Abstract:
Non-invasive therapeutic treatment and/or quantitative evaluation of bone tissue are performed in vivo, by subjecting bone to an ultrasonic acoustic signal pulse of finite duration, and involving a composite sine-wave signal consisting of plural discrete frequencies that are spaced in the ultrasonic region to approximately 2 MHz; the excitation signal is repeated substantially in the range 1 to 1000 Hz. 
     In a quantitative evaluation, the composite sine-wave signal is supplied to one of two transducers on opposite sides of the bone, and the signal received by the other transducer is processed (a) to sequentially average the most recently received given number of successive signals to obtain an averaged per-pulse signal and (b) to produce a Fourier transform of the averaged per-pulse bone-transmitted signal. In a separate operation not involving the bone, the same transducers are subjected to the same excitation, reception and processing, wherein the transducers are exposed to a medium of known acoustic properties and path length, all to the end of producing a reference Fourier transform which is processed with the Fourier transform of the bone-transmitted signal, to yield an evaluation or measurement. 
     In a therapeutic treatment, the transducer supplied by the composite sine-wave signal is thus supplied for a period or periods of time, and with a magnitude, as may be prescribed by the physician for a given patient.

Description:
RELATED CASE 
     This application is a continuation-in-part of copending application Ser. No. 07/922,136, filed Jul. 30, 1992. 
    
    
     BACKGROUND OF THE INVENTION 
     The invention pertains to apparatus and method for non-invasively therapeutically treating and/or quantitatively evaluating bone tissue in vivo, wherein the evaluation is manifested, at a given time, through one or more of the quantities: bone-mineral density, strength, and fracture-risk. 
     In recent years, various attempts have been made to use ultrasonic energy to assess the condition of bone tissue, in vivo, but these attempts have been essentially ad hoc, with no consistent framework within which to analyze data. A great deal of information is obtainable from ultrasonic experiments, but much of the information has not been used. The signal-processing techniques that have been used have been so simple as to ignore available and useful aspects of the data, and the signal-to-noise ratio of experimental data has been relatively poor. 
     U.S. Pat. No. 3,847,141 to Hoop discloses a device to measure bone density as a means of monitoring calcium content of the involved bone. A pair of opposed ultrasonic transducers is applied to opposite sides of a patient&#39;s finger, such that recurrent pulses transmitted via one transducer are &#34;focused&#34; on the bone, while the receiving response of the other transducer is similarly &#34;focused&#34; to receive pulses that have been transmitted through the bone. The circuitry is arranged such that filtered reception of one pulse triggers the next pulse transmission; the filtering is by way of a bandpass filter, passing components of received signals, only in the 25 to 125 kHz range; and the observed frequency of retriggering is said to be proportional to the calcium content of the bone. Thus, Hoop is not concerned with anything more than what he perceives to be transit time for pulses in the indicated band. 
     Pratt, Jr. is identified with a number of U.S. Pat. Nos. including 4,361,154, 4,421,119 (divisionally related to the &#39;154 patent, and subsequently reissued, as Re. 32,782), 4,913,157, and 4,941,474, all dealing with establishing, in vivo, the strength of bone in a live being such as a horse. In the first three of his patents, the inventor bases his disclosures on the measurement of transit time from &#34;launch&#34; to &#34;reception&#34; of pulses of 0.5 MHz and 1.0 MHz through the bone and soft tissue, and from measurement of pulse-echo time, to thereby derive a measurement of transit time through bone alone. A data bank enables his evaluation of the meaning of variations in measurements of transit time, which the inventor deduces to be propagation velocity through each measured bone. The inventor&#39;s U.S. Pat. No. 4,913,157 operates on the same general principle of transit-time/velocity deduction, using the later preferred frequency of 2.25 MHz as the base frequency of pulsed &#34;launchings&#34;, and he purports to derive the bone-transfer function from analysis of an average of received pulses. In his U.S. Pat. No. 4,941,474, the inventor further refines his technique of transit-time/velocity deduction, inter alia, by separately determining the ratio of the velocity of his observed &#34;bone signal&#34; to the velocity of his observed &#34;soft-tissue signal&#34;, using the technique of matched filtering/Fourier transform filtering set forth in his U.S. Pat. No. 4,913,157. 
     Duarte, U.S. Pat. No. 4,530,360 discloses apparatus and a method of using ultrasonic energy for therapeutic treatment of bone tissue in vivo, using a pulsed sine wave at substantially a single frequency within the range 1.3 to 2.0 MHz, and at a pulse repetition rate of 100 to 1000 Hz. This disclosure represents a relatively narrow-band approach and does not take into account significant differences in ultrasonic attenuation between soft tissue and bone, thus substantially limiting the therapeutic effectiveness of Duarte treatments. 
     Palmer, et al., U.S. Pat. No. 4,774,959 discloses apparatus for deriving the slope of the relation between ultrasonic frequency and attenuation, for the case of a sequence of tone signals, in the range 200 to 600 kHz, applied to one transducer and received by another transducer, (a) after passage through a heel bone, in comparison with (b) passage between the same two transducers without the intervening presence of the heel. The assumption necessarily is that the frequency/attenuation relation is a straight line, i.e. of constant slope. 
     Brandenburger, U.S. Pat. No. 4,926,870 discloses another in vivo bone-analysis system which depends upon measuring transit time for an ultrasonic signal along a desired path through a bone. A &#34;Canonical&#34; wave form, determined by previous experience to be on the correct path, is used for comparison against received signals for transmission through the patient&#39;s bone, while the patient&#39;s bone is reoriented until the received signal indicates that the patient&#39;s bone is aligned with the desired path. Again, ultrasonic velocity through the patient&#39;s bone is assumed to have been determined from measured transit time. 
     Rossman, et al., U.S. Pat. No. 5,054,490 discloses an ultrasound densitometer for measuring physical properties and integrity of a bone, upon determination of transit time, in vivo, through a given bone, in comparison with transit time through a medium of known acoustic properties; alternatively, the Rossman, et al. device compares absolute attenuation of specific frequency components of ultrasound acoustic signals through the bone with the absolute attenuation of the same frequency components through a medium of known acoustic properties. For attenuation measurements, a &#34;broad-band ultrasonic pulse&#34; is recommended and is illustrated as a single spike &#34;which resonates with a broadband ultrasonic emission&#34;. The necessary comparisons are performed by a microprocessor, resulting in a slope of attenuation versus frequency in the broadband of interest. The frequencies or frequency ranges are not disclosed. 
     The prior art, exemplified by the references that have been briefly discussed, proceed on the assumptions either that transit time is all-important in assessing acoustic velocity or that only one or a few specific ultrasonic frequencies are significant in the determination of the attenuation versus frequency &#34;slope&#34; of a presumably linear relationship. However, the present inventors have found that the attenuation versus frequency relation for bone is non-linear, over the range of ultrasonic frequencies of likely interest, namely, up to approximately 2 MHz, and that potentially significant data exist and have been discarded or overlooked in the prior art through a preoccupation with measuring transit time and/or the velocity of ultrasonic acoustic propagation through bone and soft tissue. Moreover, prior efforts to achieve a broadband analysis have overlooked a need to assure adequate signal above noise throughout a relevant broadband of ultrasonic frequencies. 
     BRIEF STATEMENT OF THE INVENTION 
     It is accordingly an object of the invention to provide an improved method and apparatus for non-invasive and quantitative evaluation of bone tissue in vivo. 
     Another object is to meet the above object, such that bone-mineral density, strength, and fracture risk may be readily and more reliably evaluated than heretofore. 
     A specific object is to achieve the above objects with a broadband approach wherein ultrasonic signal sufficiently exceeds noise throughout the broadband, to enable evaluation of received signal above noise, throughout the broadband ultrasonic region to about 2 MHz. 
     A further object is to use the above-noted evaluation signal as a therapeutic source for bone treatment. 
     It is a general object to achieve the foregoing objects with apparatus components that are commercially available. 
     Briefly stated, the invention in its presently preferred form achieves the foregoing objects by iteratively subjecting bone to an ultrasonic acoustic excitation signal pulse of finite duration, supplied to one of two transducers on opposite sides of the bone, and involving a composite sine-wave signal consisting of plural discrete frequencies that are spaced in the ultrasonic region to approximately 2 MHz; the excitation signal is repeated substantially in the range 1 to 1000 Hz. Signal-processing of received signal output of the other transducer is operative (a) to sequentially average the most recently received given number of successive signals to obtain an averaged per-pulse signal and (b) to produce a Fourier transform of the averaged per-pulse signal. In a separate operation not involving the bone, the same transducers respond to the transmission and reception of the same excitation signal via a medium of known acoustic properties and path length to establish a reference signal, and this reference signal is processed to produce the Fourier transform of the reference signal. The two Fourier transforms are comparatively evaluated to produce a bone-transfer function, and the bone-transfer function is processed to derive the frequency-dependent specific-attenuation function μ(f) and the frequency-dependent group-velocity function v g  (f) associated with the bone-transfer function; specifically, the frequency-dependent group velocity function v g  (f) is related to the derivative of the phase of the bone-transfer function, as a function of frequency. Finally, a neural network, configured to generate an estimate of one or more of the desired bone-related quantities, is connected for response to the specific-attenuation function v g  (f) and to the group-velocity function v g  (f), whereby to generate the indicated estimates of the status of bone that is being analyzed. 
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The invention will be described in detail for a presently preferred embodiment, in conjunction with the accompanying drawings, in which: 
     FIG. 1 is an electrical-circuit diagram schematically showing the interconnected relation of components of apparatus of the invention; 
     FIG. 2 is, for a first embodiment, a flow chart of computer-controlled operations in automatically analyzing and quantitatively reporting estimates of relevant bone-related factors; and 
     FIG. 3 is a flow chart similar to that of FIG. 2, but for another embodiment. 
    
    
     The invention is shown in FIG. 1 in application to interconnected components for constructing apparatus for performing methods of the invention, namely, for non-invasively and quantitatively evaluating the status of bone tissue in vivo, as manifested through one or more of the quantities: bone-mineral density, strength, and fracture risk at a given time. These components are, in general, commercially available from different sources and will be identified before providing detailed description of their total operation. 
     In FIG. 1, the bone locale 10 to be analyzed in vivo is shown surrounded by soft tissue 11 and to be interposed between two aligned and opposed ultrasonic transducers 12, 13, which may be identically the same, and obtainable from Panametrics, Inc., Waltham, Mass.; suitably, each of transducers 12, 13 may be Panametrics &#34;VIDEOSCAN&#34; part number V318-SU, having a nominal element size of 3/4-inch diameter, and rated for 500 kHz. As shown, transducer 12 is used for signal launching and transducer 13 is the receiver of the launched signals after passage through bone 10, through its surrounding soft tissue 11, and through a coupling medium such as a gel between each transducer face and outer skin of the soft tissue 11. 
     Basic operation is governed by computer means 14, which may be a PC computer, such as the &#34;25 MHz 386&#34; available from Gateway 2000, Inc., North Sioux City, S.D.; as its designation suggests, this computer contains a 25 MHz clock-pulse generator, and an Intel 80386 processor, with provision for keyboard instruction at 14&#39;. 
     An arbitrary function-generator card 15 is shown installed in the computer. This card is relied upon to generate an excitation signal which is periodically supplied to the launch transducer 12, via power amplifier means 16. The power amplifier is suitably Model No. 240L, an RF power-amplifier product of EIN, Inc., Rochester, New York. This product provides a 50 dB gain, over the range 20 kHz to 10 MHz. 
     The excitation signal generated by card 15 is a finite-duration composite sine-wave signal, consisting of plural discrete frequencies that are spaced in the ultrasonic spectral region to approximately 2 MHz, and this excitation signal is repeated substantially in the range 1 to 1000 Hz. Card 15 may suitably be a waveform synthesizer product of Quatech, Inc., Akron, Ohio, identified by Quatech part No. WSB-100. This waveform synthesizer provides generation of analog signals independent of the host computer 14, allowing full processor power to be used for other tasks, including calculation of waveform data; it has the capacity to generate an output signal comprising literally thousands of points in the indicated ultrasonic frequency region. 
     Another card 17 is also shown installed in the computer for converting signals received at 13 in digital format for further processing in computer 14. Card 17 may suitably be a 100 MHz waveform digitizer, part number &#34;STR*8100&#34;, a product available from SONIX, of Springfield, Va. A connection 18 is shown by dashed lines, connecting the signal-generator card 15 to the A/D card 17, for synchronizing purposes and for the purposes of digitizing the excitation signals, to enable computer 14 to perform a suitably compensated, continuously operative updating average of the signals received at 13. 
     Finally, general signal-processing/display/storage software, for the signal-processing control and operation of the computer is not shown but will be understood to be a floppy disk loaded at 19 into the computer; this software is suitably the MATLAB-386, available from The Math Works, Inc., Natick, Mass. Further software, also not shown but loaded into the computer, is neural-network software, identified as EXPLORENET 3000, a product of HNC, Inc., San Diego, Calif. 
     In the presently preferred embodiment, involving the described components of FIG. 1, the same components are utilized not only for performing the continuously updated averaging of the latest succession of signals received at 13, but also for establishing and entering into computer storage the Fourier transform of a reference signal that is obtained by removing the body part 10, 11 from the space between transducers 12, 13. 
     Computer operation on the updated average of the received signals will be referred to as the averaged per-pulse signal, and this averaged per-pulse signal is also signal-processed in the computer into the Fourier transform of the averaged per-pulse signal. 
     The computer will be understood to be further programmed to comparatively and continuously evaluate the Fourier transform of the currently averaged per-pulse signal, against the Fourier transform of the reference signal, thereby producing a bone-transfer function. Still further, the computer will be understood to be programmed to process the bone-transfer function to derive the frequency-dependent specific-attenuation function μ(f) and the frequency-dependent group-velocity function v g )f) associated with the bone-transfer function. Finally, these two functions, for each of the large plurality of involved frequencies in the composite sine-wave signal are supplied within the computer to the neural network, it being understood that the neural network will first have been trained and configured to generate an estimate of one or more of the above-indicated and currently analyzed bone properties, namely, bone-mineral density, strength, and fracture risk. 
     In the presently preferred embodiment of the invention and with additional reference to the flow diagram of FIG. 2, data is collected and processed as follows. A bony member (10, 11) is placed between two ultrasound transducers (12, 13). An ultrasound signal is transmitted from transducer (12), passes through the bony member, and is received by the other transducer (13). The transmitted ultrasound signal is generated using a finite-duration composite sine-wave signal. A single repetition of this waveform is described by ##EQU1## where a i  and φ i  are the amplitude and phase, respectively, associated with frequency f i , i=1, . . . ,N, and T is chosen to be at least two times longer than the period of the lowest frequency f 1 . The frequencies f i  are selected from within the range 25 kHz-2 MHz. In this preferred embodiment, the lowest frequency f 1  =100 kHz, T=20 microseconds, and the frequency range is 100 kHz-800 kHz, with 50 kHz intervals, for a total of N=15 frequencies. The phases φ i  are pseudo-random numbers distributed uniformly between 0 and 2π. This ensures that peak amplitudes are minimized for fixed signal power. The amplitudes, a i , are chosen according to the relationship ##EQU2## In this expression, B is the attenuation of an average bony member and |H r  (f i )| is the magnitude transfer function of the overall ultrasound measurement system when a medium of negligible attenuation is placed between the two transducers. 1  In this preferred embodiment of the invention, B=10 nepers MHz -1 , and |H r  (f i )| is the magnitude Fourier transform of the received waveform after it has propagated through water using an impulsive-type input signal. This choice for the amplitudes of the composite sine-wave signal ensures that the received signal has approximately constant signal-to-noise ratio throughout the frequency range. 
    
     The above waveform is transmitted periodically at a repetition rate of 500 Hz. In the presently preferred embodiment, each received waveform, s j  (t), is averaged a total of 100 times to obtain the averaged per-pulse signal, s(t). Subsequently, the Discrete Fourier Transform (DFT), S(f), of s(t) is obtained using the Fast Fourier Transform (FFT) algorithm. 
     A reference signal, r(t) is also obtained by averaging 100 ultrasound signals, transmitted through water only, i.e., by removing the bony member and replacing it with water. The same composite sine wave input signal is used for generation of the reference signal, in order that the bone-transfer function be obtained as shown below. The DFT, R(f), of the reference signal is then obtained using the FFT. 
     The data is further processed to obtain the bone transfer function, H(f), where ##EQU3## H(f) is processed further to obtain the frequency-dependent specific-attenuation function, μ(f), and frequency-dependent group-velocity function, v g  (f): 
     
         μ(f)=-log(|H(f)|.sup.1/L)             (4) 
    
     and ##EQU4## Here, v w  is the velocity of ultrasound in water, L is the thickness of the bony member, and arg[H(f)] evaluates the phase of the complex bone transfer function, H(f). 
     The frequency-dependent specific-attenuation, μ(f i ), and frequency-dependent group-velocity, v g  (f i ), i=1, . . . ,N, serve as inputs into an appropriately configured neural network to generate an estimate of one or more of the above-indicated and currently analyzed bone properties, namely, bone-mineral density, strength, and fracture risk. In the presently preferred embodiment, the neural network is a feedforward network with 30 inputs, 1 output, and one hidden layer which consists of 300 processing elements. The network is trained with the backpropagation algorithm to estimate bone mineral density. 
     The above set of inputs was used to evaluate the ability of the neural network to predict bone mineral density. In this connection, a training set of data was established from 27 bovine trabecular bone cubes for which the ultrasound specific-attenuation, ultrasound group-velocity, and bone mineral density had been measured. Using simple linear regression, the average percent errors for predicting density were 25 and 23 percent for specific-attenuation and group-velocity, respectively. In contrast, the neural network provided a 15 percent error in predicting density, representing about a 40 percent improvement in prediction accuracy. The neural network was able to nonlinearly combine additional information from the specific-attenuation and group-velocity functions compared with the univariate regressions. Moreover, this neural network based approach does not require any a priori information on the functional form relating specific-attenuation and group-velocity to density (or strength or fracture-risk). It extracts this information from the data itself. 
     In a variation of the described procedure, both the frequency-dependent specific-attenuation μ(f i ) and frequency-dependent group-velocity v g  (f i ), i=1, . . . ,N, are modelled with polynomials whose coefficients are obtained using linear-least-squares analysis. These coefficients, i.e., μ 0 , μ 1 , . . . μ M  and v g0 , v g1 , . . . , v gK  serve as inputs to another appropriately configured neural network. In this preferred embodiment, M=2 and K=1, and the neural network is a feedforward network with 5 inputs, 1 output, and one hidden layer consisting of 50 processing elements. The neural network can also be configured to estimate bone strength and/or fracture risk, in addition to bone density. In these cases, different sets of training data are required to specify the neural network. 
     In another variation of the described procedure, the transmitting transducer is adapted for measuring the reflected ultrasound waveform in order to obtain an estimate of the traversed soft-tissue thickness. Reflection measurements are made with a Panametrics (Waltham, Mass.) Pulser/Receiver Model #500 PR which excites the transmitting transducer with a narrow pulse and subsequently measures the reflected waveform. The arrival time of the reflected signal provides a measure of the round-trip transit time, π, for the acoustic pulse to travel from the transducer through the soft-tissue, to the bone surface (where it is partially reflected), and back through the soft tissue. The soft-tissue thickness d s  can then be calculated as 
     
         d.sub.s =v.sub.s τ                                     (7) 
    
     where v s  is the velocity of ultrasound in soft tissue and is given by v s  =1540 ms -1 . Equation (7) includes a factor of two for estimating the soft-tissue thickness on both sides of the bone. 
     The soft-tissue thickness, d s , may then be used to correct the specific-attenuation, μ(f), and group-velocity, v g  (f). These corrections are given by ##EQU5## where μ s  (f) is the specific-attenuation of soft-tissue, and μ corr  (f) and v g ,corr (f) are the soft-tissue corrected frequency-dependent specific-attenuation and soft-tissue corrected frequency-dependent group-velocity, respectively. The soft-tissue specific-attenuation is modelled as a linear function of frequency, namely, μ s  (f)=2×10 -4  f, where f is the frequency in Hz. Application of the above correction equations (8-9) has a relatively small effect on specific-attenuation (about 0.5%-2%) and a larger effect on group-velocity (4%-10%), depending on the relative amount of soft tissue and acoustic properties of the bony member. 
     In another variation of the process of FIG. 2, the transmitting and receiving transducers can both be adapted for pulse-echo mode, in order to obtain a more accurate estimate of total traversed soft-tissue thickness, d s . In this embodiment, individual estimates of the soft-tissue thickness on each side of the bone are made in an identical fashion to that described in the above paragraph, and added together to obtain the final estimate. The corrected specific-attenuation and corrected group-velocity are obtained in an identical fashion as in equations (8-9). 
     In still another variation of the invention, the variance, σ B   2 , of the frequency-dependent specific-attenuation, μ(f), and the variance, σ v   2 , of the frequency-dependent group-velocity, v g  (f), are evaluated on-line. The value of the variance, relative to the mean, can be used to determine the time at which sufficient signal averaging has been achieved. Monitoring of the variance can also be used to indicate lack of precision in the data, and that the experimental conditions must be modified. The expressions for recursively calculating the variances are ##EQU6## 
     In these expressions, μ i  and v gi  are the specific-attenuation and group-velocity associated with data-acquisition i, respectively, while the overbar on each represents the current mean value. By comparing the respective variances with the respective mean values (squared), the number of acquisitions (μ avg  and v avg ) needed to achieve estimates of specific precision can be assessed. For example, in some instances, 1000 acquisitions were required to achieve a relative precision of 0.01 (the ratio of the square root of the variance to mean) in both the specific-attenuation and group-velocity, while in other cases 100 acquisitions were sufficient to attain the same precision. 
     In the second embodiment of the invention, namely, as indicated in the flow diagram of FIG. 3, direct estimation of the frequency-dependent specific-attenuation and frequency-dependent group-velocity is performed. In this embodiment, an input signal which produces an acoustic pulse with a Gaussian envelope is used. The signal which propagates through the reference medium, r(t), is given by 
     
         r(t)=e.sup.σ.spsp.2.sbsp.t.spsp.2 cos(Ω.sup.2.sub.c t.sup.2 +ω.sub.c t+φ.sub.c)                             (12) 
    
     The bone-transfer function is assumed to be reasonably well-modelled by the following second-order polynomial expansion of the phase, Φ(f), and attenuation, A(f) 2  : 
    
     
         H(f)≈e.sup.-[A.sbsp.0.spsp.A.sbsp.1.spsp.2πf+A.sbsp.2.spsp.(2.pi.f).sbsp.2.spsp.] e.sup.-j[Φ.sbsp.0.spsp.+Φ.sbsp.1.spsp.2πf+Φ.sbsp.2.spsp.(2.pi.f).spsp.2.sbsp.]                                        (13) 
    
     With the above Gaussian input signal and bone-transfer function approximation, the signal measured at the receiver is 
     
         s(t)=e.sup.-a.sbsp.0 e.sup.-Δ.spsp.2.sbsp.0.spsp.(t-τ.sbsp.0.spsp.).spsp.2 cos[Ω.sup.2.sub.0 (t-τ.sub.0).sup.2 +ω.sub.o t+Φ.sub.o ]                                                         (14) 
    
     The signal parameters in equation (14) can be written as explicit functions of the input signal parameters and the bone-transfer function parameters. One can invert these relationships to obtain: ##EQU7## Each of these equations may be used sequentially to finally obtain the parameter set {A 2 ,A 1 ,A 0 ,Φ 2 ,Φ 1  }. The expression for the phase Φ 0  is not explicitly shown since it is not used in the calculation of the group-velocity. 
     Direct evaluation of the specific-attenuation and group-velocity functions is obtained through demodulation of the output signal s(t). To accomplish this, the signal s(t) can be passed through a rectifier and a low-pass filter to obtain the envelope, s env  (t): 
     
         s.sub.env (t)=e.sup.-a.sbsp.0 e.sup.-Δ.spsp.2.sbsp.0.spsp.(t-τ.sbsp.0.spsp.).spsp.2 (20) 
    
     A peak detector gives e -a  o (at t=τ 0  ) and the identification of the time at which the maximum occurs gives τ 0 . The time interval between the two half-peak amplitude points gives Δ 0   2 . 
     The zeros of s(t) correspond to ##EQU8## where t n  is the time at which the nth zero occurs. Then by identifying three times t 1  &lt;t 2  &lt;t 3 , corresponding to three zeros of s(t), respectively, we can identify ω 0  and Ω 0   2  : ##EQU9## 
     The foregoing discussion for the variations and embodiments of FIG. 2 has proceeded largely on the basis that digital processing is preferred. In contrast, the discussion for the embodiment of FIG. 3 has proceeded on the basis that analog processing is preferred. It will be understood, however that both respective embodiments and their variations can be implemented through either digital or analog techniques. 
     It will be seen that the described invention meets all stated objectives as to evaluation of the status of bone tissue in vivo, with specific advantages that include but are not limited to the following: 
     (1) Improved signal-to-noise ratio over the prior art, which uses pulse-type input signals. In contrast, a finite-duration composite-sine wave signal is used which takes into account the spectral properties of the bony member and of the ultrasound transducers/measurement system. This allows more accurate estimates of the frequency-dependent specific attenuation function, μ(f), and frequency-dependent group-velocity function, v g  (f), to be made; 
     (2) Incorporation of additional information not used by the prior art, which includes: (a) using both the frequency-dependent specific-attenuation, μ(f), and frequency-dependent group-velocity, v g  (f), functions; (b) taking into account the frequency dependence of the group-velocity v g  (f) as well as the frequency-dependence of the specific-attenuation μ(f); and (c) taking into account the nonlinear frequency-dependence of the specific-attenuation function μ(f) and/or the group-velocity function, v g  (f); 
     (3) Use of an analytic derivation for describing the group-velocity function, v g  (f). This is in contrast to the prior art which uses simple time-of-flight measurements to evaluate ultrasound velocity. Such measurements are not able to characterize the frequency-dependence of the group-velocity, nor are they able to determine at what frequency their pseudo-velocity estimates apply. In contrast, the methods described here are specifically designed to determine the frequency-dependent group-velocity function according to well-characterized mathematical relationships; 
     (4) Sophisticated analysis of the data, in contrast to the prior art which relies largely on simplistic univariate linear regression. In contrast, the processing described relies on neural network technology, which provides multivariate nonlinear analysis to determine the density, strength, and/or fracture risk of bone. This approach also may be regularly updated and improved, as more data becomes available; 
     (5) Capability to obtain in real time and with relatively simple and inexpensive analog-based technology the polynomial coefficients of the frequency-dependent specific attenuation, μ(f), and the frequency-dependent group-velocity, v g  (f); 
     (6) Capability to correct both the frequency-dependent specific-attenuation function, μ(f), and frequency-dependent group-velocity function, v g  (f), for the effects of soft tissue; 
     (7) Capability to assess the degree of variance of the frequency-dependent group-velocity, v g  (f), and the frequency-dependent specific-attentuation, μ(f). In contrast to the prior art, which makes no attempt to adapt to the measurement conditions, this embodiment of the invention adapts to the data ensuring that high quality estimates are obtained; 
     (8) The nature of the apparatus as described here serves best the purposes of further experimentation and exploration for better ultrasound bone data that can be correlated for the indicated objectives. The embodiments of the invention as described above can explore a wide range of experimental configurations. Their use is expected to lead to the development of compact and efficient apparatus for obtaining the indicated objectives. For example, an analog implementation can easily be constructed if economy and simplicity are the primary objectives. Other systems which rely on analog-to-digital converters are more expensive, yet can be more flexible in terms of the type of processing which can be performed. Either type of system can either be built as a stand-alone unit or as part of a PC-based system. 
     Not only does the disclosed apparatus and method meet stated objectives as to bone-tissue evaluation, as noted above, but the same apparatus and method, insofar as they involve signal generation and application to bone tissue, have further useful application to bone-tissue therapy, wherein the exposure time for therapy may extend substantially beyond time required for any given event of bone-tissue evaluation.