There is an old tale of three blind men who were brought
to the zoo for the first time and allowed to touch the elephant.
On their way home, they shared this exciting experience. “An
elephant is a long, flexible, and cylindrical creature,” said the
man who had touched the elephant's trunk. “No! It is a thin and
flat creature,” said the man who had touched the elephant's ear.
“No, no! An elephant is rough and rigid like a tree stem,”
disagreed the third person who had touched the elephant's leg. And
the truth is that all three men were right!When trying to see the invisible with our medical imaging systems,
we are much like those three blind men. With each imaging
modality, we shed some light on a different aspect of the general
physiological picture. Although in some cases one modality may
suffice to provide a definitive clinical answer, this is not the
case in many other situations. Multimodal imaging (MMI) is
needed for three basic reasons: (a) to acquire complementary information which may be needed to reach a definitive diagnostic conclusion, exclude certain pathologies, or obtain quantitative values (e.g., [1, 2]); (b) to create
synergism by data fusion (i.e., to provide added
information and new images which are more informative than the
individual source images); (c) to plan therapeutic
procedures and monitor treatment (e.g., [3, 4]).An ideal MMI system or method should be capable of performing all
three tasks mentioned above. Naturally, that requirement might be
too demanding in terms of technological capabilities and
operational considerations. Hence, diagnostic and therapeutic
systems are commonly separated. However, one may see in
the near future more system integration in the form of
image-guided therapy.There are several technical issues that are associated with MMI. A
prerequisite is to obtain effective fusion and display of the data
(e.g., [5-7]). Accurate spatial (and maybe also temporal)
alignment is crucial for effective data fusion. There are
basically two approaches for achieving coregistration. The
first, which may be called the “hardware” approach, utilizes a
hybrid design comprising two (or more) imaging modalities that are
contained within a single device. The advantage of this approach
is that the imaging modalities acquire data sequentially while the
patient lies on the bed. The disadvantage is the need for
dedicated MMI equipment which may be cumbersome or costly.The second approach for achieving coregistration is the
“software-” based approach. With this approach, image properties
and tissue geometry and texture are used as clues for aligning the
data sets. Alignment is thus achieved by manipulating the acquired
data under certain optimization constraints or 3D model to achieve
the best (most probable) match (e.g., [8-11]). Of course
this approach is susceptible to noise and artifacts, but on the
other hand it allows better versatility, and in many cases may be
applied successfully to scans performed on different occasions and
at different locations. Nevertheless, it is now widely recognized
that the merger of information is more efficiently achieved by the
hardware approach. The recent (2001) introduction of hybrid
scanners has led to an expansion of this approach through the
rapid adoption of the technology into the clinical arena.One of the most promising examples of MMI hybrid systems that is
currently demonstrating a significant clinical impact is the
combination of CT with nuclear imaging, and specifically positron
emission tomography (PET). Following the development of a
prototype in the late 1990s [12], the first commercial combined PET/CT scanner was introduced in 2001 and since then,
close to 2000 of such devices from different vendors have been
installed in clinics worldwide. Both CT and PET technologies
continue to advance and since 2006, new PET scanners are now only
available in combination with CT. The MMI technology available
clinically has demonstrated particular impact in staging malignant
disease [13, 14] and in monitoring response of the disease to
therapy. The recent incorporation of high-speed, multislice CT
scanners with PET also opens up the potential for applying this
technology to cardiac disease.Another attractive modality for MMI is MRI. Although MRI imposes
severe restrictions on the imaging environment, it offers a broad
spectrum of scan types and image contrast. Compared with CT, MRI
offers greater soft-tissue contrast, better capability for
quantitation of function (e.g., measurement of blood flow or
tissue metabolism), and potentially new types of molecularly
targeted contrast agents. Efforts for combining MRI with other
modalities (e.g., PET/MRI and ultrasound/MRI) are currently under
development.Another aspect of MMI is the development of multimodal contrast
enhancing materials. Such materials can be used in the form of a
“fit-all” type of marker (e.g., [15]). Thus, their signals can be used as control points for 3D alignment. Alternatively,
they can be used as standard contrast agents used for disease
detection and characterization (e.g., [16]).In conclusion, considering the current tends in radiology, it can
be expected that MMI devices will become increasingly available in
the clinical arena. PET/CT has already made an important clinical
contribution to patient care for oncology, while the new combined
SPECT/CT designs are enhancing SPECT applications and improving
physicians' confidence with image interpretation. No doubt, new
combinations of hybrid devices will appear in the clinical arena
and in many situations. As demonstrated by PET/CT in the oncology
field, they will become the primary imaging option. A PET/MR
design for simultaneous acquisition of PET and MR has recently
acquired the first patient images, and a combined PET and
ultrasound device is also under development for breast imaging.
For many reasons, therefore, hybrid imaging devices are finding
widespread acceptance within the clinical environment and some are
already contributing to patient care and management. There is
little doubt that this trend will continue in the future with an
increasing reliance on MMI devices for medical imaging, thereby
ensuring that all involved can be satisfied that they will
eventually obtain a true and consistent picture of the elephant.
Authors: J L Bernon; V Boudousq; J F Rohmer; M Fourcade; M Zanca; M Rossi; D Mariano-Goulart Journal: Comput Med Imaging Graph Date: 2001 Jul-Aug Impact factor: 4.790
Authors: P Sabbah; H Foehrenbach; G Dutertre; C Nioche; O DeDreuille; N Bellegou; J F Mangin; C Leveque; T Faillot; J F Gaillard; M Desgeorges; Y S Cordoliani Journal: Clin Imaging Date: 2002 Jan-Feb Impact factor: 1.605
Authors: T Beyer; D W Townsend; T Brun; P E Kinahan; M Charron; R Roddy; J Jerin; J Young; L Byars; R Nutt Journal: J Nucl Med Date: 2000-08 Impact factor: 10.057
Authors: Rachel Bar-Shalom; Nikolai Yefremov; Ludmila Guralnik; Diana Gaitini; Alex Frenkel; Abraham Kuten; Hernan Altman; Zohar Keidar; Ora Israel Journal: J Nucl Med Date: 2003-08 Impact factor: 10.057