excel file, where problems regarding survey were resolved and then, was translated into English. From the order of filtering order, we obtained the distribution of survey participants by qualification and distribution of survey participants by specialty.

We set up a page of data view and variable view on SPSS statistic program, version 26, that is filled, for each specialty by the numbers of participants from all qualifications and for each qualification by the numbers of participants from all specialties. From Graphs-Legacy Dialogs-line -Simple-Summaries for groups of cases, we obtained the first group of curves. Figure 2 represents distribution of survey participants by qualification. Figure 3 represents distribution of survey participants by specialty. Figures 4, 5, 6, 7 and Additional file 1: Fig. S1 show distribution of each specialty participants by qualification; Figs. 8, 9, 10 and 11 show distribution of each qualification participants by specialty.

Fig. 2
figure 2

Distribution of survey participants by qualification

Full size image
Fig. 3
figure 3

Distribution of survey participants by specialty

Full size image
Fig. 4
figure 4

Distribution of survey dentistry participants by qualification

Full size image
Fig. 5
figure 5

Distribution of survey medicine participants by qualification

Full size image
Fig. 6
figure 6

Distribution of survey pharmacy participants by qualification

Full size image
Fig. 7
figure 7

Distribution of survey science participants by qualification

Full size image
Fig. 8
figure 8

Distribution of survey other participants by qualification

Full size image
Fig. 9
figure 9

Distribution of survey college degree participants by specialty

Full size image
Fig. 10
figure 10

Distribution of survey college student participants by specialty

Full size image
Fig. 11
figure 11

Distribution of survey M.A degree participants by specialty

Full size image

To get the rest of the curves, we followed these steps: from file-import data-excel, we transferred the survey file from an excel file to the statistical program SPSS.

The curves of the first group of survey questions in Figs. 12a, b, 13a, b, 14a, b, 15a, b and Additional file 1: Fig. S2 were prepared for, by splitting data file by qualification, whereas curves in Figs. 16a, b, 17a, b, 18a, b, 19a, b were prepared for, by splitting data file by specialties. Figures (a) for the choice: I know it from cultures, (b) for the choice: I don’t know. A table is made for each group of curves.

Fig. 12
figure 12

a I know it from cultures and b I don’t know

Full size image
Fig. 13
figure 13

a I know it from cultures and b I don’t know

Full size image
Fig. 14
figure 14

a I know it from cultures and b I don’t know

Full size image
Fig. 15
figure 15

a I know it from cultures and b I don’t know

Full size image
Fig. 16
figure 16

a I know it from cultures and b I don’t know

Full size image
Fig. 17
figure 17

a I know it from cultures and b I don’t know

Full size image
Fig. 18
figure 18

a I know it from cultures and b I don’t know

Full size image
Fig. 19
figure 19

a I know it from cultures and b I don’t know

Full size image

Curves of Figs. 20a–d, 21a–d, 22a–d, 23a–d and Additional file 1: Fig. S3 were prepared for by splitting data file by qualification, and curves Figs. 24a–d, 25a–d, 26a–d and 27a–d by splitting data file by specialty. A table was set for each group of curves. (a) for the choice: Yes, (b) for: No, (c) for: May be, and (d) for: I don’t know.

Fig. 20
figure 20

a I don’t know, b may be, c yes and d no

Full size image
Fig. 21
figure 21

a I don’t know, b may be, c yes and d no

Full size image
Fig. 22
figure 22

a I don’t know, b may be, c yes and d no

Full size image
Fig. 23
figure 23

a I don’t know, b may be, c yes and d no

Full size image
Fig. 24
figure 24

a I don’t know, b may be, c yes and d no

Full size image
Fig. 25
figure 25

a I don’t know, b may be, c yes and d no

Full size image
Fig. 26
figure 26

a I don’t know, b may be, c yes and d no

Full size image
Fig. 27
figure 27

a I don’t know, b may be, c yes and d no

Full size image

Each group of curves in a figure is obtained as follows: Graphs-Legacy Dialogs-line -Multiple-Summaries for Separate Variables.

3 Results

When interviewed, a number of local oncologists in the Syrian Arab Republic who reported that they visually delineate the contour of the tumor to be removed, and in order to reduce the number of future possible interventions, a large margin of healthy tissue is often excised (This precaution, however, reflects negatively on the speed of healing process). Furthermore, a number of pathologists who reported that preparing samples of excised tissues for examination takes a long period of time which may extend to several days, and that the results of histopathology indicate in some cases the integrity of removed tissues. Studies taking place currently in some parts of the world show that, owing to the THz sensitivity to tissue content of water, which increases in case of tumors, THz imaging can delineate tumor contour with a high precision. At present, studies of excised tissues are carried out utilizing each of the metabolites signature in a tissue when subjected to the terahertz radiation, as well as, the capability of this radiation to distinguish malignant tumor from benign ones without need to a preparation process.

The number of participants in the survey was 1549 after deleting the wrong cases. Figure 2 illustrates the distribution of survey participants by Qualification, while Fig. 3 shows the distribution of survey participants by Specialty. The participation of College Students (Fig. 2) from different specialties was the highest (696, 44.9%, and in particular, participants with a background in medicine (Fig. 3) of various qualifications (college degree, college student, M.A and Ph.D.) were highest (873, 56.36%). Figures 4, 5, 6 and 7 show the statistical distributions of the survey participants from Dentistry, Medicine, Pharmacy and Science (Other faculties) according to Qualification, and that the participation of the college students is the highest regardless of their specialty. Figures 8, 9, 10 and 11 show the statistical distributions for the qualification levels, college degree, college student, M.A and Ph.D., respectively, with their specialty is the variable. Regardless of their qualification’s level, medical participants were always dominant.

The answer choices for the second group of survey questions were

  1. 1.

    Yes.

  2. 2.

    No.

  3. 3.

    May be.

  4. 4.

    I don’t know.

4 Discussion

4.1 Statistical results of the first group of questions

The answers were distributed, in particular, between the third choice and the last one. To deduce the information describing the awareness of the Scientific Community of THz technique, we plotted the statistic curves for those who chose “I know it from lectures” and for those who selected “I don’t know” for all the participants of various specialties and qualifications and for all the questions. The ratios of other answer choices (1, 2, 4 and 5) were very low. The curves showed a magnificent coherence between various qualifications in a specialty (Figs. 12, 13, 14, 15) with a minor exception. The curves of Additional file 1: Fig. S2a show very little coherence between various qualifications in other specialties (Medical Engineering, Informatics, …,), while Additional file 1: Fig. S2b show a slightly higher degree of coherence. Figures 16, 17, 18 and 19 show the strong degree of coherence between various specialties in a qualification. The total number of participants in the survey with medicine background reached 873, of which 402 (46.0%), are undergraduates, 297 (34.0%) with a university degree, 117 (13.4%) with a master's degree, and 57 (6.5%) are Ph.D. holders (Fig. 12a, b).

For the dentistry, the total number of participants in the survey with dentistry background is 228, of which 105 (46.1%) are undergraduates, 64 (28.1%) with a university degree, 47 (20.6%) with a master degree, and 12 (5.3%) are Ph.D. holders (Fig. 13a, b). For the Pharmacy, the total number of participants in the survey with pharmacy background reached 124 members, of which 52 (41.9%) are undergraduates, 45 (36.3%) with university degree, 24 (19.4%) with a M.A. degree, and 3 (2.4%) Ph.D. holders, Fig. 14a, b, while for the science, the total number of participants in the survey with Science background is 244 members, of which 110 (45.1%) are undergraduates, 87 (35.7%) with a University degree, 24 (9.8%) with a M.A. and 23 (9.4%) are Ph.D. holders (Fig. 15a, b).

Finally for the Other Specialties (Medical Engineering, Informatics, …), the total number of participants in the survey with various specialties background is 80 members, of which 27 (33.8%) are undergraduates of various specialties, 28 (35.7%) with a University degree, 19 (23.8%) with a master's degree and 6 (7.5%) are Ph.D. holders (Additional file 1: Fig. Fig. S2a, b).

By classifying the answers based on undergraduate students, the total number of participants is 696, 402 (57.76%) of medicine, 105 (15.09) of dentistry, 52 (7.47%) of pharmacy, 110 (15.80%) of science and 27(3.88%) of other faculties, Fig. 16a, b. For university degree of various specialties, the total number of participants is 521, of which 297 (57.01%) of medicine, 64 (12.28%) of dentistry, 45 (8.64%) of pharmacy, 87 (16.70%) of science and 28(5.37%) of other faculties (Fig. 17a, b). For Master's degree holders in any specialty, the total number of participants is 231, of which 117 (50.65%) in medicine, 47 (20.35%) in dentistry, 24 (10.39%) in pharmacy, 24 (10.39%) in science and 19(8.23%) in other faculties (Fig. 18a, b). For the Ph.D. holders in any specialty, the total number of participants is 101, of which 57 (56.44%) in medicine, 12 (11.88%) in dentistry, 3 (2.9%) in pharmacy, 23 (22.77%) in science and 6 (5.94%) in other faculties (Fig. 19a, b).

4.2 Statistical results of the second group of survey questions

The answers were distributed between the 4 choices. We plotted the statistic curves for each choice for all the participants of various specialties and qualifications and for all the 5 questions. The curves show highly coherent response of participants of various qualifications in each specialty (Figs. 20, 21, 22, 23), with some exception. The curves of Additional file 1: Fig. S3a–d show much less coherence, for some choices, between various qualifications from faculties that are less concerned with the technique of terahertz. Figures 24, 25, 26 and 27 show the coherence between various specialties in a qualification. For the medicine of various qualifications, Fig. 20a–d, for the choices 1, 2, 3 and 4, respectively.

For the dentistry of various qualifications, Fig. 21a–d, for the choices 1, 2, 3 and 4, respectively. For the pharmacy of various qualifications, Fig. 22a–d, for the choices 1, 2, 3 and 4, respectively, and for the science of various qualifications, Fig. 23a–d, for the choices 1, 2, 3 and 4, respectively, while for the Other specialties (Medical Engineering, Informatics, …) of various qualifications, Additional file 1: Fig. S3a–d, for the choices 1, 2, 3 and 4, respectively.

For the Undergraduate students of various specialties, Fig. 24a–d, for the choices 1, 2, 3 and 4, respectively. For the university degree of various specialties, Fig. 25a–d, for the choices 1, 2, 3 and 4, respectively. For M.A., of various specialties, Fig. 26a–d, for the choices 1, 2, 3 and 4, respectively, and for Ph.D. of various specialties, Fig. 27a–d, for the choices 1, 2, 3 and 4, respectively.

5 Conclusions

This result is logic. The first author was engaged in teaching medical physics for students of medicine at Damascus University since 3 decades. 8 years ago engaged in teaching Medical Physics to students of dentistry at Syrian Private University, meanwhile engaged in the program of Physics for Preparatory year for medical colleges (medicine, dentistry and pharmacy). That is why most of the survey participants were undergraduate students of medicine, fewer young physicians of different specialties, comprising radiologists, M.A and PHd.

From the above curves, we have found that the great coherence of awareness between participants of various qualification with medicine and dentistry background, less coherence with faculties that are less concerned with the technique of Terahertz. A significant number of participants in the survey provided us, on messenger, with comments demonstrated that the importance of dealing with THz imaging and THz spectroscopy, encouraging to implement the technique in the Syrian Arab Republic. We present in this paper some comments for undergraduate students of medicine, physicians and pharmacists.

A significant number of participants in the survey provided us (on messenger) with comments that highlight the importance of adopting THz imaging and THz spectroscopy and urge encourage to implement this technique in the Syrian Arab Republic. We present in this paper some comments for undergraduate students of medicine, physicians and pharmacists.